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Multiplying investment and retirement knowledge www.projectm-online.com # 17 1/2014 How to use This Cover TO FIND HIDDEN INSIGHTS Follow the instructions below to see the cover come alive. #17 hidden insights The big data boom and how it is transforming life as we know it 1. Choose your device The cover uses augmented reality (AR) to showcase the rapid growth of data generation. The AR is optimized for use on both iOS and Android devices. 2. Scan the QR code to download the Junaio App If not already available on your device, please use the QR code below to download the Junaio app. The app is needed to launch the AR animation. go deeper into the story for tablet and smartphone http:// goo.gl/ d1Wn5x 3. Launch the junaio App and set the right channel Once downloaded, launch the Junaio app and scan the QR code below to set the right channel for the AR animation. Scan the page to see the future Flip the page for more information 4. Scan the cover Scan the cover with your device and the AR animation will launch. Use the four buttons at the bottom of your screen to see hidden insights. Micro One year after launch, NEST is shaking up the UK pension system. Macro Growing inequality mars recovery in the US, says political economist and commentator Robert Reich. Meta 102-year-old Creole singer and trumpeter Lionel Ferbos looks back at a life like few others. Chart Art 2010 The digital universe Rapid expansion: by 2010, computers, devices and human digital activity had generated roughly 1,227 exabytes of data. SE LE CTE D AWARDS for project m print and on l in e FROM 2011-2014 Annual Multimedia Awards: Silver (Websites) Astrid Awards: Grand Award (Best of Cover Design – Magazines); Gold (Covers: Magazines); Silver (Websites: App Launch); Honors (Photography: Repor tage) 2020 By 2020, this As technology advances, data generation accelerates dramatically. The outcome is an expanding and increasingly complex digital universe. amount is expected to have multiplied almost fortyfold, to 40,026 exabytes. MASTHE AD to buy, sell or hold any securit y and shall not be deemed an offer to sell or a solicitation of an offer to buy any securit y. Publisher Allianz SE International Pensions Königinstrasse 28 80802 Munich, Germany projectm@allianz.com w w w.allianz.com · P ROJEC T M is issued in the U.S. by Allianz Global Investors U.S. LLC , an investment adviser registered with the U.S. Securities and E xchange Commission Executive Editor Brigitte Miksa, International Pensions Emerging Markets’ Share Emerging markets take up a growing share of the total amount of data generated by humans and machines. In 2012, total emerging markets share of the digital universe made up around one-third of the generated data. By 2020 it could reach two-thirds. Editorial Board Petra Brandes, Glenn Dial, Dirk Hellmuth, Andreas Hilka, Arne Holzhausen, Tony Hore, Paul Kelash, Sue King, Jens Reisch, Stacy Schaus, Gerhard Scheuenstuhl, Reinhardt Schink, Cathy Smith, Mar y Wadsworth-Darby, John Wallace, Bonnie Wu Editorial Christian Gressner, Lois Hoyal, Greg Langley (EiC), Christine Madden, Oliver Purcell, Marilee Williams Contributors Michael Evans, Renate Finke, Marek Handzel, Paul Hodges, Christof Mascher, Nikhil Mehta, Justin Pugsley, Bernd Scharrer, Stacy Schaus, Jan Oliver Schwarz Publishing Company Burda Creative Group GmbH, Arabellastr. 23, 81925 Munich, Germany Managing Directors: Gregor Vogelsang (COO), Dr. Christian Fill Head of International: Sabine Twest Editors: Geoff Poulton, Leonie Adeane, David Barnwell Senior Managing Editor: Susan Sablowski Editorial Office: Asa Tomash Graphic Design: Michael Helble (Art Director), Andrea Hüls, Michelle Neuhauser (Cover Concept) Production: Wolfram Götz (Dir.), Rüdiger Hergerdt, Silvana Mayrthaler, Cornelia Sauer Photo Editing: Elke Latinovic, Anka Müller Printer: Pinsker Druck und Medien, 84048 Mainburg, Germany Copyright: The contents of this magazine are protected by copyright law. All rights reserved by Allianz SE. Machine-made data Machines and smart devices such as sensors generate growing amounts of data. The percentage share of automated, machinegenerated data has grown from 11% in 2005 to 30% in 2012, and is expected to reach 42% by 2020. 2 • Allianz Best of Corpor ate Publishing: Gold (Financial Ser vices B2B); Gold (Website); Silver (Best Crossmedia Solution) Gal a x y Awards: Gold (Website, Online Media); Honors (Financial Ser vices); Best of Website Grand Award (Online Media) Mercury Awards: Silver (Writing: Thought Leadership); Silver (Custom Publications: Financial Ser vices); Silver (Design: Magazine Financial) W3 Awards: Gold (Website, Online Media) Since f irst being published in 2008, PROJECT M has won a total of 53 corporate publishing awards. Notice: The opinions expressed in the articles in this magazine do not necessarily reflect the views of the publisher or the PROJECT M editorial team. The materials in this publication are based on publicly available sources verified at the time of release. However Allianz SE does not warrant the accuracy, reliability or completeness of any information contained in this publication. Neither Allianz SE nor its employees and deputies will take legal responsibility for any errors or omissions. The magazine is intended for general information purposes only. None of the information should be interpreted as a solicitation, offer or recommendation of any kind. Certain of the statements contained herein may be statements of future expectations and involve known and unknown risks and uncertainties that may cause actual results, performance or events to differ materially from those expressed or implied in such statements. Photo Credits Cover/U2 Peter Riedel; illustrations: Berto Martínez; p.6 - p .11: Agency: JL Design, VFX/Design company: KORB, Client: CCT V; p. 15-17 WorkByKnight; p. 20 Nastplas; p. 22-23 Brian Finke/galler ystock; p. 25-27 Todd McLellan; p. 28 - 3 0 Artwork/Generative Design: Projekttriangle Design Studio, w w w. projekttriangle.com; p. 32 The New York Times/Redux/laif; p. 34 Vincent Fournier/galler ystock, p. 36 - 3 7 Marc Dittrich w w w.marcdittrich.de; p. 38-39 Catherine Balet “Strangers in the light” (Steidl) 2012, p. 40 Stephen Wilkes 2012/from The Human Face of Big Data, Adam Tow; p. 42 David Sisso/ w w w.sissochouela.com.ar; p. 44 Lewis Hine/National Archives & Records Administration USA; p. 45 Abbas/Magnum Photos /Agentur Focus; p. 46 gettyimages; p. 48 - 4 9 Mads Nissen/laif, Sanjit Das/Panos Pictures, Alex Telfer/galler ystock, Shiho Fukada/Panos Pictures, p. 50 Brian Finke/ galler ystock, action press (M); p. 52 ©Warner Brothers; p. 54 Cris Wiegandt; p. 56 Rik Tanner/Contour by Getty Images; p. 59 - 6 0 Todd Antony/ galler ystock; p. 62 Skip Bolen /gettyimages, ddp images Circulation: 6,000 Published: March 2014 PROJECT M is printed on paper certified by the Forest Stewardship Council®. The FSC® certifies that products come from responsibly managed forests and verified recycled sources. Under FSC certification, forests are certified against a set of strict environmental and social standards, and fiber is tracked all the way to the consumer through the chain-of-custody certification system. Impor tant Information · I nvesting involves risk. The value of an investment and the income from it will fluctuate and investors may not get back the principal invested. Past performance is not indicative of future performance. · T his document does not constitute investment advice or a recommendation making of the cover To subscribe to PROJECT M or provide feedback, contact: The PROJECT M cover was created to visualize the expansion of the digital universe. To do so, raw growth-projection data was fed into a computer program. The program then generated 3-D visualization models of the growth between today and 2020, at which time the combined data volume is expected to exceed 40,000 exabytes – or 40,000 billion gigabytes. (Artwork/Generative Design: Peter Riedel – www.peterriedel.com) projectm@allianz.com www.projectm-online.com Allianz • 63 Opening Bell Brigitte Miksa Head of International Pensions Finding value from the chatter “Everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it. …” D i s c ov e r P RO J ECT M f o r tab l e t a n d s ma r t p h o n e Want more? Find these icons printed throughout the magazine, and download the PROJECT M app to explore bonus multimedia content. Picture Gallery Video Audio When behavioral economist Dan Ariely posted his comment on Facebook last year, he poked fun at the ‘big data’ hype by comparing it to teenage sex. With 1,676 likes and 82 comments, few of them disagreeing, Ariely’s quip caused hardly a ripple on the ocean of information. The chatter about big data, the collection and analysis of petabytes of information, had exploded in mid-2011. Worldwide Google searches for the term, coined nearly a decade earlier in astronomy and genomics, have increased almost by a factor of 10 over the past three years. Yet, despite Ariely’s cynicism, there is far more to big data than just talk. Both humans and machines are creating a swelling sea of information by churning out facts which describe their very life cycle – be it the millions of photos uploaded hourly to social media networks like Facebook, or the terabytes of data that machines like jet engines create during a 60-minute flight. Once digitalized, the amount of information doubles roughly every three years, reducing its analog cousin to irrelevance. But big data is not just about quantity, it’s about applying mathematics and increasingly sophisticated algorithms to extract hidden insights and meaning from enormous amounts of unstructured information. Aided by sufficient computing power, analysts can now plow through nearly any amount and diversity of information in search of probabilities and, by logical extension, predictions. While Ariely is right to point a finger at the excitement that goes with this modern-day treasure hunt, big data is bringing sweeping changes to all aspects of life. This edition of PROJECT M sets out to trace and analyze the potential as well as the particular challenges this will likely bring to the financial industry. Yours sincerely, Brigitte Miksa, March 2014 Allianz • 3 Contents Contents MICRO FOCUS (I s s ue s in d e pt h) ( Local kn owledge) Hidden insights 06 –11 Hidden insights Big data and digitalization turn both business and private life upside down. 12 –14 Conference call: Drilling for insights DJ Patil and Sean Gourley debate the impact of big data with Ralf Schneider. 15–17 Crunching sense out of big data Asking the right questions is critical in the search for hidden value in vast data sets. 18 If … then Privacy and security expert Fred H. Cate on developing a rational approach to big data. 19–21 Exploring the future Jan-Oliver Schwarz on the role of scenario planning in the financial services sector. 22–23 Back to the future of insurance Berlin-based friendsurance.de takes aim at disrupting the insurance market. 24 –27 Reshaping the industry New technologies, big data and digital change are disrupting an entire industry. 44–45 28–30 What’s in it for the customer? Christof Mascher on how technology can be used to build customer trust. 31–33 Minority warning Just because we can doesn’t mean we should, says Viktor Mayer-Schönberger. 34–35 Automating advice Stacy Schaus on balancing automated advice with sound investment strategies. 36 –37 Fast-forward The Allianz Digital Accelerator works to keep ahead of the digital curve. 38– 40 Watching the world develop a nervous system Photographer Rick Smolan on the profound impact of big data in everyday life. 41–43 Strength in numbers Carolyn McGregor’s Artemis project uses human data output to detect diseases and save lives. Blurred picture Children across the globe often work more than they study. Still, the case against child labor isn’t as straightforward as some may think, says Eric V. Edmonds. 46 – 47 Auto-enrollment shakes up UK pensions The NEST auto-enrollment scheme targets a looming financial crisis in an aging population by getting more people to save for their pensions. 48–49 Can elderly well-being be measured – and maintained? Research can assist policy-makers across the world in developing responses to mass aging. Approaches, however, vary greatly. MACRO ( Global opportu n i ti es) 50 – 52 Wired on economics The hit TV show The Wire tells us more about economics than most dry analyses, argues economist Peter Antonioni. 53 From the labs The price of the average data breach is going up while the price for storing data is going down. Digitalization is changing all facets of business as we know it. 54 – 55 China’s currency steps onto the world stage The renminbi plays a central role in China’s rise to economic power. Foreign investors, however, are still not entirely convinced. 56–58 Inequality for all The US recovery is gathering pace, but too few people are feeling the benefits, argues political economist, filmmaker and commentator Robert Reich. 59–61 Population aging creates capital repayment risks for government bonds To avoid the growing risk of bond-repayment default, governments must find new, sustainable models. thought leaders in this issue meta ( Th e ou tsi der’s vi ew) 62 DJ Patil Data-oriented company culture is essential. Page 12 Viktor Mayer-Schönberger Human reliance on big data remains a challenge. Page 31 Carolyn McGregor Using human data to generate insights that can save lives. Page 41 Robert Reich Why growing inequality is a threat to financial recovery. Page 56 The old man and the Cs At 102, Creole singer and trumpeter Lionel Ferbos is a local legend and the oldest actively working musician in the jazz capital of the world, New Orleans. 63 Masthead 4 • Allianz Allianz • 5 Focus Is sues in depth Hidden insights The explosion in information-gathering is leading to unprecedented ways of collecting and combining vast new sets of data – a resource with huge potential. What impact will this have on industry, medicine, social and political policy – as well as the private individual? W ith rain in the air and time to kill, you head into a department store to do a little shopping. As you enter, security cameras record your arrival, while a shopper-tracking camera later records exactly how much time you spend looking at shoes. After deciding on a pair, you head to the till and join the queue. Waiting to pay, you pull out your smartphone, which constantly feeds your movements and location via GPS back to the cell phone provider. Feeling proud of your purchase, you post a picture on Facebook, which automatically logs your time and location. Your credit card transaction then registers your payment with the card supplier, while the loyalty card allows the store to track your spending habits. As you leave, you call a friend – another action duly noted by your phone carrier. In a matter of minutes, your mundane everyday actions have left a trail of data that reveals more about who you are 6 • Allianz and what you do – and what you’re likely to do – than you can possibly imagine. Around the world, millions of others are doing the same – constantly adding to an ever-growing universe of raw data. Whether we like it or not, we’re all cogs in this new universe. That may be an uncomfortable prospect, but it’s one we quickly need to come to terms with, as opting out is nearly impossible. » T he insights that data can reveal are changing the nature of business, markets and the societies in which we live. « The growth of this digital universe is exploding: the pervasive use of digital devices and social media is expected to increase the rate of data production to be 50 times greater in 2020 than in 2010, according to the information technology firm IDC. Yet, currently only 0.5% of the world’s data is being used for analysis, the IDC says, despite a quarter of it – rising to a third in 2020 – containing potentially useful information. This untapped value could be found in anything, such as “patterns in social media usage, correlations in scientific data from discrete studies, medical information intersected with sociological data or faces in security footage,” the IDC wrote in The Digital Universe in 2020. Is the quantification of our lives something to fear or embrace? Already making its impact known, the ‘big data’ universe has the potential to alter almost every aspect of our lives. Companies and organizations are sorting through masses of information to extract unexpected correlations and surprising connections. By knowing more about us, they can cleverly offer innovations and more tailored services, from book recommendations and meal vouchers to loans and insurance policies. Legitimate privacy concerns The insights that this data can reveal are changing the nature of business, markets and the societies in which we live. Take health: big data can reveal previously hidden patterns relating to the causes of disease and the effects of different treatments in order to enable better, more costeffective healthcare. However, there are pitfalls. Edward Snowden’s revelations on the extent of government surveillance of the digital activity of hundreds of millions of people raise concerns over data privacy and security that are legitimate. Viktor Mayer-Schönberger, co-author of the book BIG DATA, cautions against over-relying on data when predicting future events (see pages 31–33). Big data provides correlations but does not comprehend the Allianz • 7 Focus Video Bonus content in the PROJECT M app Focus We leave a distinct data exhaust: digital activity is spurring immense growth in data generation, allowing us to track and analyze nearly all aspects of contemporary life. concept of cause and effect. Data-driven observations may have the power to change the world, but human interpretation will remain an irreplaceable factor in our increasingly digital universe. Unlocking the value contained in data As data-driven industries, the potential for change in the finance and insurance sectors is enormous. Longestablished business models based on face-to-face interactions are being revolutionized by social media and digital devices, while the ability to access and interpret a wealth of new information about existing and potential clients is opening opportunities for competitors. Cloud technology has made it possible for firms to store vast amounts of information. In the past, most of this was rigidly structured – sheets of numbers, for example. Now, information is more chaotic: photographs, films, text, speech or social media streams could all contain valuable insights on anything from market movements to demographic trends. As Volker Stümpflen, CEO of data analytics firm Clueda, explains, the key to unlocking the value in the data lies in asking the right questions (see pages 15–17). By using a complex series of algorithms and visualization tools, companies such as Clueda are quickly able to analyze huge amounts of information on a scale far beyond what the human brain could achieve. Data leads to tailor-made solutions Banks and credit card associations are using algorithms to examine millions of transactions every day to look for unusual patterns indicating fraud, but they can also predict things like the probability of divorce as much as two years in advance – with startling accuracy. By improving their ability to anticipate changing market conditions and customer preferences, financial organizations can also deliver new customer-centric products and services. The age of relying on focus groups or averages to determine decisions is disappearing. In Singapore, when select Citigroup customers swipe their credit card, the company notes the time and location, and combines it with data on a customer’s previous spending habits. Based on this, it can almost instantly send a personalized discount for a suitable nearby shop or restaurant via its mobile banking app, potentially gaining a cut on a further transaction. The system is even able to learn and improve offers based on performance. And 8 • Allianz Allianz • 9 Focus Find out the ways you may be a leaving a data trail at projectm-online.com for every Citigroup, there are countless startups eager to take advantage of the potential of big data. The changing face of social media With the phenomenal increase in data collected and the ingenuity of its usage, companies that already have access to the largest quantities of information could move into new spheres of activity, providing further competition to established players. While Facebook, Google and Amazon have yet to show signs of entering the world of finance and insurance, others have already made their move. The UK’s largest supermarket chain, Tesco, launched its own banking service five years ago, offering insurance, credit cards and loans, with plans to introduce current accounts in 2014. Combined with loyalty card spending data, the store has a considerable picture of many of its customer’s lives, giving it the chance to assess accurately creditworthiness and offer targeted cross-selling. In using personal data to sell products, though, firms must exercise caution not to alarm customers or even risk legal action. While some may balk at allowing a single company such a detailed insight into their daily lives, the number of customer accounts – 6.8 million, and rising – suggests Tesco’s banking model could be here to stay. With few brick-and-mortar branches and an emphasis on online service, it is just one example of how the digital world is transforming our relationship with providers. Integral in this is the growth of social media – a doubleedged sword for businesses. While reaching new and existing customers has never been easier, different customers require different channels of communication and a prompt response. They are also able to assess information and spread opinions quickly on products, prices and services. The increase in virtual communication, however, has strengthened online communities, allowing some companies to provide a fresh take on a concept that dates back to the beginning of the insurance industry. Based in Berlin, friendsurance, for instance, allows users to share risks and costs within their own communities, no matter where people are geographically (see pages 22–23). 10 • Allianz Health benefits and saving lives By harnessing the power of the digital universe, firms can create better, more personalized consumer products, save customers time and money, and drive profit margins. But by discovering more about how humans function, data can also help improve our health and save lives. Our bodies give off thousands of different data signals every second, most of which go unnoticed and unrecorded. But within this data lies potentially crucial information about our physical health. Technology has recently enabled people to monitor and analyze a small selection of data related to their own everyday activities. These wearable devices, in the form of small bracelets, give an insight into what happens when we exercise, eat and sleep. Regular users form part of a growing ‘quantified self’ movement, many of whom upload data and exchange tips and advice in online forums. A more powerful impact can be seen in the work of Dr. Carolyn McGregor (see pages 41–43). In collaboration with IBM, McGregor and her team are developing Artemis, a platform that captures and processes more than 1,000 data points a second for prematurely born babies. By identifying patterns in the data, McGregor hopes the system will allow doctors to detect slight changes in their vulnerable patients that may signal the onset of a potentially deadly infection. The more we quantify our body’s individual make-up, the more personalized the service we can receive. This ultimately leads to more effective preventative care and treatment. As Dr. Craig Feied, professor of emergency medicine at Georgetown University, points out, there is a lot of information about patients that doctors are simply unaware of. “If this were a game of Jeopardy, the category ‘Things Your Doctor Doesn’t Know’ would have so many entries that it’s scary to think about.” By providing doctors with more information, we should be able to live longer, higher-quality lives. As we begin to get to grips with the vast potential of the digital universe, we see how data is creating knowledge to help predict the future, rather than just understand the past. But we must remember that it is a tool and not a crystal ball. Data can help us to understand, but it cannot provide all the answers – and human interpretation remains vital. before big data and after The one thing we can be sure of is that the amount of data will continue to grow. While it can offer tailored products, better lifestyles and improved healthcare, its use must be regulated to protect citizens. The responsibility for this lies not just with lawmakers, but also with the private sector as creators and keepers of a large proportion of this data. The Internet has redefined how the world communicates, but big data is changing the way we understand the world. Rick Smolan, photographer and publisher of the book The Human Face of Big Data (see pages 38–40), compares it to the world developing a nervous system. He believes we are standing at a major period of demarcation in our history – “before big data and after.” Allianz • 11 Focus Focus Drilling for insights Big data is without doubt a promising resource, but the guidelines for extracting and ref ining it still have to be written. Handled with care, data securit y and data privacy will become a competitive advantage for companies. » PALO ALTO CALIFORNIA SAN FRANCISCO CALIFORNIA MUNICH Germany DJ Patil Data Scientist, Greylock Partners Known for coining the term “data scientist” together with Jeff Hammerbacher, founder of data analytics company Cloudera, DJ has worked at LinkedIn Corporation, Skype, PayPal and eBay. As a University of Maryland faculty member, he focused on nonlinear dynamics and chaos theory. DJ worked with the US Department of Defense to prevent the proliferation of bioweapons. In 2011, Forbes ranked him and Jeff Hammerbacher as the #2 data scientists, second only to Google’s co-founder Larry Page. Sean Gourley Chief Technology Officer, Quid With a PhD in physics from Oxford University, Sean has worked in fields as diverse as nanotechnology and the mathematics of war. He has advised the Iraqi government, briefed the Pentagon and addressed the United Nations. In his spare time, he studies string theory and occasionally returns to the simpler world of track and field. Ralf Schneider Chief Information Officer, Allianz SE A mathematician with a PhD in information technology, Ralf was named Allianz Chief Information Officer in 2010. With prior experience at a midsized consulting firm and as a sales manager for Allianz, Ralf now focuses on providing a standardized IT platform to a global company. 12 • Allianz Schneider: Gentlemen, big data has become one of the world’s most important resources. In a way, it resembles oil: it needs to be extracted, refined and used responsibly to make full use of its value. What is your take on the current discussion? Patil: Behavioral economist Dan Ariely once compared big data to teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it. “Do you have a big data strategy?” is now the hip question to ask at cocktail parties, replacing “Do you have a social media strategy?” However, its opportunities, as well as its risks, have to be taken seriously. Gourley: There is a lot of hot air in the discussion, but you can’t ignore it. The analysis of information created by our everyday use of computers very likely alters the way we live. One economic consequence is that granular information about individual preferences can improve pricing structures and increase cost efficiency across all sectors by 5% to 10%. Schneider: The sheer size of data makes the topic impossible to ignore, particularly for insurers. We expect the amount of data to increase by factor 40 over the next 10 years. At the same time, computing power continues to grow exponentially, allowing us to refine the data in a sensible and responsible manner. But let me briefly define big data for the purpose of this conversation as proprietary information generated and owned by an agent – for example, a company. In a second step, the information is analyzed, possibly in conjunction with additional data gathered from outside sources. Patil: That works for me. And you’re right, Sean, there’s more than just talk. Agriculture company Monsanto, for instance, just paid approximately a billion dollars to acquire Climate Corporation, a company that analyzes data to provide crop insurance to farmers. On the other hand, there are clear risks to big data, and we’re struggling to define good practice. What is best practice at your company, Ralf? Schneider: At Allianz, we do less than we could. We now have the ability to analyze multitudes of unstructured, unrelated texts and figures from various sources with a varying degree of accuracy. Its quantity allows us to accept a degree of imprecision, and the advantage of big data is that we are now in a position to extract meaning from such messy information. We also have more accurate predictors for the risks we insure. The danger is to rely too much on correlations which say nothing about actual causality. Gourley: The predictors may become as detailed as how a person’s education and driving style affect the premium of his car insurance. Schneider: True, but the concept of insurance can only function if risk is distributed across various members of a group. For insurers, information analysis has always been at the core of understanding the risks they accept. So while this is not new, the basis for finding new patterns has expanded. However, neither the patterns nor the data are personalized. What we can do is show how a group with similar age, gender and education behaves – to the benefit of our clients. Big data enhances our ability to identify and respond to individual customer’s needs. Gourley: Can you give us an example? Schneider: Sure. Take liability insurance fraud. These cases often share common patterns: they take place in the home of the insured, with visitors; most objects reported as broken are alike; and the relationship between the insured and the culprit is similar, too. If a claim seems suspicious, we look for aberrations in the patterns to confirm our initial suspicion. Apart from that, do you T he sheer size of data makes the topic impossible to ignore, particularly for insurers. Ralf Schneider « Allianz • 13 Focus » S imilar to gentlemen have any advice on how insurers should handle big data? Patil: I recommend that larger corporations in general do a data review just like they do a risk review before they roll out a major project. Schneider: What exactly do you mean? Patil: Just because we can with data, doesn’t mean we should. Every company should have an internal process of data checks and balances in place that allows them to make use of big data in a responsible manner. Similar to physicians, big data users need to make efforts to ensure they are acting in an ethical manner. Schneider: Absolutely. Increasing opportunities also bring growing responsibilities. The question for us is not “What is the legal maximum?” but “Do we want to do everything that is legal?” My answer is no, and I am convinced that data privacy and data security will eventually become a competitive advantage. In the meantime, we’re focusing on building an appropriate IT infrastructure throughout our global organization to safeguard our clients’ data. Gourley: I think it comes down to money and transparency. If a company makes money thanks to their customers’ data, they ought to be up front about it and willing to share some of that profit with those who made it possible in the first place: the people generating the data. In the long run, this will increase clients’ trust, counter Big Brotherlike concerns and enable us all to make the most of big data. Patil: A data-oriented company culture is essential. The best data-driven companies start with what we call “silenced sustained data reading” where they take 15 minutes just to look at the data. Once that is complete, then they can dig into the questions. It’s about being intellectually honest as a team. Data is a team sport, and it will play out its benefits when it’s 14 • Allianz democratized – that is, when accessed by various entities within a company. Schneider: So far, we spoke about technology and its potential. What role will humans play? Patil: I think this is a false dichotomy. Humans have one great advantage over technology: intuition. The best data scientist is one who brings intuition and information together and moves effortlessly between both areas. Schneider: That’s for those of us who are prepared to work with data. What about the rest? Patil: Well, it is the data scientist’s job to make data accessible. From then on, almost everyone can be educated to deal with data. And we have already done this successfully with technology. I can’t think of a single three-yearold who is incapable of using an iPad. Gourley: Owning the information and the computing power is not enough. That’s like having a Ferrari in the garage but no idea how to drive it. To get the most out of large quantities of data, human expertise – with the support of algorithms – needs to structure it in a meaningful way. The interpretation of data and its patterns will remain a human task. Schneider: How do you see the future of big data evolving, Sean? Gourley: I see three major trends. First, I expect people to demand more value back if their data is used to generate profits. Second, we will see more visualization, so interfacing with big data will become easier. Lastly, there will be a move from prediction to persuasion engines. While predictions like that of Nate Silver’s 2012 US election outcome are impressive, they forecast the future based on past actions. More interestingly, we could arrive at a choice of future scenarios independent of the past. I tend to think of this as persuasion engines, rather than prediction engines. Schneider: That is very futuristic indeed. Thank you very much for your time and insights, Gentlemen. physicians, big data users need to make sure they are acting in an ethical manner. DJ patil « Picture Galler y Bonus content in the PROJECT M app Focus Crunching sense out of Big Data We may have more information than ever before, but it’s meaningless without structure. Companies such as Quid and Clueda help us ask the right questions to extract insights from chaos. A the big picture Technology companies are trying to bring clarity to huge amounts of data available in different formats. s technology advances at breakneck speed, building up an avalanche of data, how does one make sense of the vast amounts of information crowding into everyday life? A number of companies and start-ups have taken on the ambitious task of developing digital riggings and computational knowhow powerful enough to offer much-needed clarity. They aim to build algorithms and visualization tools that can crunch enormous amounts of information at incredible speed. This way, they can assist clients in asking the right questions of their data. data-driven insights One of the companies operating at the crest of the big data revolution is Quid, a San Francisco analytics firm founded by entrepreneur and Oxford-educated physicist Sean Gourley four years ago. Already a fixture in a fast-growing industry, Quid works with technolog y giants, government agencies and financial-service providers to deliver astute data-driven insights that can lead to crucial strategic and analytic decisions. “We have built an intelligence platform that people can plug into in order to understand the complexities of the world around them,” Gourley explains. “It’s an ambitious project.” scaling information mountains The input for Quid’s analytic products varies from scientific journals and files through financial transactions to court documents – mountains of information that would other wise be impossible for the human mind to handle. The result arrives on the client’s desk in the form of advanced, interactive, three-dimensional visualizations and graph structures that represent an intuitive, deeper grasp of the problem at hand. “What we offer is a high-dimensional mapping structure that provides an understanding of an industry, a scientific field or even a political space,” Gourley explains. “It’s structuring of information through algorithms and computational cognitive power – a replication of what an expert does when establishing relations Allianz • 15 Focus and connections in information, but on a larger and much more complex scale.” Tapping into huge amounts of data in a focused way presents enormous advantages to companies and institutions. An investor can, for instance, gain invaluable insights that help him stay ahead of the curve and, ultimately, the competition. Gourley is reluctant to talk about hard numbers, instead emphasizing “the beauty” of drawing meaning from unstructured information. “I’m very excited these days. We get to work with everyone from hedge funds to nonprofits, and they are all now able to plug in and better understand the complexities, connections and contexts of the world around them through data. It’s incredible to see this happening.” removing junk and noise Clueda, an innovative software developer and manufacturer in Munich, offers a similar service, but with a focus on the healthcare and financial-service sectors, while also planning a jump into social media analytics in the near future. Operating under the slogan “Beyond Big Data,” CEO and founder Volker Stümpflen describes his service as “associate knowledge processing.” But his mission remains the same as Gourley’s: extracting meaning from the chaos of big data. The Clueda method is based on models from cognitive science and brain research and has been refined for the past 10 years. Today, the company can produce accurate reports and visualizations on a host of topics, fields and relations, based on the targeted analysis of mind-boggling amounts of input. “There is a lot of junk and noise in big data,” argues Stümpflen. “The idea used to be that you just needed to collect a lot of data and new knowledge would come from it. Now we know that you have to remove this junk and noise for anything to be meaningful, and to find answers.” semantic analysis Clueda’s input comes from all kinds of unstructured information, Stümpflen further explains. “Our algorithms are self-learning 16 • Allianz Focus and scale easily,” he says, “so we expect to include photographs, films, recorded speech and social media streams in the future through semantic analysis and mapping of relations in social networks.” Their output can be delivered extremely fast to benefit, for example, stock traders who need information speedily, or healthcare companies that seek detailed knowledge on product impact in specific markets under specific conditions. The parameters are essentially endless. But by structuring data analysis around key bits of information and their reach, the method “effectively transforms clusters of untidy data into detailed tangible outcomes that can help decision-making,” Stümpflen says. In this data-driven field, constantly widened by advancing technologies and self-learning algorithms, the role of the human being becomes another burning question. Computerized big data analysis may help derive meaning from oceans of shapeless knowledge, but what part does good, old-fashioned human cognitive skill play in this puzzle? human involvement “We still need humans to interpret the outcomes of analysis,” says Gourley. “This, however, is not a skill that everyone has. I think that we will see a schism developing in terms of skills in the near future. There will be people who are capable of working with big data, and people who aren’t.” Stümpf len, whose algorithms are deliberately built to imitate the human mind, also sees human involvement as vital in asking the right questions and understanding the answers that arise. “Humans are exceedingly good at connecting the dots,” Stümpflen says. “There are lots of examples where cause and relation are seemingly clear. But by asking the right questions, we can eliminate this idea of automatic correlations and look beyond them to make the right connections with the analyses we do. The answers are only useful because of the contexts in which they are put to work. And in understanding these patterns, humans continue to play the leading role.” » w e will still need humans to interpret the outcome of analysis. this, however, is not a skill that everyone has. volker stümpflen « Making sense of complex data still relies on human query and analysis. Focus Focus Fred H. Cate Professor of Law at Indiana University and Director of the Center for Applied Cybersecurity Research Data privacy and security expert Fred H. Cate calls for a rational approach to the excess of data we generate in the digital world. IF T h en IF you prefer to conduct this telephone interview over the hotel’s landline, I can call back. THEN my decision is based on the connection’s quality, not its data privacy. I do use a mobile phone, including Google Maps’ location service, which leaves a large digital footprint. But I decided not to use Facebook. IF governments and private-sector firms collect more and more data on individual behavior, what will this mean for individuals’ rights? THEN we have to put appropriate oversight mechanisms in place. The collection needs to be monitored and an appeals process established to challenge decisions based on this data. IF that leaves a feeling of unease with most people … THEN I say big data is not necessarily a bad thing. We are constantly judged on often incomplete information. Depending on my zip code, my car insurance may be more expensive than yours for reasons that have more to do with my neighbor’s driving abilities than my own. IF big data provides a more comprehensive and accurate understanding, what are its risks? THEN we have to be wary not to become overly enthusiastic. Governments and companies should continually question their data’s accuracy. This – as well as the decision-making process based on big data – needs to be subject to external checks and balances. IF you consider the debate over Edward Snowden and the National Security Agency, what are the implications? THEN the NSA is exploiting ambiguities in the current legislation. While I do not condone stealing confidential information, Snowden deserves credit for initiating the necessary public debate. IF you look ahead, what will be one of the challenges concerning privacy? THEN we can do better. We have come to accept outdated legislation, but there is no need to rely on 20-year-old data privacy laws. To listen to a recording of the interview with Fred H. Cate, please go to PROJECT M online: projectm-online.com/new-perspectives/if-then-fred-cate 18 • Allianz Focus EXPLORING THE FUTURE The future is largely unknown, but that doesn’t mean you can’t try to work out what might happen next. This is where scenario planning comes in. Scenario planning is based on the premise that you can work out likely variations of the future by analyzing the main drivers shaping the present. By Jan Oliver Schwarz, Allianz Strategist I f you could travel forward in time to the next decade, what would you see? A world radically different or one scarcely changed from the present? Nobody knows, but one thing seems to be sure: we will live in an increasingly digital world, where the Internet and smartphone will reign supreme. Tomorrow’s youth won’t be able to contemplate a world before the iPhone or research information without Wikipedia’s or Google’s help. Just what form this digitally dominated world will take depends largely on two factors. First, how online communities develop will have a huge impact. These might remain communities where people simply exchange private messages and pictures. Alternatively, these communities might play an influential role in the business world, with people turning to them first for financial advice, as they do currently for travel tips. Second, game-changing technology will likely alter the way we communicate and use the Internet. For instance, semantic technology, namely the intelligent linking of data from a huge number of different databases, will be able to transform the Internet into an intelligent vehicle and answer a search query in a direct and relevant way by relating your latest search query to previous searches. exploring future scenarios Using the scenario-planning approach, we came up with four scenarios to depict possible variations of a digitalized future. The first scenario, ‘Brave World on the Move,’ is conservative and envisions a world barely different from the present day, but with more prevalent Internet and mobile-phone usage. In this imagined world, people would still seek out an insurance agent to discuss queries or a financial advisor to talk about the state of their finances. » [online] communities might play an influential role in the business world, with people turning to them first for financial advice, as they do currently for tr avel tips. « The second, dubbed ‘Trust in Virtual Communities,’ anticipates virtual communities playing a far more dominant role. In this scenario, people would turn to the Internet more often to seek advice and exchange ideas, also concerning business and financial matters. Consumers would become active content providers, distributing content valued by their peers as sound advice. Digitalization would further evolve and play a vital role in everybody’s day-to-day life. The most progressive scenario, called ‘Good Morning, Intelligence,’ takes this a step further. It visualizes a virtual world, which responds smartly to the needs Allianz • 19 Focus of active consumers. In this future scenario, gamechanging technological advances, such as semantic technology, would lead to new ways of doing business and of compiling knowledge. Autonomous and self-driven customers would easily find the information they seek online, preferring to rely on the opinion circulated within a social web-based community rather than that of a qualified expert. To stay on top of digital advances, financial institutions will have to piece together different approaches to clients’ needs. CHALLENGE FOR FINANCIAL SERVICES This shift towards a virtual world would present a tough scenario for the financial services industry, which still depends on giving advice to people. It would be confronted with customers who could access the advanced information they need from the Internet and shun face-toface interaction with a financial advisor. Furthermore, clients would order customized products based on their own ideas and needs. And an increasing number of people would work from home. The scenario ‘High Tech and Real Friends,’ meanwhile, visualizes a more moderate world, one which has become more virtual, but where human contact and exchanging ideas with another person is still valued and people still place their trust in identifiable experts and institutions. Here, semantic technology would support humans in an intelligent way. This world incorporates the so-called ROPO effect – ‘research online, purchase offline’ – in which people research the products or services they want to buy online before going in person to a branch or shop to close a contract or buy goods. Financial institutions in this world would need to be easily accessible online, offering transparent information, products and prices. And insurance companies would need to be present on ‘aggregator websites,’ where people could easily compare policies. Contact with customers would remain important. This currently popular approach is widely predicted to become more dominant: it has already been adopted by Spanish banks such as BBVA, which, as well as building up its digital channel, has radically redesigned its branches to attract back customers and not lose that vital personal contact. One of BBVA’s touchscreen ATMs has even made it into the Museum of Modern Art in New York. GIANTS BATTLE WITH INSURERS If financial service providers want to gear up for these future challenges, insurance and financial-service companies need to be prepared. They will need to face competition, which may present itself in new guises, such as that presented by Amazon and Google. Amazon has already started making inroads into the insurance industry, offering extended warranties in some countries when you purchase a product. Meanwhile, Google, the world’s largest search engine,has launched its own carinsurance comparison site. Fortunately, these Internet giants are unlikely to develop a huge appetite for taking on the underlying financial risks, although they may end up capturing the points of direct interaction with the client – arguably the sweet spot in the financial-service value chain. In order to compete effectively in a digitalized world, companies will need to be present where their customers are. Insurers and financial service providers will need to offer customers different access routes to get in touch with them. Someone young will want to access up-front information easily online, while some elderly clients will prefer to go into an agency or branch and talk to an individual. » i n order to compete effectively in a digitalized world, companies will need to be present where their customers are. « Even future younger generations will probably still value human interaction when it comes to taking financial investment or protection decisions. But tomorrow’s customers will undoubtedly have a vast amount of intelligence, data and knowledge at their disposal, meaning that companies would need to provide even more expert and tailored knowledge to compete. If online communities continue to grow in importance, we might see the return of peer-to-peer or mutual insurance, where people insure each other and set risk selection within their communities. This would hark back to the very beginning of the insurance industry. After all, history often repeats itself. Allianz • 21 Focus Focus Back to the future of insurance as big data, could lead to better cost controls and more efficient delivery of services, he believes. Progressive Group of Insurance Companies is one of the forerunners when it comes to use of data. In 1999, the US insurer offered Texan customers a trial program called Autograph, which tracked driving styles. Today, the firm monitors driving days and times, higher versus lower speeds and braking styles in Snapshot, a voluntary program rolled out nationally in the US in 2008 and 2009. Premiums are discounted for careful drivers, as they are less likely to be involved in crashes, according to Progressive. While other information is monitored, the actual location of the car is deliberately ignored. The company initially placed a surcharge of 9% on what it considered bad driving; this has been abandoned. Seven out of 10 participating customers now receive a discount – on average of about $150 – with Snapshot. There is demand for usage-based insurance (UBI). Nearly 90% of respondents were interested in buying UBI products if the premium did not increase, a recent survey by consultancy Towers Watson found (Usage-Based Insurance Consumer Sur vey. Understanding What Customers Want, 2013). Interest was particularly high among younger drivers, whose car insurance premiums are among the highest. A network of friends is the key to a new, highly innovative and mutually beneficial type of insurance – with less risk. With the help of both real and virtual friends, the cost of insurance could be brought down while keeping clients’ risk exposure low. But many insurers are still shying away from social media. I t had to be Berlin for Tim Kunde and friends. “We aim to be a game changer for the insurance industry. For that, we chose to be close to Berlin’s buzzing Internet community,” Kunde tells PROJECT M in his fifth-floor, shared office. With exposed brick walls and the back entrance half blocked by construction work, the building oozes Berlin ambience. With the help of his two partners, Kunde, formerly an employee of Boston Consulting Group, founded friendsurance.de, an insurance brokerage cum social media network, where a circle of both real and virtual ‘friends’ share the excess of damages to a person’s car or mobile phone before traditional insurance pays the rest of the claim. Business: casual Attired in blue jeans and a pullover and sporting a patchy beard, Kunde needs to walk a fine line with his company to attract tech-lovers as clients and traditional insurers as partners. “This sector has not seen much innovation over the last decades. Yet we are realistic enough to know that clients look for solidity and reliability when it comes to insurance.” Selling the household, personal-liability and legalexpenses insurance of partnering companies such as AXA, ARAG and others on commission*, friendsurance promises users – typically known as ‘clients’ by the industry – low contributions in exchange for high deductibles. “We use the mechanics of the deductible to lower cost while its risk is shared across a community of friends,” says Kunde. Growing the network of registered friends automatically changes the tariff to include a higher deductible. As the risk of claims is reduced on the insurer’s side, premiums are lowered. The savings are retained by friendsurance to cover damage costs under the deductible with a contribution of up to €30 ($41) per friend. If the group remains accidentfree throughout the year, part of the pot is paid out. While the same product can be bought directly from the insurer, thereby cutting out friendsurance as the middleman, clients would have to shoulder the higher deductible without the help of friends. “The vast majority of customers in the German-speaking countries are too riskaverse to do that and can benefit from our approach,” Kunde says. Founded in 2010, the 40-employee start-up has since established itself as a distributor of off-the-rack insurance products to thousands of users with an average age of 30 to 35. “But,” adds Kunde, “innovation does not yet happen on the product side.” INSURANCE AGENT IN THE BACK SEAT Next to health care and energy, insurance is the sector most likely to profit from spreading digitalization and rising amounts of data. It is “about to explode” with uses for big data, said Google’s executive chairman Eric E. Schmidt late last year. The mining and processing of petabytes (1015 bytes) of information, often referred to PREVENTING FRAUD BEFORE IT HAPPENS Despite early adopters like Progressive, a discrepancy still exists in the industry, according to Craig Beattie, senior analyst with Celent, a consultant agency focusing on information technology in the financial services sector. “Every insurer we speak to says that, if the right flags are raised, social media information will be reviewed to settle the claim. On the other hand, firms lock down websites like Facebook on company computers, indicating that social media is not part of the insurance business,” says the author of the report Using Social Data in Claims and Underwriting (2011). Social elements can even help prevent fraud from taking place, Kunde adds. Knowing that it will harm the circle of friends, friendsurance users are unlikely to exaggerate claims, he says. New users also tend to seek out friends they believe to be more prudent. For the group, such behavior will lower premiums, as well as pay-outs and administrative costs for the insurer. “Social media elements can have a dual effect on insurance,” Kunde says. “By reverting back to the original concept of mutual support, costs can be reduced for all parties involved.” * Allianz, the publisher of PROJEC T M, is in dialogue with f riendsurance.de, but not a par tner. 22 • Allianz Allianz • 23 Focus Focus Reshaping the industry Big data and new technologies pose great challenges to the financial services sector, but could also help redefine an entire industry. E arlier this year, the Wall Street Journal’s blog aimed at chief information officers published a selfcongratulatory post about the use of big data by financial services firms. The post’s 533 words essentially repeated the same point over and over, producing such gems as this quote: “Financial services is a real leader in big data and analytics,’ said Mr. Bean.” Acres of coverage Not once, however, did the article mention what it means by ‘big data,’ how financial services firms are using it, what they’re doing with it, or whether the money being spent on it was producing any results. This has been the enduring problem with big data. Despite acres of coverage and a Google Trends line that has exploded to the highest measurement in just two years, the term remains ill-defined. Google engineer Peter Norvig offers an evocative way of understanding it in Viktor Mayer-Schönberger and Kenneth Cukier’s book Big Data (see pages 31-33), using the example of a cave painting and a photo of a horse. While there is an obvious difference between the two, each remains a still image. Yet a number of photos displayed at a rate of 24 frames per second and the resulting motion picture provide far more information. “By changing the amount, we change the essence,” Norvig is quoted in the book as saying. It remains the same thing – a set of pictures – but the sheer volume conveys information about how the horse moves, how fast it runs, the direction of travel, whether or not it has injuries, and much more. Added information offers a more complete image, if it is structured and presented in a meaningful way. Similarly, what big data does in the world of finance is that it allows us to extract patterns from what was just information. And within those patterns lie unexploited – and often unknown – opportunities. Working with new 24 • Allianz software like Apache’s open-source Making sense of chaos: Hadoop framework project and the a focused ecosystem of tools that have grown approach is needed to around it, businesses can use the power extract value of distributed computing to interrogate from big data. vast amounts of data quickly, efficiently and at little cost. The potential is enormous. Big data comes from a variety of sources: a lot of the digital exhaust is left by individuals as they go about their day-to-day business: searching the web (leaving records of search history, location, browser information), taking a photograph (time, date, exposure, location), making phone calls (numbers being connected) or using their credit cards. Other data is created more overtly, for example, on social media where a single tweet has more than two dozen metadata fields. And a lot of it already exists in the form of vast troves of unread documents or in data dumps like backup servers. Over time, this data, tied together with that of other individuals, accumulates to offer insights. FINDING THE RIGHT CORRELATIONs Such data is not always structured. A recent white paper from Oracle, a database company, estimates that between 80% and 90% of the data owned by banks is unstructured. In other words, it exists not in neat rows and columns ready to be plugged into Excel but as documents or in plain text. That would require weeks if not months to parse. Hadoop, along with complementary tools such as Mahout (machine learning) and Hive (data warehousing), is able to deal with such data by breaking it up and tackling it in little bits. Visa, for example, used Hadoop to analyze 73 billion transactions in 13 minutes. Without Hadoop, it would have taken an entire month. Examples abound of how big data can be used in realworld scenarios. David Gentle, Fujitsu’s director of Allianz • 25 Focus foresight, offers the example of a mobile operator that noticed its customers were leaving for other networks. “Then the company realized that they’re operating a digital service and everything they do with their customers is generating information.” Gentle says the company examined phone records of recent departees and found that they often spoke to a close friend or family member just before changing providers. “That indicated that they had been influenced by a trusted source and just needed some attention to stay behind. In response, the company automatically checked the immediate contacts of those who had recently left and made special offers to their close friends on their network, something that helped retain customers.” Separating the wheat from the chaff More impressive still is the example offered by Andrew Sheppard, a financial technology consultant, former hedge-fund CTO and analyst. According to Sheppard, big data should simply be understood “as anything that either doesn’t fit in Excel or that requires hours for Excel to process.” He points to Counterparty Valuation Adjustment (CVA), or the value of the risk of default by a counterparty, as a way to measure the true value of a portfolio. Under new regulations, a financial institution with strong risk management will receive a break on its risk capital – the amount of money needed to run an operation in a bank, says Sheppard. However, it is hard for banks to get a handle on this because such calculations must take millions of possible scenarios into account, which may take anything from several minutes to several hours. That is not ideal for an industry that relies on speed. But with big data analytics, it is possible to do it with great efficiency. What does that mean? Sheppard offers an example: “Let’s suppose for a bank the cost of capital must be about 10%. If you assume the bank has $20 billion of operating capital and it gets a 10% break on that, it would need to have $18 billion. Since the cost of capital is 10% for a bank, that $2 billion less saves $200 million, which goes straight to the bottom line.” Sheppard stresses that this is the result of nothing more than good data wrangling. “The bank hasn’t acquired one customer, it hasn’t done one deal and it’s done nothing different other than get a better handle on risk with big data. And all of a sudden it’s making $200 million a year more for doing nothing but using data in an intelligent way,” he says. Indeed, this is applicable in myriad ways beyond just regulatory matters. ZestFinance, a firm that helps lenders 26 • Allianz Focus Once big data make credit decisions for small, shortis structured, term loans by using big data, has a it can yield default rate more than 30% lower than invaluable insights. the industry average, according to the book Big Data. It does that by looking at a vast variety of incomplete data rather than focusing purely on traditionally accepted data points. Yet, there is also a pitfall to big data, which is the risk of seeing patterns where there are none. Fortunately, using big data for finance is easier than using it, for example, to define policy. “As a user of big data in finance, the final question is, ‘Can I make money with this?’ If I can, then it’s good data – and if I can’t, it’s bad data,” says Sheppard. But big data is no panacea. “The thing is to look at the areas where it can generate an advantage,” says Gentle. Take social media. Volker Stümpflen, CEO of Clueda, a German data analytics firm (see pages 15-17), says there is plenty of noise on social media, but there are some gems that can be market-moving. The crucial task is to separate the wheat from the chaff. The hubs of social networks – people with a lot of followers – are not necessarily the most reliable, or indeed the first with the news. Rather, Clueda’s algorithms are programmed to identify valid information by looking at the reliability and authority of the sources picking up and spreading information. Value might lie at the edges of the network. But above all, it lies in the use of data analysis to put chaotic information into useable contexts. Setting the scene for change Consumers – the people creating a lot of this data – may not be thrilled by the idea that their digital trails are being analyzed in such detail. Yet, the benefits of commercial adoption of big data far outweigh the risks. Returning to the example of ZestFinance, for every person denied a loan, there are plenty more who may have struggled to meet traditional, less accurate assessment criteria who are now able to get one. Better data analysis means more accurate decisions. Customers might not like a telecom operator seeing who their friends are, but it could mean that they receive savings on their bills when the operator tries to retain them. Safe or infrequent drivers could be in a position to pay lower car-insurance premiums through the installation of telematics boxes, which gather data as a car is driven and show that these drivers are reliable. The benefits, then, are broad. Finance professionals and businesses of all stripes benefit from greater insight and efficiency. Consumers get better service, lower prices and more personalized attention. And a whole new industry blooms, building on what already exists. The world is set for some big changes. Allianz • 27 Focus Focus What’s in it for the customer? To benefit from the digital revolution, one must understand both business potential and customer needs, writes Christof Mascher, COO and Management Board member of Allianz SE. T Christof Ma s c h e r Christof Mascher has been a member of the Management Board and chief operating officer at Allianz SE since September 2009. 28 • Allianz he digital revolution goes far beyond digitalization and networking communication. Smart and mobile devices, sensors and cognitive systems bridge physical and even mobile locations and interactions. The possibility of being connected anytime, anywhere and with every kind of device comes with a new level of convenience: first, people can quickly adapt their use of technology, and second, people can better manage their life, gain time and save money. The seamless customer journey If seeking advice or information, customers can easily reach out to peers via social networks – and quickly gain transparency on products, prices or services on a much broader scale. In Germany, discussions on car insurance on the popular MOTORTALK online platform generate up to 7.5 million views annually. Analysis shows that 25% of these inquiries receive a response from peers within 10 minutes of posting and 50% within an hour. This significantly changes the traditional relationship between the customer and the insurer. In order to retain the customers’ trust in our brand, insurers must be equally present, agile and responsive. How fast the communication landscape is changing is evident in the fact that some 15% of Internet searches relating to insurance are now conducted on mobile devices. As an absolute number, this will grow threefold by 2016 in line with the general growth of mobile commerce. This embracing of new communication technology from smartphones and tablets to social networks is not just restricted to ‘Generation C’ (the connected generation): already, 75% of customers aged 55+ rely on social media for purchase decisions in the US and UK. In the digital world, companies no longer control this relationship; consumers are increasingly making their power felt. Connectivity significantly reduces transaction costs, prov ides a never-before-seen transparency and improves the quality of direct communication. Customers consuming on the go can share their experience – positive or negative – immediately online and seek to shape and optimize offers. The conversation is now a dialogue which puts customer experience much more into focus and intensifies the existing relationship between customers, consumers and insurers. Customers want to have the choice of when and how to interact with us through multiple access points – via phone, net, mobile apps or in person with our agents. They consider the exchange of information and communication as one stream, maintaining the conversation on different devices or face-to-face from where they originally left off. It is simply part of their day-to-day life, and they expect real-time offers and services delivered seamlessly with the same level of professionalism and expertise both online and offline. Finance and insurance companies have to realize that digital is not just a channel characteristic. The actual need for change is radical: it is a business model evolution A comprehensive digital strategy can help paint a more wholesome picture of issues like customer trust. with simplified and competitive offers that will open up new areas of business with existing clients as well as gaining access to new customers – based on seamless customer journeys. To benefit, one must first understand Taking a 360-degree perspective on our customers diminishes extensively the traditional product and channel focus of an insurer. The question is no longer which product fits best and is best sold via which channel. Rather it is our clients’ interactions, points of contact, mobility, whereabouts in daily life, their activities, changes in circumstances and corresponding interests and needs that now help define how risk mitigation and our products and services are designed. The sharing of information has become an aspect of virtually every daily habit, of both our digital and physical lives. This explains how Amazon can recommend us the ideal book or the ability of Facebook to know what we like. In 2010, we were already creating as much information through digital means every two days as we did from the dawn of civilization up until 2003, according to Eric Schmidt, former CEO of Google. In such a complex environment, how do companies know when to approach a particular customer at a particular time and place? This knowledge comes from data and, to achieve this, the ability to obtain, filter, understand and channel customer-related data becomes a must. A small amount of the data is actually provided by the customer. According to Forbes Insights, the majority of consumers will willingly share information if they perceive it to be in their favor in order to obtain individual and competitive offers. The largest part of the data comes not directly from people but from interconnected devices. Data accessibility and the ability to leverage data to better serve the customer at every Allianz • 29 Focus step of our relationship, while respecting the customer’s privacy, will become a key competitive advantage. ‘the most trusted partner’ In a world where technology opens new possibilities to make people’s lives more convenient – just think of smart homes, connected cars or e-health – Allianz wants to offer improved additional value to its customers. Consumers are expecting new, individualized ways of being insured, customized services and prevention, as well as a free choice of the means to interact and communicate with us. To deliver exactly these types of products and services, we at Allianz embarked on a comprehensive digital program a couple of years ago. In this new digital world, however, we want to remain ‘the most trusted partner.’ It is therefore of the utmost importance to Allianz to keep our customer and business-critical data secure from prying eyes. We carefully Emerging patterns: the denser the cluster of pixels, the higher the level of social trust in the surveyed countries. 30 • Allianz balance risk by building highly secure data center hubs for Allianz’s powerful, global private cloud infrastructure, including carefully selected security measures. The fact that we have been offering cyber-risk protection to business clients since 2013 underlines the point that Allianz is one of the few players with the size and skills to ensure customer data privacy is protected to the highest security standard. Protecting our customers’ most valuable asset – trust – remains a core value at Allianz – especially in the digital world of the immediate future. A measure of trust: the PROJECT M COver PROJECT M uses data to create its award-winning cover art. For the cover of the magazine’s 11th issue, global social-trust-level data was used to generate the ‘TRUST’ image. Focus Minority warning The challenge of big data is not its quantity or variety, but human over-reliance on its infallibility. W hat sounds like a strange location for lunch turned out to be a great choice for Mark Eveleth. Seated in a dark corner of a multistory parking garage in downtown Santa Cruz, California, the police sergeant was about to unwrap his sandwiches when two women strolled by, casually checking car doors in search of an easy burglary. The lunch break led to two arrests. Eveleth did not pick the spot by chance. He was guided by Predictive Policing (PredPol), a software program devised by University of Santa Clara mathematician George Mohler and colleagues. Based on historic crime data and updated on a daily basis, PredPol predicts crime hotspots of 164 yards by 164 yards (150m x 150m), including the garage Eveleth had lunch in. The incident recalls Steven Spielberg’s Minority Report (2002), where people are arrested for crimes they are predicted to soon commit. What Spielberg envisioned for Washington, DC, in 2054 is only a few steps away from what PredPol and similar programs do today in the US and UK, warns Viktor MayerSchönberger, professor of law, Internet governance and regulation at Oxford University. “Big data’s biggest risk is that it is misused to explain the causality of facts when all it can do is indicate correlations,” he explains in an interview with PROJECT M. “Big data reveals something is happening; however, it cannot explain why.” PROPENSITY JUDGEMENT Listing two other key risks – lack of privacy and data dictatorship – Mayer-Schönberger’s main concern is that penalties are applied on the basis of probabilities. Judgment and punishment based on big data “negate ideas of fairness, justice and free will,” he and co-author Kenneth Cukier write in Big Data: A Revolution That Will Transform How We Live, Work and Think (2013). A society relying primarily on big data destroys positive incentive. “What incentive do I have not to commit a murder if I am punished anyway? More mundane: what interest do I have to improve my lifestyle if my health insurer charges a higher premium based on my genetic likelihood to suffer diabetes?” The shortcomings of small and big data alike have been ignored too long. Mayer-Schönberger points to Robert McNamara, former US secretary of defense, as an early victim of data dictatorship. To measure success during the Vietnam War, McNamara relied on the opposing side’s daily body count, a figure blown out of proportion by US soldiers on the ground. “Clearly, our data has become more sophisticated in the last 50 years. Yet the lesson to be learned from McNamara is that we need to question the validity of data and the analysis drawn from it.” ANECDOTAL ONLY In Santa Cruz, the numbers look good. From July 2011 to the beginning of 2012, when PredPol was installed on laptops in patrol cars, crime rates in the city decreased. Figures for assault were down by 9%, burglary by 11%, robbery by 27%; but the number of arrests rose by 56%. “And the only thing we changed in that period of time was PredPol,” says Steve Clark, the city’s deputy chief of police. The thought of blind reliance on statistics like these is what keeps Mayer-Schönberger awake at night. “By providing correlations, big data does not fit the concept of cause and effect, yet it is often abused to explain causal relations.” Prior to big data, individuals would expect their insurance premiums to rise only in the aftermath of accidents for which they had claimed compensation. Now, the price may go up before the accident occurs. “In the US, drivers with better high-school grades pay less for car insurance because better grades correlate with a lower risk of accidents. But do we really want to penalize people for something they have not done and may never do?” While PredPol only uses information about Viktor Mayerthe type of crime, its time and location, Clark is Schönberger and keenly aware of the risk involved in numbers. Kenneth Cukier analyze how “Any evidence from Santa Cruz that PredPol big data could works is anecdotal,” he argues. If anything, the transform our lives. program helped officers deter crime more Allianz • 31 Focus Focus often, Clark believes. And he prefers to add gut feeling to his judgment. “The best sign of success for me is if I see a woman walking down the street with a stroller.” The number of arrests is clearly the wrong benchmark to measure the success of crime programs, warns George Mohler, PredPol’s chief scientist and an assistant professor at Santa Clara University’s Department of Mathematics and Computer Science. To measure the program’s success accurately, the amount of patrol time per hotspot needs to be related to changes in the crime rate, Mohler suggests. Randomized controls should be added to establish a causal relation between the crime rate and PredPol. “However, this is an academic interest. Most police departments using the software do not conduct randomized controls.” And that’s fine, Mohler says, but “you just won’t be able to say for sure what caused the crime rate reduction.” PredPol and programs like it are used in cities across the US, including New York Cit y. ERRORS WILL BE MADE As a safeguard against big data’s dark sides, MayerSchönberger calls for a use-by date as well as legal procedures for consumers to disprove the data-based probabilities calculated by the software’s algorithms, if necessary. In contrast to current strategies such as ‘notice and consent,’ the onus of handling such algorithms and probabilities responsibly should be placed on data users. Based on a code of conduct, such users would have to assess the impact on individuals described by the data. Breaches would be liable to fines and maybe even criminal prosecution. “These reforms need to be implemented as soon as possible. Otherwise, the use and abuse of data establishes facts which will be difficult to reverse.” Also, private-sector firms such as insurers could create a niche by emphasizing their responsible approach towards big data. Fred H. Cate, professor of law at Indiana University (see ‘If … Then,’ page 18), supports the call for an appeals process. “In the meantime, however, a relatively small number of people will likely suffer from incorrect correlations drawn from big data, for example by being denied access to a plane or by paying a higher insurance premium,” he says. With big data’s use in law enforcement and elsewhere likely to increase in the future, the debate about the National Security Agency (NSA) triggered by Edward Snowden is crucial for democratic societies. “As police officers, our use of big data is a reflection of the society we are serving,” Clark notes. Whether society will heed the warnings of MayerSchönberger and Cukier remains to be seen. “I tend to be optimistic on days with even dates,” Mayer-Schönberger says. The interview was conducted on an uneven date. 32 • Allianz Allianz • 33 Video Bonus content in the PROJECT M app Focus Automating Advice The rise of digitally delivered, managed accounts offers convenience, but the quality of investment advice underpinning them must be paramount. Technology can help when planning for retirement, but one must stay vigilant regarding goals. 34 • Allianz Focus By Stacy Schaus T he ultimate responsibility for retirement investing and planning increasingly rests on the shoulders of individuals. Workers must count on defined contribution (DC) programs to meet their retirement savings needs, as few today have the defined benefit pension that traditionally offered financial security in their golden years. To help ensure they reach their retirement income goals, they often look for expert advice. DC participants are often offered one or more sources of advice, either delivered within an investment structure or a separate offering. The primary question being addressed for participants is this: “How should I invest my money?” Target-date strategies and managed accounts both aim to answer this question for participants and, better yet, shift an individual’s asset allocation over time. Placing trust in sponsor or employer For the mass population, these packaged, technology-delivered advice solutions fill an important need in the retirement market. Unlike target-date strategies, managed accounts give participants the opportunity to view retirement income projections, to add in outside funding (for example, spousal retirement savings), as well as the option to modify risk levels to inform the advice models. In reality, however, fewer than 20% of managed account participants add information into the models. As a result, the advice from the managed account system may be no more informed than target-date strategies – that is, both will tend to default a participant based on the assumed number of years to their retirement date or the expected time horizon for investment. Despite the fact that few participants engage with their managed accounts in this way, both target-date strategies and managed accounts offer a big advantage over static balanced portfolios or participant self-selection from a fund line-up. By at least managing assets with a participant’s anticipated time horizon in mind and offering professional oversight, they are likely to serve workers better. The most important role these offerings must play is their ability to evaluate the underlying advice and confirm its appropriateness for plan participants. This is important because workers defaulted into these programs are highly likely to remain invested in them over many years – and even throughout their retirement years when they retain assets in the DC plan. In many cases, participants blindly trust their plan sponsors or employers to put them on the right path toward reaching their goals and trust that they are receiving reasoned and appropriate guidance. In essence, the tendency for schemes to default participants, combined with the participants’ own inertia, determines early on whether participants are likely to succeed or fail in meeting their income goals. Given their weighty responsibility here, it’s all the more important for plan sponsors to evaluate the plan’s default investments carefully – whether target-date strategies, managed accounts or other types of investment. It is absolutely critical, then, that fiduciaries are able to evaluate the risks. They need to ask the right questions, receive guidance on selecting sound advice and be helped to evaluate advice providers. » T echnology helps workers see and understand how their retirement plans are progressing. « Don’t be dazzled by technology Technology helps workers see and understand how their retirement plans are progressing – people like to see the balance of their DC accounts on their phones and how they are allocated. It makes the planning process so much clearer and easier for the individuals. But it’s important not to be dazzled by technology. The plan sponsor must not lose sight of the end goal: to help people build purchasing power in inflation-adjusted dollars with investment plans that minimize risk and perform regardless of the kind of economic environment they operate in. Advice made easy through digital tools is a step forward, but it has to be sound advice. Yo u n g a n d o l d ta k e adv i c e t h ro u g h n e w t e c h n o l o g y In the US, the take-up of managed account and advice solutions delivered to end users through technology, rather than face-to-face advice, seems to differ by age cohort. Those most interested tend to be either very young or much older people. The interest among those closest to retirement is surprising. It’s not yet clear why this is so, and further research needs to be done. Allianz • 35 Focus Focus How we view and conduct each aspect of our lives is changing – and faster than ever. fast-forward A new Allianz-owned company, the Digital Accelerator, is racing ahead of current digital developments in order to serve insurance customers better – now and far into the future. By Bernd Scharrer G adgets that give us constant feedback (such as cars that tell us our braking efficiency), giant data sets that help authorities warn of the next flu outbreak, websites where people can swap goods and services instead of buying them – it’s an understatement to say that modern technology is changing the way we live and conduct business. The question is actually, “How can technology help people live the lives they want and meet fundamental needs, such as the need to feel secure and be connected with others?” Business ideas that focus on the smart home, telematics, e-health or wearable computing may make a contribution in this area. In the end, each business model fits into a larger technological trend, such as the move to interlink devices (the Internet of Things), predictive analytics, the shared economy or the ‘quantifiable self.’ And it is often small, creative businesses – start-ups – that are bridging the gap between technology and human needs. They’re competing in a race to solve problems in the fastest, most creative way. In the entrepreneurial sector, start-ups use a ‘lean’ approach: a young company begins testing a product on the market once it has a ‘minimum viable’ version available, with little up-front investment. In large companies, where established brands are at stake, the approach is the opposite. In the corporate world, people take days, months and even years to create and validate a product concept. Then a large portion of the budget is spent building the product. Finally, in a third phase, the company gathers real customer feedback, which is also about the time the budget is exhausted. Some large companies, however, are taking cues from the start-up world and turning this corporate product development cycle on its head. proactive customer care At the Allianz Digital Accelerator (an independent Allianzowned company) we’re exploring new business models as part of our effort to shape the digital insurance world. We’re using lean start-up ideas to take business concepts and fast-forward them to the customer-feedback stage. We are acting instead of reacting to find out what people really want. These business ideas stand to benefit Allianz in any number of ways by helping the company interact more frequently and naturally with customers and potential customers, or sell additional services. Imagine insurance products that act similarly to shared-economy business models, such as car sharing or Airbnb.* This is not a fiction. There are already tech companies and start-ups venturing into this field. Alternatively, what if there were a way to create products or services based on the vast data many companies already possess – for instance, by developing anonymous consumer profiles that could be used to provide individual or customized insurance and service offerings? There’s also potential in the smart home because people want to understand and manage their lives better. There are already apps that inform absent users what’s happening in their homes. Pulling data from a variety of sources and sensors, the app informs working parents when their children arrived home and if they forgot to lock the door on the way back out. It could also alert absent homeowners if the smoke or water alarm goes off so that they can react quickly to limit damage and loss. the quantifiable self The Accelerator is also focusing on vehicle telematics and data analytics. To this end, the company is testing a nonAllianz branded app for young drivers that allows them to collect ‘credit miles’ for their driving and redeem them for awards, such as gift certificates or coffee. The project allows the Accelerator to test how open young people are to apps like these that could potentially help them gain driving experience and improve their skills. This can also allow companies to provide them with better insurance benefits in the future and enable services to be more tailored for individual needs. While drivers today can gain credits when they brake and drive in an energy-efficient way, tomorrow’s motorists are more likely to demand a ‘pay-as-you-drive’ rate for insurance premiums. Would an app that enables pay-as-youdrive, in conjunction with data recorded in vehicle telematics, function? Two final areas of interest are e-health and wearable computing. Online health and activity marketplaces that bring people together, much like a sports club does in the physical world, could make a positive difference. Such a site could help like-minded people gather for sports and leisure activities – for instance, to set a meeting point for a Saturday morning jog. When people do meet, they often have a number of computers attached to their clothing or worn as accessories. A watch or sensor sewn into a jogging outfit may double as a fitness tracker, measuring the kilometers run and calories burned. Similarly, wearable computers could be used to keep workers safer at a dangerous construction site or to monitor and prevent certain medical conditions. Such new possibilities – often referred to as ‘the quantifiable self’ – are all part of the interesting data trends that are shaping lives – and our business. *A website f or seeking and of fering inf ormal and unconventional accommodation around the world 36 • Allianz Allianz • 37 Focus From the cradle to the grave: data collection today begins at the earliest stages of modern life. my creative juices flowing. And then [Yahoo CEO] Marissa Mayer mentioned big data to me. I told her, “I’m a photographer. I don’t really think that sounds like something for me.” Then she said you could compare it to the planet developing a nervous system. That got my attention. It’s still quite an abstract topic, though. Smolan: We spent 18 months trying to figure out how to tell the story, to see if we could capture this transformation in the form of photographic essays. A lot of publishers were very dubious, so we decided to self-publish the book. How do you explain big data? Smolan: Thanks to my 10-year-old son, at some point I hit upon an analogy. One night he asked me why I was always talking about big data whenever I was on the phone – what did it mean? I struggled to come up with something that would make sense to him and then said, “Imagine if, for your whole life, you had only been looking through one eye, and then scientists allow you to open up a second eye. All of a sudden you’re not just getting more vision, you’re getting a different dimension, a whole new perspective.” He told me how cool that was and asked whether we could also open up a third or fourth eye, or even a thousand eyes. And that’s exactly what’s happening now. » From the beginning of recorded time until 2003, we created 5 exabytes (5 billion gigabytes) of data. In 2011, the same amount was created every two days. By 2013, it’s expected that the time will shrink to 10 minutes. Rick Smolan « WATCHING THE WORLD DEVELOP A NERVOUS SYSTEM You thought the Internet was big. But it’s not as big as big data, the global information network that is transforming the world. Photographer Rick Smolan tells PROJECT M how he captured the rapidly changing face of the data revolution. W here did you get the idea to put together a book on big data*? Rick Smolan: I had some experience in putting together large-scale projects with the “Day in the Life” series of books. I found it fascinating to gather a group of journalists from around the world to really explore a place in as much detail as possible. After exploring different countries, I set up my own production company with my wife, and we started to focus on more technological themes. A couple of years ago, I found myself looking for a new subject. I was going to TED conferences and seeing some interesting stuff, but there wasn’t anything that really got Which areas of our lives do you think will be most affected? Smolan: For me, the medical and healthcare aspect was particularly interesting. By the time we become ill, our body has often been giving off signs that something isn’t quite right for some time. Until recently, we just haven’t had the means of measuring ourselves and creating a baseline for own body. But things are changing. When Steve Jobs had his DNA sequenced five years ago, it cost $100,000. Today, it’s $3,000. In five years’ time, it might well be $50 at your local pharmacy. And then you’ve got wearable devices, such as the UP wristband, that you can use to track your own exercise, diet and sleep patterns. It’s the ‘gamification’ of health. The projec t “ The Human Face of Big Data” is editoriall y independent and is made possible through the generous suppor t of EMC Corporation, which ser ves as it s primar y sponsor. Suppor ting sponsor ship comes f rom Cisco Sy stems , SAP and FedE x . 38 • Allianz Allianz • 39 Focus As technology continues its advances, big data is increasingly entering the public agenda. Are you worried about what happens with all this data? Smolan: I am worried that, for the most part, it seems to be governments and large companies who are realizing the value of it. I don’t think the average person should say that they don’t really care about their personal information. It’s naïve to think there’s no value to it, and I think we should have more of a say in what happens with our data. the Internet. Now we need the Internet, its worldwide network, to form the basis of big data. All these devices are now talking to each other, and they change their behavior based on their interactions. I think that 2013 will come to be known as a point of demarcation – before big data and after. It’s going to be such a huge part of how everything works. There’s almost no field you can think of where it’s not already having some sort of impact. Do you think it’s a topic that is properly understood by the general public? Smolan: When we started with this book, a lot of people weren’t familiar with The Human Face of Big Data, by Rick Smolan and Jennifer Erwitt the idea of big data. But during the last year or two, it How do you picture something that isn’t concrete – an idea, a method, movement itself? Big data – the incomprehensible amount of information has certainly entered the collected, processed and deployed second by second – can be neither depicted public agenda. It’s really nor comprehended. Yet The Human Face of Big Data sets our imaginations growing on a daily basis. in motion with images and graphics that explain why, in the words of British I must admit that, initially, data commercialization entrepreneur Clive Humby, “Data is the new oil.” I thought it was a lot of In compiling their volume, Smolan and Erwitt took photographs of the people and their work marketing hype created by that have transformed global data collection and use – and been transformed by them. We’re technology companies to in the thick of “an extraordinary knowledge revolution,” Smolan writes in his foreword, “that’s suit their own needs. Now sweeping almost invisibly through business, academia, government, healthcare and everyday life … big data may well turn out to be the most powerful toolset the human race has ever had there’s no doubt in my to address the widespread challenges facing our species and our plane ... [and it] carries the mind that this is going to potential for unintended consequences.” be a thousand times more influential on our species than the Internet has been – Rick Smolan and the Internet has been pretty damn dramatic. It’s i s a former Time, Life, and National Geographic photographer. Now, as CEO of an evolution. We needed Against All Odds Productions, Smolan producers large-scale global photography projects which combine storytelling with state-of-the-art technology. to have microprocessors to Against All Odds Productions was named one of the “25 Coolest Companies build computers. Then we in America” by Fortune Magazine,and its projects have been featured on the covers of Fortune, Time, Newsweek, and U.S. News & World Report. needed computers to build 40 • Allianz Focus STRENGTH IN NUMBERS We live in the age of information, where the sheer volume, velocity and variety of data being created necessitate their being processed in a new way. The data and its related technology offer more than just health insights – they could even save lives. N » They needed a computer platform to take all the different signals from lots of different babies and environments. Dr. Carolyn McGregor « othing is quite as vulnerable as a premature baby fighting for its existence, alone in a neonatal intensive care unit. That tiny body lies tethered to numerous monitoring devices that provide a continuous feed of vital signs – such as heart rate, breathing and blood pressure – at a rate of a thousand readings per second. The exhaustive volume of data is too much for physicians and nurses to absorb. After 24 hours, it is discarded. Such data, however, could provide vital signals about a premature baby’s fragile condition. Computer scientist Dr. Carolyn McGregor, whose first child died after an early birth, hopes to provide premature babies with an extra chance. She has devised an online health analytics platform called Artemis, named after the Greek goddess of childbearing. As Canada Research Chair in health informatics at the University of Ontario Institute of Technology (UOIT), McGregor and her team of researchers are collaborating with IBM at a number of hospitals to test software that tracks vital signals in premature babies. McGregor’s work follows research showing that babies who develop infections display changes in their heart rate, or heart-rate variability, 24 hours before the infection sets in. “People had already identified this trend but didn’t have a way to watch it in real time,” she explains. “They needed a computer platform to take all the different signals from lots of different babies and environments to continue research on infection, but also use the same platform to research many other conditions.” The software processes the newborns’ vital signs in real time, tracking 16 different data streams – such as heart rate, breathing, blood oxygen levels and blood pressure – which together amount to 1,260 data points per second per baby. It also seeks patterns in the data, then stores the information. The hope is that Artemis will allow doctors to identify subtle changes in a baby's condition that may signal the onset of infection or another medical condition. Taking over from a doctor's ‘intuition,’ the software provides signals that the naked eye would miss, and allows clinicians to administer medical treatment before symptoms deteriorate. “We monitor premature babies’ heart rate and respiration,” McGregor continues, “and can delineate whether heart rate variability happens shortly before the onset of an infection or because the baby is being given certain drugs, which can also trigger heart-rate variability.” LOOKING BEYOND INFECTION Artemis was first introduced at the Hospital for Sick Children in Toronto in 2009. In 2010, a cloud-computing version went live at the neonatal unit of the Women & Infants Hospital in Providence, Rhode Island, where readings are fed to the UOIT. The project was extended in December 2012 to China’s Children’s Hospital of Fudan University in Shanghai. “In China, they don’t use morphine,” McGregor explains, “allowing us to carry out cross-cultural studies and see the different heart-rate variability changes without the use of morphine.” McGregor and her team have now moved beyond looking only at infection to examine various other conditions, such as retinopathy of prematurity (an eye disease that causes some premature babies to lose their sight, notably afflicting blind pop star Stevie Wonder), or premature babies who forget to breathe, as their brain stems aren’t yet fully developed. Allianz • 41 Focus Focus » There is a human factor in trying to keep an eye on 250 people. You can’t continuously monitor each one for every second. Professor Dr. Timothy Buchman « McGregor is also trialing an algorithm that classifies different types of conditions, such as low oxygen levels or gaps in breathing. Other plans include a study on adults. She also intends to continue testing with the Apollo project, which provides home-based monitoring. “When these premature babies go home,” she says, “the Apollo platform would alert a medical person if there is a change in the babies’ condition.” While McGregor is still in the process of publishing and confirming the findings from the project, she is hopeful that Artemis will be introduced in neonatal intensive care units (NICUs) worldwide. She is equally confident about the beneficial effects of big data in the medical arena. “Big data has the potential to be the next disruptive technology after genomics. We are at the cusp of a whole new wave in clinical research.” WHOSE INFORMATION IS IT? With the vast amounts of personal data collected, the question of moral responsibility urgently needs to be addressed. Who has the right to collate and publish all this information about a person’s body and its functioning? How does it affect the individual’s right to privacy? McGregor concedes, “We still need a framework for this. It needs to be on the mandate for public policy.” Opinion surveys so far are positive. While people have concerns about health insurers’ use of big data, most are in favor of its use if it can provide insights that might mean the difference between life and death for premature babies. As Dr. Timothy Buchman, professor of surgery and anesthesiology at Emory University in Atlanta, Georgia, and director of the Emory Critical Care Center, points out, the data involved in such projects are hardly sensitive or high-risk. “We’re talking straight physiology values, such as your blood pressure,” he says, “which most reasonable humans aren’t going to get sensitive about. Can you remember what your blood pressure reading was two years ago even, and are you bothered about it?” He adds, “There is a human factor in trying to keep an eye on 250 people. You can’t continuously monitor each one every second.” Fortunately, computers lend a hand where humans could fail. Buchman and colleagues have been using software from IBM and Excel 42 • Allianz Medical Electronics since early 2013 to monitor intensive care patients using real-time streaming analytics. The system can analyze more than 1,000 real-time data points per patient per second and identify patterns that could indicate serious complications, such as atrial fibrillation, an abnormal heart rhythm triggered by a lack of blood oxygen or drugs. Buchman is certain that the research project will be deployed quickly at the hospital. “Instead of looking at single, six-second snapshots of ICU patient data, this system lets us see new views and trends of data that are being processed in real time.” In his opinion, big data technology and real-time analytics will ultimately transform the world of critical-care medicine. “Big data will not make a diagnosis for us but will act as an early warning for caregivers to show us who is heading in the wrong direction.” He envisages a future where the same predictive capabilities possible in weather forecasting, for example, will also be employed in medicine. This new world of healthcare will include better preventative care. “We are going to look after patients by keeping an eye on them not just in the ICU but also in their daily lives via tracking devices,” says Buchman. “There is a lot of information we need to know. If you are old, infirm and forgetful, we need to know that you are taking your medicine. Or if you get lost frequently, we need to know if you are straying off your usual routes.” The next generation of caregivers will need a broad skill set, including being adept at technology. With ground-breaking devices to monitor, collect and assess data, the ability to manage these tools will be vital in assisting healthcare practitioners to allow all of us to live longer, high-quality lives. Big data and disease detection Dr. Craig Feied, professor of emergency medicine at Georgetown University, believes big data will transform medicine for the better. The inventor of a system known as Azyxxi, which provides real-time access to patients’ medical history at the touch of a button, is convinced big data will help identify patterns that can help in the early detection of diseases, such as cancer. Read this exclusive interview at www.projectm-online.com Allianz • 43 Micro Picture Galler y Bonus content in the PROJECT M app Loc al k now le dge Blurred picture those who are at the start of a crisis, rather than leaving them to be eventually rescued from a factory or become a victim of human trafficking.” Using education as a weapon in the fight against child labor would also help children who are being exploited by their families to work long hours on various domestic chores, and those who are treated harshly. Globally, says Edmonds, primary school numbers have increased dramatically over the last 15 years, but secondary-school enrollment remains at a low level in many developing nations. Children in many parts of the world spend far more time at work than in the classroom. But until countries offer truly universal education, we should be slow to pass judgment on all forms of child labor. In many countries, child labor is a thing of the past. A distressing examples, such as Uzbekistan – where the t the turn of the 20th century, child labor was government has introduced a forced-labor system to get commonplace in the West. Children from poor backgrounds could be found working in mines, under-age workers to harvest cotton – the majority of child factories and mills, and on street corners, selling labor is not a product of coercion. Nor does it involve children working in dark, dangerous 19th-century-like newspapers or cleaning shoes. Sometimes working at night, conditions, separated from their families, says Eric V. minors – with their ability to handle small parts and tools – were an attractive commodity for employees who only paid Edmonds, professor of economics at Dartmouth College in them low wages for their labor. New Hampshire, US. Deprived of an education and a carefree childhood, many working children also developed serious health Educational investments problems, such as stunted growth and lung diseases. “Those horrific images of children stuck in a Bangladeshi Others suffered horrific injuries following accidents factory fire [November 2012] – that’s not what most working involving machinery. children are doing. Most children who are working are But thanks in part to the social activism of campaigners doing so in the family business or farm, beside their parents or other family members,” says Edmonds. such as photographer Lewis Hine, the prevalence of child labor died out, with several governments eventually The US academic, who has served as an advisor on child passing laws to prohibit minors from working – such as the labor for the ILO and the US government, says that in India, Fair Labor Standards Act of 1938 in the US. As a for example, many parents feel that their children should develop skills in the home, reporter for the National Child Labor M ost children who are working Committee, Hine stirred consciences in the US farm or business that they are eventually going are doing so in and beyond with his images, which depicted to step into and run themselves. “Parents are the family children as young as six working under struggling to weigh up the sense that the child business or farm, hazardous conditions. His photography is a should be learning life skills versus the sense beside their reminder of a bygone age in much of the that the child should be in general education parents or other developed world, but child labor remains and accumulating those sorts of skills,” he says. widespread in many countries, and even in family members. The reverse is also true. Edmonds explains pockets of Europe and the US. that there is compelling evidence from Brazil The International Labour Organization (ILO) estimates that shows that parents face problems in preventing their that there are some 168 million children whose primary offspring from leaving school to enter the labor market. activity is work. Asia and the Pacific have the largest “Kids tend to be more myopic and not understand the value population of child laborers (78 million), followed by Subof educational investments when young, so parents face Saharan Africa (59 million). Latin America, the Caribbean, this same problem throughout much of the world. How do the Middle East and North Africa also have high populations you stop children from trying to assert their independence of under-age workers. Apart from some notable and at such an early age?” he asks. » « 44 • Allianz Micro For less developed countries, children remain a vital source of labor. Although many children are willing workers, particularly if they come from an impoverished background, the ILO and similar organizations remain concerned for their welfare. Even though they may be working in agriculture alongside their family members, as many are, they run the risk of being exposed to chemicals or machinery without adequate protective gear or training. Preventing children from being exposed to such risks, however, is difficult. Every country in the world, bar Somalia, has laws prohibiting minors from entering the labor market, but the public and the authorities in child labor hotspots either ignore them or are powerless to implement them. In fact, most countries have, for varying reasons, chosen to overlook elements of their own laws. The US government is one such culprit. It has decided not to enforce the laws of child employment in family farms, precipitating a bizarre situation in which 14-year-olds in Wisconsin can operate combine harvesters but still be two years away from taking their driving tests. But as Edmonds says, a laissez-faire attitude to enforcement of minimum working-age regulations is actually a practical one to take. Although keen policing would provide a useful extra tool to identify and tackle abuse, most countries simply do not have the capacity to enforce their existing minimum employment regulations. And in other cases, the cost of upholding such laws far outweighs the benefits. Instead, Edmonds argues, governments should concentrate on extending education and implementing compulsory schooling laws. “This is an under-used tool,” he says. “We have widescale primary school enrollment around the world, and it can be used as a way of monitoring children and identifying Compulsory schooling is more effective “I expect enrollment to grow, and we should also see a decline in child labor associated with secondary school growth,” he explains. And there is a historical precedent illustrating the power of education to discourage child labor. More than a century ago, Western countries shocked into action by the likes of Hine demanded action. The introduction of compulsory schooling laws arguably had a better effect than any laws forbidding the employment of children. Edmonds warns, however, that until education becomes more common and there is a clear black-or-white choice for families, simply taking children out of a freely chosen work environment can only be justified if there is a better alternative for them. “I always ask myself what a child who is working in a particular job would be doing if they didn’t have that job. And I’ll tell you right now, it’s not going to be enrolling in elite private schools around the world,” Edmonds says. “Where there are free and functioning labor markets,” he continues, “and a child in a particular job, then most of the time that child is doing that job because either the child or the parent believes the job the best possible opportunity available to the child. Sitting in my office in the US, am I in any position to know better?” c h i l d l a b o r fac t s •9 8 million children around the world work; 54 million of them in services and 12 million in industry. •S ince 2000, labor among girls has fallen by 40%; among boys, by 25%. •T he International Labour Organization wants to eliminate the worst forms of child labor by 2016. These include work in dangerous environments (underground, in water or at dangerous heights); work with dangerous machinery only suitable for trained adults; and long hours of factory work. Source: Marking progress against child labour – Global estimates and trends 20 0 0 -2012 (ILO - IPEC , 2013). Allianz • 45 Micro The government introduced reforms in order for private pensions to become simpler, cheaper and more accessible. It’s also running a nationwide communications program to educate the public, featuring ads on the main television channels. These measures are making pensions a mass-market financial product, like car insurance and bank accounts. Many experts believe that auto-enrollment in UK pensions has been a success. AUTOENROLLMENT SHAKES UP UK PENSIONS Minimum Contributions Employer Total minimum contribution 1 % A new UK initiative to get greater numbers of people saving more for their pensions aims to avert the imminent financial crisis posed by an aging population I n October 2013, Prince Charles gave a speech to the National Association of Pension Funds in which he suggested the UK’s pension industry should turn away from quarterly capitalism and instead address sustainability issues. The event coincided with the first anniversary of the UK’s auto-enrollment initiative for pensions, which stipulates that the employers must automatically enroll 46 • Allianz workers in a pension scheme if they fit certain criteria. By 2018, most of the working population should be saving in a private-sector pension scheme. The new law was introduced because of government fears that the growing number of pensioners will eventually create too much of a burden on state pensions. The Department for Work & Pensions warns that by 2050 there will only be two workers per pensioner, compared with three in 2010 and ten in 1901. The government aims to increase the number of individuals saving in a workplace pension plan by around 8 million, funneling an estimated extra £11 billion ($17.6 billion) a year into pension schemes. So far, 1.6 million people have been enrolled. Auto-enrollment is also the biggest shakeup in the UK’s pension industry for decades. Employer staging date to 30 Sept 2017 2 % 2 % 1 Oct 2017 to 30 Sept 2018 5 % 3 % 1 Oct 2018 onwards 8 % Source: The Pension Regulator Setting up a NEST egg In order to shake up the pensions market and ensure that there is always a provider of last resort, the government launched the National Employment Savings Trust (NEST), a notfor-profit organization with a number of innovations, including retirement date funds. Its asset allocation changes according to economic conditions and how far an individual is from retirement. “Auto-enrollment is having a beneficial impact. It is creating lower-cost pensions,” says David Pitt-Watson, a spokesperson for the Royal Society for the Encouragement of Arts, Manufactures and Commerce. “NEST has been particularly good in leading the way.” Savers can take their NEST accounts with them as they change employers, and some companies offer NEST pensions alongside other alternatives. Additionally, a major UK pension provider has thrown down the gauntlet by cutting its fees and even challenged the government to lower its 0.75% fee cap to 0.5%. Industry experts such as Henry Tapper, director of First Actuarial and a founding editor of Pension PlayPen, see NEST as a good default pension scheme for small businesses, given its simplicity and ease of use. Graham Vidler, director of communications and engagement with NEST, says the organization has deliberately developed tools to make the process easier for small employers. “The big challenge is ensuring employers and intermediaries know what they need to do,” he says. He advises smaller firms to start preparing at least six months before implementation. But one year on, has it worked? OUTSTANDING SUCCESS The government expected one-third of employees to quit; instead, only 9% have left the scheme. “So far it has been an outstanding success,” says Tapper, whose website Pension PlayPen is dedicated to helping small businesses with auto-enrollment. He notes that employee acceptance has been good, and that the government and employers have done a good job explaining the scheme. The Trades Union Congress, which represents 54 unions, also hails it as a success. “Auto-enrollment plays on people’s tendency towards inertia,” says Neal Blackshire, benefits and compensation manager with restaurant chain McDonald’s UK. “Besides, people know that they should be saving for their old age.” McDonald’s employs 37,000 people in the UK, with 35,000 of them paid hourly. There are another 57,000 working in franchised restaurants. To date, the fast-food chain has auto-enrolled over 1,150 salaried employees and 11,500 on hourly pay. The optout rate has been 3.48% and 2.15% respectively. Drawbacks and difficulties Implementing the scheme has been difficult for companies with large workforces. Blackshire says that several years of preparation and close cross-departmental cooperation were required, and McDonald’s brought in outside consultants to help communicate auto-enrollment to its workers to make sure they understood it. There is some concern that opt-out rates will rise once small companies have to implement the scheme. Firstly, they may be less financially able to bear the burden of partly funding employee pension plans. Secondly, they often have very little in-house knowledge about running pension schemes. “There’s been a lot of scaremongering about the costs of autoenrollment, particularly for small businesses,” says Tapper. “But I think it’s overdone. It is not that difficult to set up.” He notes the increasing numbers of providers launching products to make implementation easier. The scheme may even have caught the mood of the nation: “I think the financial crisis has changed many consumers’ priorities from being in debt towards wanting to save,” says Vidler. “People aren’t spending so freely.” Nonetheless, there is some expectation in the industry that opt-out rates will probably increase over time. But so far, so good. Allianz • 47 MICRO MICRO CAN ELDERLY WELL-BEING BE MEASURED – AND MAINTAINED? Global Age projections P r o p o r t i o n o f t h e w o r l d ’s p o p u l a t i o n aged 60 years or more: 22% 16% Aging populations in both industrialized and emerging countries are posing a challenge to policy-makers all over the world. Research can assist in coming up with effective solutions. 11% 2012 T POLICY DILEMMAS The long-term sustainability of public finances was a core issue of many policy measures in developed countries in recent times and – as pensions, health and care account for the lion’s share of public expenditure – they have been the 48 • Allianz 2050 Sources: UNDE SA Population Division, Population Ageing and Development 2012, Wall Char t, 2012; UNDE SA Population Division, World Population Prospec t s: The 2012 Revision, 2013. By Renate Finke, senior researcher he pressure that mass aging is placing on pension systems is a worldwide phenomenon that affects industrialized and emerging countries alike. It is driven by rising life expectancy in combination with decreasing birthrates. As a result, the number of elderly in society is growing, while the proportion of younger people is shrinking. The reasons lie in the interplay between better healthcare, improved nutrition and higher standards of living. The consequences affect different economic and societal areas and are complex. Although nearly all countries have been experiencing aging-related pressure, solutions are running at different speeds and start from different markers. As a result, policy-makers have differing perspectives on the impact of aging in their respective countries. In addition, policy approaches tend to tackle particular issues independently. Research can contribute to widening the approach and analyzing interactions between different areas of life and living conditions. The recently launched Global AgeWatch Index from HelpAge International, an organization that advocates the rights of the elderly, provides one such approach by combining aspects that contribute to a satisfactory life in old age. The index includes indicators for the four areas “income security,” “health status,” “employment and education” and “enabling environment.” A country’s ranking shows how well it is doing in supporting the well-being of its aging population and focuses attention on individuals. 2030 most affected areas. In an effort to ease pressure on public finances, most countries commenced pension reforms at the turn of the century, which saw benefit levels reduced and more responsibility placed on the shoulders of individuals to provide for their own retirement. While improving the sustainability of the system, these reforms have often left future retirees with the prospect of a lower replacement level from first-pillar pensions than today’s retirees. This has placed the question of the adequacy of retirement income on the political agenda. While it is no surprise that wealthier countries top the list of the Global AgeWatch Index, this may change in the future. Australia and New Zealand both rank high on the Allianz Pension Sustainability Index (PSI), which analyzes the Nearly all countries are feeling the pressure of aging, but their approaches and solutions vary greatly. sustainability of first-pillar pensions. It is interesting, however, to see that both have low rankings in the income security sub-index of the Global AgeWatch Index. This may point to the fact that sustainable pension systems struggle to deliver adequate levels of retirement income. On the other hand, Brazil ranks low on the PSI but has a relatively good ranking in the Global AgeWatch Index. Obviously, a more generous pension system together with a basic pension scheme for the elderly there protects people from old-age poverty, but this ranking could change. A young nation, Brazil’s population is bound to age rapidly in the near future, putting the country under pressure to overhaul its pension system and possibly cut back on pension levels. CHALLENGES OF PENSION REFORM It might seem odd to compare countries with such variation in economic development, but this approach can open the discussion on potential policy options and reform paths. The challenges in emerging economies are different from those of developed countries. When providing for old age, the challenge has been – and still is – to establish wellfunctioning public pension systems and broaden the coverage of existing ones to cope with the needs of a rapidly aging society. These are typical consequences of industrialization, rapid economic growth and urbanization. The experiences of other countries, either developed or emerging, might provide insights and ideas for setting up new systems. Emerging countries have to deal with drastic socio-economic changes that are placing traditional family support systems under pressure, increasing the need for organized retirement systems and basic income security systems. It is a challenge to set up an index with such a wide variation of countries and their different concepts of and prerequisites for living in old age. But the comparison can deliver surprising results, as the positions of Sri Lanka and Bolivia (ranked 36 and 46 respectively) show. We know from the setup of the PSI that it is very difficult to find data that are comparable across countries and detailed enough to come up with suitable insights and effective conclusions. But it can indeed initiate and foster the discussion of what is required to live a decent life in old age. For an intuitive understanding of aging, scan the code and view the interactive graph “Demographic Insights.” An updated version of the PSI is to be published in March. It will be extended to cover 50 countries, including Brazil, Chile, Mexico, Indonesia, Malaysia and South Africa. Allianz • 49 Video Bonus content in the PROJECT M app Global oppor tunities WIRED ON ECONOMICS Drama can provide a graphic illustration of economic analysis. Economist Peter Antonioni argues that the hit TV show The Wire contains more truth than many a dry formula. MACRO W ith the world facing many very real financial problems, you might wonder why any economist would turn his professional attention to TV drama. Although, given the damage some economists have wreaked in recent years, many people would perhaps be happier if more of them spent time engrossed in alternative worlds. Peter Antonioni, an economist from the department of management science and innovation at University College London, surprisingly agrees. “In a sense, all economists are fantasy writers, but not all fantasy writers are economists,” he quips, sitting wrapped up in the chilly courtyard of the Set Theatre in Kilkenny, Ireland. Victor Hugo, to name a few examples,” he says, pausing to sip from the pint of Guinness in front of him. “But at the moment, what really expresses our world is not the novel but the long-form television program.” He sees The Wire as a near-perfect dramatization of many key themes economists study, particularly all that can go wrong with a city’s ecosystem. It starts with cops and dealers, then spirals out to include the decline of the working class, political institutions, the school system, judiciary and media. Along the way, it illustrates such standard economic fare as the prisoners’ dilemma (why two individuals might not cooperate, although it is in their best interests to do so), as well as offering a twist on Nash’s Equilibrium (where two individuals stick to a chosen strategy because each strategy supposes knowledge of the other and a unilateral change brings no advantage). Central to understanding The Wire, argues Antonioni, is the tragic figure of Frank Sobotka, a union official who takes bribes to keep his struggling chapter alive. At one point, Sobotka says to a lobbyist, “You know what the trouble is, Brucey? We used to make s*** in this country. Build s***. Now we just put our hand in the next guy’s pocket.” The series is set at a time when Baltimore was a strong contender for murder capital of the US, with homicides numbering nearly Economic theory & stand-up comedy The evening before, at the 2013 Kilkenomics Festival, he delivered a talk on economics as it relates to The Wire. His sold-out performance mixes economic theory with stand-up comedy. Set in Baltimore, Maryland, The Wire is a television drama depicting a city on its knees, as seen from the perspective of the police, politicians, junkies, gangs, street kids and scared citizens. Antonioni explains that economic insight can come from anywhere, and it can sometimes be better expressed by artists than economists or analysts. “Throughout history, a lot of insights have come from literature – Sophocles, Dickens, » ALL ECONOMISTS ARE FANTASY WRITERS, BUT NOT ALL FANTASY WRITERS ARE ECONOMISTS. « The price of cocaine D r a m at i c d e c l i n e i n d o m e s t i c c o c a i n e p r i c e s d e s p i t e i n c r e a s i n g s p e n d i n g f o r o v e r s e a s d r u g s u p p r e s s i o n ef f o r t s b y t h e U n i t e d St at e s Note: Cocaine prices are purit y- and inf lation- adjusted and spending is inf lation- adjusted. All Prices e x pressed in 2011 USD. US i n t e r n a t i o n a l d r u g c o n t r o l s p e n d i n g (b i l l i o n s USD) 80 0 8 70 0 7 60 0 6 50 0 5 40 0 4 30 0 3 20 09 20 07 20 08 20 05 20 06 20 03 20 04 20 01 20 02 1999 20 0 0 1997 1998 1995 1996 1993 1994 1991 1992 1989 1990 1987 1988 1985 1986 0 1983 0 1984 1 1981 2 10 0 1982 20 0 US spending on international drug control (billions) P r i c e p e r g r a m (USD) Retail price per gram (USD) TV series The Wire depicts Baltimore as seen through the eyes of the police and the gangs, street kids and scared citizens. Source: US Of f ice of National Dr ug Polic y 50 • Allianz Allianz • 51 Macro The police combated the emergence of drug gangs with limited success. » THERE’S ALWAYS A BALTIMORE SOMEWHERE, WHETHER it’s CALLED MEDELLÍN, CIUDAD JUÁREZ OR DETROIT. « For more multimedia content featuring Peter Antonioni, please visit projectm-online.com/ new-perspectives/ wired-on-economics 52 • Allianz 50 per 100,000 residents annually. That rate is more than double the 20 per 100,000 recorded in 13th-century England, an era known for political instability, mayhem and bloodshed. Baltimore, both in fiction and reality, was then at the tail end of a period of industrial change that saw the percentage of people employed in manufacturing in the US decline dramatically from the 1960s onwards. While more is now being produced by fewer people to create greater general wealth, Antonioni argues that this transition comes at a significant cost. Economics is ‘gangster’ science With his bushy beard, thick-rimmed glasses, tattoos (a portrait of Austrian economist Joseph Schumpeter is inked on his inner right arm and an X-Men montage on his shoulder) and skull-hugging beanie, Antonioni resembles a minor character in his favorite television program. Perhaps one of the scruffier undercover cops or a shaggy docker watching helplessly as his job gradually disappears. In the chilly light of day, Antonioni is more earnest than he was the evening before. “Economics is ‘gangster’ science,” he says. “Not so much in the way, say, that Nobel Prize winners carry gold-plated Berettas, but rather in the way economists look at the world with a cold, hard eye, as if people don’t matter.” Antonioni says economists are poor at accounting for the transitional costs of industrial transformations. There are unemployment statistics, but intangibles like the costs borne by families and communities (such as rising rates of delinquency or declining mental health) cannot be easily assessed until the data comes out later. “This is where something like The Wire is challenging, because it dramatizes the social consequences and forces us to change cost-accounting models.” Unpacking the consequences With his position compromised, Sobotka let the rot set in. In real life, containerization – the packaging of cargo into large standard containers – had made it easier and cheaper to ship goods (including what the dealers call ‘product’) around the globe. Antonioni notes that, despite the billions spent and ‘successes’ achieved since Richard Nixon first spearheaded the war on drugs in 1971, the price for cocaine over the decades has been steadily falling (see graph on page 51). The consequence for Baltimore was the emergence of drug gangs. The police responded, sparking a local version of mathematician Lewis Fry Richardson’s Arms Race model, as both sides sought to counter the threat of the other, resulting in a heavy body count and corrupt leaders. The middle class fled, which drained the tax base. Parts of the city then fell into disrepair – with high local unemployment, fragmented families, crime and abandoned buildings creating a desolate, inhospitable city landscape. At the end of The Wire, despite a few minor personal victories achieved by some of the more likeable characters, there is a hopeless feeling of déjà vu: major institutions further corrupted; a greasy, venal officer in charge of the police; and a psychopath controlling the drug trade. “Baltimore in The Wire seems to be a microcosm of US governance at the beginning at the 21st century,” Antonioni reflects. “Maybe this is only a temporary period. But in another sense, there is always a Baltimore somewhere in the world, whether it’s called Medellín, Ciudad Juárez or Detroit. “Should we be depressed about it?” he asks, but doesn’t wait for an answer. “We should be angry about it! We should look for alternatives and realize the damage that is being caused by the war on drugs. As one of the police in the series says, it can’t even be called a war, because wars end.” MAcro From the Labs Dwindling prices on data storage, explosive growth in mobile data output and a continued battle against cybercrime – digitalization is changing all facets of business as we know it. Explosive Data Growth from Mobile Devices: The accumulated amount of data generated exclusively by mobile devices (phones, tablets, phablets) is expected to reach 11 exabytes (billions of gigabytes) by 2016. Source: OECD, Exploring Data-Driven Innovation as a New Source of Growth,2013 11,000,000,000,000,000,000 B Value in numbers Full use of big data in Europe’s 23 largest governments might reduce administrative costs by 15-20%, creating the equivalent of $206 billion to $412 billion in new value. Similar studies from the United Kingdom show that the public sector could save $3.3 billion in fraud detection and generate $6.7 billion through better performance management by using big data analytics. Source: OECD, E x ploring D ata- Dri ven Innovation as a Ne w Source of Grow th, 2013 Data intensity on file Data intensity (measured as the average amount of data per organization) is highest in financial services, communication and media, utilities, government, and discrete manufacturing. In these sectors, each organization typically stored over 1,000 terabytes (1 petabyte) of data in 2009. S ource: OECD, E x plor ing D ataD r i ven Innovat ion as a N e w Source of Gr ow t h, 2013 What's in a name? Fear of losing reputation through social media is one of the biggest growing concerns among businesses, according to Allianz experts. On the 2014 index of Changes in overall risk perception, fear of losing brand value through digital activity jumped four spots from 10th to 6th. Source: Allianz Risk Barometer on Business Risk s , 2014 Decline in Data Storage Costs The average cost per gigabyte on consumer hard disk drives has dropped from $56 in 1998 to $0.05 in 2012 – an average decline of almost 40% a year. Source: OECD, E x ploring D ata- Dri ven Innovation as a Ne w Source of Grow th, 2013 Growing challenges A severe data breach is estimated to cost a US company $5.4 million on average, the highest in the world, according to Allianz Global Corporate & Specialty. US organizations experience an average of 122 successful attacks per week, up from 102 per week in 2012. The average time it takes to solve a cyber-attack is 32 days. In 2012 it was 24 days. More than 1 million people worldwide become victims of cybercrime every day Source: Ponemon Research Institute: Cost of Cy ber Crime 2013 Stud y Cyber-security Staying safe Businesses in the United States spend the most on cybercrime (on average, $8.9 million annually per business), followed by Germany ($6.0 million). Cybercrime costs were much lower in Australia ($3.4 million) and the United Kingdom ($3.3 million). Source: w w w.inf ormationweek .com/at tack s/ c y bercrime- at tack s- cost s- escalating/d/d-id/1106719? Allianz • 53 Video Bonus content in the PROJECT M app MACRO CHINA’S CURRENCY STEPS ONTO THE WORLD STAGE China is determined to make its currency, the renminbi, a major force in the global market. But the country’s path to internationalization has left many foreign investors unsure of what its next step will be. 54 • Allianz A s China moves increasingly to cement its role as an international economic power, the internationalization of its currency, the renminbi (RMB), plays a key role. Little used as a means of trade and investment outside China, the RMB is slowly but insistently promoted by Chinese authorities around the globe. The use of the RMB outside China has grown steadily since the project was launched in 2009. But Paola Subacchi, research director of international economics at Chatham House, says the development of the RMB into a truly global currency is held back by the tight grip policy-makers in Beijing still have on it, by foreign investors’ uncertainty where the process of internationalization is heading and by China’s inability so far to assuage doubts about the future of its monetary policy. The current two-pronged push to expand foreign use of the RMB promotes the use of renminbi in cross-border trade while creating an offshore RMB market. But Subacchi cautions that this internationalization process is essentially a temporary measure. “It’s a way to overcome the lack of convertibility,” she says, “a process to increase the use of the renminbi while China is preparing the ground for the renminbi to become a ‘normal’ currency.” Subacchi views the outward push as “one step in a long and complex process of developing the currency,” which fits alongside wider moves to reform interest rates and the financial sector, and even improve corporate governance. The center of the expanding RMB offshore market is Hong Kong, the traditional trade conduit to mainland China, which currently handles over 60% of China’s foreign direct investment and more than 80% of all RMB payments. In 2011, China moved to boost the use of the renminbi in Europe by choosing London as a second RMB offshore center, albeit reliant on Hong Kong for its liquidity. The European market shows great potential, accounting for 47% of the total value of RMB payments in the first quarter of 2012, more than the entire Asia-Pacific region. But in terms of investment in RMB-denominated financial products, the European market is held back by doubts over the currency. London less keen than Hong Kong “If you talk to people in Hong Kong,” says Subacchi, “lots of investors are happy to hold renminbi in their portfolios because of the proximity to China, because they understand China and its policies and political dynamics. But if you talk to people in London, they are considerably less keen to hold renminbi in their portfolios, because they see it as a non-convertible currency.” The government’s control over the renminbi is viewed by many as a major liability, with the currency potentially subject to the whims of Beijing policy-makers. The task of building this necessary trust with Western investors is “really very difficult,” Subacchi says. “There isn’t a series of policies they can implement. People need to trust the government, that the government will apply the rule of law and not do anything to completely change the policy or undermine the currency.” The internationalization of China’s currency marked another milestone in September, with the launch of the MACRO Shanghai Free Trade Zone (FTZ). China’s State Council declared that the zone would play host to a “pilot and test” of a convertible renminbi capital account, making the zone China’s first onshore RMB market center. In the weeks following the official opening of the FTZ, however, foreign investors still have only a murky sense of what exactly the zone is and how Chinese authorities intend to pursue their stated goals within its boundaries. Potential of the Shanghai Free Trade Zone Foreign banks in particular have been hesitant to set up branches in the Shanghai FTZ. So far, six foreign banks have applied for and received approval to open branches in the free trade zone, with others preferring to wait until more concrete regulations are unveiled. Subacchi sees little cause for concern in this official opacity, a standard approach to new and potentially risky projects that has been seen many times before. “In 2009, when the pilot scheme for RMB trade settlement was launched, nobody really knew what it was, and not even the authorities had a clear idea,” she recalls. “In a very Chinese fashion, there was a case of moving step by step, ‘crossing the river by touching the stones,’” explains Subacchi, using a phrase commonly used to describe Deng Xiaoping’s cautious approach to introducing China’s first post-Mao market reforms. “They literally created a policy, tested the market reaction, and moved on.” Those familiar with China’s strategy are well aware of the potential of the Shanghai Free Trade Zone. “There is a lot of concern in Hong Kong that Shanghai might overtake them and become the key financial center,” Subacchi notes. “At the moment, the authorities have been very careful to reassure Hong Kong that this is not going to happen.” Given the pivotal position Hong Kong holds in the offshore RMB market and the ambiguity surrounding Shanghai’s nascent role, a shift in the balance of power is unlikely anytime soon. Subacchi stresses, however, that while the expansion of offshore RMB centers is key to China becoming a major presence in global financial markets, Chinese authorities are building a system to last. “We have to be clear,” she cautions. “Eventually the renminbi will be a fully conversable currency. Therefore there will be no need for this kind of construction, and Hong Kong in particular will be less relevant as an offshore center.” Similarly, the importance of London and other cities hand-picked by Chinese officials as RMB trading hubs will also diminish once control of the currency eventually leaves the official domain for that of the market. Allianz • 55 MAcro Inter view Bonus content in the PROJECT M app MAcro INEQUALITY FOR ALL Political economist and commentator Robert B. Reich is out to expose the heart of our economic problems. For over 30 years inequality has been worsening. R obert B. Reich dissects the state of the American economy with his writings and movies. In an interview with PROJECT M he delivers a clear message: the gap between rich and poor needs to close for the good of society. The book Aftershock and the film Inequality for All discuss widening inequality in the United States. How dramatic is the situation? Robert Reich: Well, 95% of all the economic gains since the start of the recovery in 2009 have gone to the top 1%. The rest of America has shared the remaining 5%. The medium household income continues to drop, adjusted for inflation. This means even families with two wage earners are doing worse than they did before the recession. In other words, we haven’t seen this degree of inequality in a century. contributed towards widening prosperity in these ways. In other periods – the 1890s, 1920s and more recent years – the pendulum swung in the opposite direction. unequal recovery Are you saying that the democratic system has been corrupted by the rich? Reich: I am stating it unequivocally! You have never seen this amount of money in power, at least in living memory. You have to go back to the 1890s – when the lackeys of the robber barons would literally put sacks of money on the desks of legislators – to find anything similar. The Supreme Court in 2010, in a shameful decision called “Citizens United against the Federal Election Commission,” opened the floodgates to money and politics. It is now literally possible to purchase a president or a governor. Going back to before the Great Crash of 1929? Reich: Actually, if you look at wealth as well as income, we haven’t seen something like that since the days of the robber barons in the 1890s. RO B E R T B . R E I C H Chancellor’s professor of Public Policy at the University of California at Berkeley. He served in the administrations of US Presidents Gerald Ford and Jimmy Carter and was secretary of labor under President Bill Clinton (1993-1997). He has written 13 books, including the best-sellers Aftershock and The Work of Nations. 56 • Allianz What are the mechanisms whereby society becomes more equal? Reich: The times in which the United States moved towards equality and more widespread prosperity were periods in which higherquality education was more widely accessible, when the nation made substantial investments in infrastructure, the top tax rate was much higher, financial regulations were stricter, the right to unionize was observed and companies were required to bargain in good faith with unions. And when money did not reach an overwhelming influence on the political process. Reforms between 1901 and 1916, 1933 and 1940, and also 1963 and 1969 all So what makes it swing back? Reich: Well, when the moneyed interests get a greater foothold in politics and begin to entrench themselves, we reach a point where capitalism goes so far off track that the public demands changes. In this country those changes have primarily been in the direction of reform rather than major political upheavals towards fascism, socialism or communism. Our preference, deeply ingrained, is to save capitalism from itself, from its own excesses. A B Not all Americans b e n ef i t e q u a l l y f r o m e c o n o m i c r e c o v e r y. Si n c e 20 0 9, 95% of gains have gone to t h e t o p 1% (A), w h i l e t h e r e s t of t h e p o p u l at i o n h a v e h a d to settle for the r e m a i n i n g 5% (B). America is not the only country where inequality is growing. Australia, Canada, the United Kingdom and others are experiencing growing inequality. Reich: The causes are similar. Among rich countries, the United States has witnessed the greatest lurch towards inequality, though others are close behind. The underlying dynamic has to do with globalization and technological displacement of workers. But other nations have developed political and institutional Allianz • 57 MACRO bulwarks against as much inequality as the United States has. Now, I am not suggesting the US move towards European-style social democracies. In my book and movie, I make a more modest proposal: that the US simply moves back to the society we had in the 1950s to early 1970s, when we had institutions and laws that dramatically reduced inequality and spread prosperity more widely. their lives. This is a higher percentage than in any other rich nation, higher even than the UK with its history of class consciousness. Widening inequality would be far less of a problem if we had ease of upward mobility. Even though many US citizens have become poorer, they still cling tightly to the American Dream. That seems a triumph of fantasy over reality and is difficult to understand. Reich: It is quite simple actually. When Americans are afraid and frustrated, when they are anxious about their economic status even though they are working harder than ever, then they are vulnerable to demagogues on the right or left who seek scapegoats. Some of the scapegoating is directed at government, some at the rich and big corporations, some at immigrants and the poor, some at labor unions. In reality, the system has gone awry. The wealthy would do better with a smaller share of a rapidly growing economy than they are doing now with the large share of an economy barely growing. The reason why the economy has stopped is that the vast middle class doesn’t have enough purchasing power to keep it growing. And the reason it doesn’t have the purchasing power is that almost all economic gains are going to the top. Even Bill Gross, head of PIMCO*, the bond trading firm, in November (see online article “Scrooge McDucks”) called upon the wealthy to recognize the dangers from this kind of inequality. After the Great Crash of 1929, the GlassSteagall Act was introduced. This is credited with ensuring stability in the financial system for decades, so it seems surprising that there is little agitation to have it re-introduced. Reich: As I speak to different community groups, labor groups, Democratic groups and occasionally even Republican groups, all I have to do is just mention Glass-Steagall and I get a round of applause. This is quite remarkable as, five or six years ago, no one even knew what Glass-Steagall was. The Clinton administration in 1999 made the mistake of joining Republicans and repealing Glass-Steagall. To ensure Wall Street won’t melt down once again, we need two things: not just to resurrect Glass-Steagall, but also to cap the size of the biggest banks. Unless we do both, we risk a repeat of 2008. Your net worth puts you in the top 1%. Does anyone question your credentials in speaking for the 99%? Reich: If you look back in US history, some of our greatest reformers have been wealthy: Franklin D. Roosevelt, Teddy Roosevelt, John F. Kennedy – all were from exceedingly wealthy families. Warren Buffett is in favor of much higher income tax on the wealthy. Bill Gates Sr. has led a charge for closing tax loopholes for the wealthy. There is no inconsistency in being in the top 1% and at the same time arguing that the organization of our economy is out of whack. In the book The Spirit Level, there is a line that says, “If you believe in the American dream, move to Denmark” – because upward mobility is no longer a feature of US society. Reich: Well, mobility has slowed considerably. Some 42% of children born into poverty in the United States will remain in poverty throughout * PIMCO is an autonomous subsidiar y of Allianz. 58 • Allianz Reich’s work includes Inequality for All, which won the Special Jury Prize at the 2013 Sundance Film Festival. I n ter v ie w To listen to an audio version of the interview, please go to projectm-online.com/ leading-thoughts/ inequality-for-all Do you think equality is recoverable in the United States? Reich: We have done it three times over the last century. It is the matter of political will. The socalled free market doesn’t exist in the state of nature. The market is based on rules, and those rules emerge from legislators, courts and agencies. There is nothing that dictates the inevitability of widening inequality. If we wanted to, if our political system was not engulfed in money, if Americans understood the problem we face, we would change those rules towards more widespread prosperity. We have done it before and we will do it again. The alternative is an economy that no longer functions and a democracy incapable of reflecting the public will. Picture Galler y Bonus content in the PROJECT M app macro POPULATION AGING CREATES CAPITAL REPAYMENT RISK FOR GOVERNMENT BONDS Good news for all of us as individuals is now potentially bad news for those who invest in government bonds. The reason is the dramatic rise in the percentage of people in the ‘New Old’ 55+ generation. By Paul Hodges T he good news is that life expectancy has increased by 50% since 1950, to around 70 years. Thus today there are already 1 billion ‘New Olders,’ compared with just 300 million in 1950. And the UN Population Division forecasts they will number 1.8 billion by 2030. The bad news is that fertility rates have also fallen by 50%, with each woman now having an average of just 2.5 children. Until 2000, the post-World War II baby boom disguised the problem this created for investors, as the proportion of New Old in the adult population remained constant at around one in five. But since then, it has been rising very rapidly, such that the proportion of New Old will be almost one in three people by 2030. “Where’s the problem with this?” you might well respond. Life expectancy 200 years ago, after all, was only around 36 years old in the developed world and 24 elsewhere. And even when Otto von Bismarck and David Lloyd George introduced the world’s first state pension schemes in 1888 and 1909 respectively, Western life expectancy was less than 50 years. Yet today, US residents aged 65 still have on average a quarter of their lives ahead of them. rethinking pensions The problem is that our thinking about work and pensions has not caught yet up with these developments. Bismarck and Lloyd George saw pensions as being means-tested social insurance and set pension age at 20 years above life expectancy. A pension was meant to be a small amount of money paid to a small number of people for a small period of time. Thus only 600,000 of the UK’s 40 million population were initially eligible to receive a pension in 1909. Lively for much longer: the New-Old adult population Yet today, pensions are a universal entitlement, with 13 million receiving a UK pension. And instead of pension age being 20 years above life expectancy (or around 100), it is instead now below the 1909 level. Until recently, this paradigm shift created a benign environment for bond investors, as people realized they needed to increase their savings and spend less, in order to finance their unexpectedly long life. They naturally favored ‘safe’ Western government bonds, given stock market uncertainties. In addition, of course, the shift from spending to saving helped to reduce inflation and created a more deflationary environment. Japan is the obvious model for this shift. Its baby boom took place earlier than in the rest of the G7, meaning that its Allianz • 59 macro the development of a global Aging population N e w O l d 55 + p o p u l at i o n , & p e r c e nt a g e of a d u l t s w o r l d w i d e , 195 0 -20 30 (F ) N e w O l d 55 + M i l l i o n s New Old % of Adults 2,0 0 0 32% 1, 80 0 30 1,60 0 1,40 0 24% 1, 20 0 1,0 0 0 35 22% 21% 25 22% 80 0 20 60 0 40 0 15 20 0 2030 (F) 2020 (F) 2010 20 0 0 1990 1980 1970 1960 10 1950 0 Source: Unite d Nations Population Di v ision society’s proportion of New Old rose from a benign 20% of the adult population in 1970 to 32% by 1990, and 47% today. In turn, its government bond yields fell from 8% in 1990 to current levels of 1%. Other G7 countries have seen the same phenomenon in more recent years, as Germany and Italy’s New Old percentage has risen to 43%, and the US and UK’s to 36%. » m odern genetics has not yet found a way of turning 55-year-olds back into wealth-creating 35-year-olds. « By 2030, almost one in three of the global population will be ‘New Olders,’ creating problems for governments previously in denial. But this virtuous cycle is now in danger of turning vicious, as doubts increase about governments’ ability to repay today’s historically high levels of borrowing when growth remains anemic at best. The problem is twofold: first, aging populations inevitably reduce economic growth. Official data for household spending confirms the common-sense conclusion that spending peaks by the age of 55 once the kids leave home. Older people essentially represent a replacement economy, as they already own most of what they need, while their incomes reduce as they approach retirement. And, given that household consumption is 60% of GDP, this means the economy will slow as the New-Old percentage rises. Second, policy-makers ignore this issue at their peril. They have been too cowardly to propose meaningful increases in pension age, or even to warn that the ‘demographic dividend’ had turned to ‘demographic deficit.’ Instead they have tried to restore growth by following the failed Japanese playbook of major stimulus spending and massive increases in government debt. Ignored warnings They have thus chosen to ignore last year’s warning by former Bank of Japan governor Masaaki Shirakawa: “most Japanese people, along with economists, did not grasp the gravity of population aging coupled with a low birth rate for Japan’s economy.” China has made the same mistake: its one-child policy, in force since 1978, will cause its New-Old population, currently at a moderate 20%, to double by 2030. Today, therefore, the main question now facing government bond investors is when to jump ship. They have profited hugely over the past two decades from the increase in saving and low inflation rates caused by the rise of the New-Old generation. But now they face the risk of a ‘Custer’s Last Stand,’ with policy-makers continuing to believe they can somehow kick-start growth by adding yet more debt. Contrary to expectations, this debt will not be inflated away as in the 1970s. Back then, the rapid rise of the boomers created a vast increase in demand at a time when the small interwar generation was totally unable to provide the necessary supply. But today, the supply-demand balance is instead moving steadily in the opposite direction. Rising proportions of New Old inevitably create a deflationary rather than inflationary environment, as the various consumer price indices are increasingly confirming. Thus the old adage of ‘don’t fight the Fed’ will progressively face the reality that modern genetics has not yet found a way of turning 55-year-olds back into wealthcreating 35-year-olds. Western government bonds will carry increasing capital repayment risk until policymakers finally agree to recognize the true economic consequences of today’s aging populations. Pau l H o d g e s Paul Hodges is the chairman of advisory group International eChem (IeC) and the author of Boom, Gloom and the New Normal: How the Western BabyBoomers are Changing Demand Patterns, Again www.new-normal.com Allianz • 61 Meta The out sider’s v iew THE OLD MAN AND THE Cs “ W hen did I f ir st k i ss a girl? ” a sk s 102-year- old Lionel Ferbos , repeat ing the quest ion. “I don’t k now. There were so many of them .” C Name Lionel Ferbos Born 17 July 1911 Awa r d s 2003 Big Easy Lifetime Achievement Award See the Century Club interview with Lionel at www.projectm-online. com/demographics/ the-old-manand-the-cs 62 • Allianz reole singer and trumpeter Lionel Ferbos is the oldest actively working musician in New Orleans, the jazz capital of the world. He first picked up a cornet at a French Quarter pawn shop at age 15 after seeing an all-girl band playing horns. Most Saturday nights he still leads the band at the packed Palm Court Jazz Cafe, the venue where he has had a standing booking for more than two decades. He occasionally has gigs with younger, renowned musicians, such as Troy “Trombone Shorty” Andrews, Irvin Mayfield and Jason Marsalis. He has also played every year at the New Orleans Jazz & Heritage Festival since its inception in 1970. Born on 17 July 1911, Lionel used to make about a dollar a night in the early 1930s with bands such as the Starlight Serenaders at society events and the famed Pelican Club. It wasn’t much money, but they had a good time. Back then, Jim Crow still ruled the South. Black bands could play to white audiences, but there was no mixing, not even with white musicians. “But white musicians wanted to play with us, because we were the best,” recalls Ferbos. “Segregation, it was absurd.” Lionel is surprised he’s still alive. “I never thought I would make it much past 50,” he confides. “I was a sickly child with asthma.” Music has been good to Lionel. He played with the greats of his day, including Captain John Handy, Walter “Fats” Pichon and blues singer Mamie Smith. He also performed with saxophonist Harold Dejan and trumpeters Herbert Leary and Gene Ware and toured Europe eight times. With his dapper clothing style and crooning voice, Ferbos proved a hit with women. For a while, he was known as the “Sheik,” at least until he met Marguerite Gilyot, who became his wife in the 1930s. She died in January 2009 after 75 years of marriage. The pain of his loss is still evident when he talks about her. Lionel has had 15 operations in recent years. He is now cared for by his daughter Sylvia in a house that was ravaged by Hurricane Katrina in 2005 and subsequently rebuilt. When asked about the secret of his longevity, he replies with a line echoing his guest appearance on the hit HBO television series Treme. Looking the interviewer straight in the eyes he says, “There is a lot to be said for doing just one thing right.”