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Sophia Van, Swiss Re, Presentation at The Chief Data & Analytics Officer Forum, Singapore

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Welcome to the Chief Data and Analytics Officer Forum, Singapore.

The CDAO Forum Singapore gathered some of the region’s leading data and analytics executives to share their insights and case studies on developing the infrastructure, ecosystem, buy-in, culture whilst providing the strategies to turn data into a strategic asset.. This two day event presented a roadmap from the building blocks of data strategy, governance and value awareness to championing the benefits of increased returns, better customer service and reduced risk enabled by data analytics.
http://www.cdaosingapore.com

We are delighted to announce the dates for our Melbourne Chief Data & Analytics Forum, 5-7 September 2016.
http://www.cdaoforum.com/

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Sophia Van, Swiss Re, Presentation at The Chief Data & Analytics Officer Forum, Singapore

  1. 1. Big Data and its impact on the insurance industry Sophia Van VP, Strategy & Innovation, Asia, Swiss Reinsurance July 2016
  2. 2. Swissnex risk dialogue | Matthias Weber | 15 April 2015 Where are we and where are we going? 2
  3. 3. 3 In 2009, Uber received the first seed funding of US$200,000. How much is Uber’s estimated valuation today? a. 250.1 million b. 1 billion c. 50.5 billion d. 62.5 billion
  4. 4. 4 "At $831.5 million, investment in insurance tech this year is already up nearly ______ times what it was in 2010" a. 3 b. 6 c. >10
  5. 5. 5 How many Innovation Labs/ Centres have been set up in Singapore last 24 months (for all industries)? a. Around 4 b. Around 10 c. Around 18 or more
  6. 6. 6 Industrial Revolution I & II
  7. 7. 7 Digital Revolution
  8. 8. 8 The Fourth Industrial Revolution? Internet of Things + Big Data
  9. 9. 9 "I never think about the future – it comes soon enough" - Albert Einstein
  10. 10. 10 Technology + Consumers + Governments Who changes the world?
  11. 11. 11 Technology
  12. 12. 12 Consumers
  13. 13. What we share with one another every second 13 http://pennystocks.la/internet-in-real-time/
  14. 14. 14 Governments Smart Engergy Smart Water Smart Building Smart Transport Smart Health Smart Cities
  15. 15. 052000 60,000 20201510 50,000 40,000 30,000 20,000 10,000 0 Data availability is increasing exponentially 25.0 94.0 99.0 99.9 x % of data in digital form Big Data & Smart Analytics are about: ▪ Creating and extracting information from large amounts of available data (internal and external) ▪ Applying innovative approaches/methodologies in analysing available data to expand the reach of knowledge and customer insights Examples Source: McKinsey research, Forbes, Internet World Stats, IBM, The Economist By 2020, 29.5 Billion Connected Things globally and 1/3 is in APAC. 83% of IT Executives see Smart Analytics and Big Data as part of their strategic vision 80% of all data is unstruc- tured, only 20% of available data are leveraged from traditional systems in Exabytes 15 The new world of Big Data & Smart Analytics
  16. 16. 16 APAC will not escape the “Big Data tsunami”
  17. 17. Singapore • Smart Health is an important pillar under Singapore Smart Nation vision • Analytics is defined as a key enabler capability • Variety of fundings for Innovation & Analytics available. 17 Regional Innovation / Analytics Centers of substantial scale set up in Singapore utilizing government fundings. • Environmental data collected via sensors are published at data.gov.sg • Three main ideas unveiled: smart logistics with interoperability across supply chain, Smart Nation Tech Challenges, and Smart Health Assists in Jurong Lake District. China • 200+ Smart Cities Initiative • IoT and Connectivity are expected to be the emphasis of the 13th 5 year plan (starting in 2016) • The State Council issued some guidelines promoting commercial health insurance development in 2014, encouraging information sharing and the creation of health insurance information systems. South Korea Songdo –the world's first smart city close to final completion in 2016. India • 100 Smart Cities Initiative announced in Union Budget 2014 with US$1.1 billion provided to be launched soon in 2015. • Smart Health is the lifeline for Smart Cities Japan Pilot projects are running in 4 cities (Yokohama, Toyota City, Keihanna Eco City, Kitakyushu) Malaysia Industry-led IoT data centre and research lab set up with Feb 2015 with focus on wearables in healthcare APAC will not escape the "Big Data tsunami" APAC will take the lead over in Smart Cities by 2025 17 22 out of 37 major smart cities across the globe are in APAC by 2022 with the investment of 63.4 billion from 2014 to 2023
  18. 18. Singapore Smart Nation 18 Healthcare Transport Logistic Environment Analytics Security Sensors Smart Cities 5G/ HetNet Singapore Smart Nation Smart Nation is built on data & the ability to move, collect and make sense of it before we can glean insights that can improve lives.1 Singapore as a global Analytics Hub Key areas Enabling Capabilities 1. source from IDA
  19. 19. APAC is the opportunity land for Big Data 19 “Asia is a hotbed of digital adoption”1 By 2020, 1/3 of connected things (8.6 billion) will be in APAC2 Huge protection gap is the opportunity for innovation US$58 trillion mortality gap in 20143 Source: 1. Master Card. 2. IDA 3. Swiss Re Mortality Protection Gap report 2015
  20. 20. Swissnex risk dialogue | Matthias Weber | 15 April 2015 Technology advance and Big Data is transforming the way insurance is underwritten, sold, and engaged 20
  21. 21. Changing risk landscape will require insurers to adapt their underwriting capabilities 21 Risks change hands New risk pools will emerge Some risks will shrink and some potentially become more extreme
  22. 22. 22 New data sources will revolutionize underwriting Sensors Genomics Platforms Real-time. Personalized. Fast. Accurate. Transparent. Disruptive
  23. 23. Wearable sensors Smart lenses Smart garments Smart Pill Enhanced monitoring of our behaviours Source: www.proteus.com 23
  24. 24. Genomics is a big data problem 24 6 billion DNA letters 22,000 genes 313 Exabytes if everyone in the US has their genes sequenced which gene mutation are associated with which diseases
  25. 25. Genomic sequencing Increasing speed of developments Sanger (capillary) sequencing 2020 ? ~1day ?? $500 2005 ~3 years ~$ 20million 2010 ~1month $9,500 (Illumina) AML Melanoma Small-cell lung Breast 2008 ~4 months ~$ 1.5million Lung(NSCLC) Cancer Genomics 2000 ~10 years ~$ 3.5 billion Myeloma Hepatocellula r CLL MouseAML Next generation sequencing 25
  26. 26. PatientsLikeMe New communities for patient-led data sharing 26
  27. 27. 27 The New World of Connected Health Pharmacy Non-living things linked to living things Smart wheelchair RFID tags Companion Robot Mobile & apps Wearables Public Authority Care Providers Connected Health Labs Smart Home Smart Appliances Environment Weather Station Air pollution sensor Source: CitiSense Source: wikimedia
  28. 28. Technology makes the mission possible! 28
  29. 29. Predictive Underwriting Innovations in Underwriting 29 New data sources (genetic data, behavior, wearables, etc.) New tools and technology (text analytics, etc.)  Better Risk Assessment  Efficiency  Differentiator Evidenced- Based UnderwritingAutomated Underwriting Real-time. Personalized. Fast. Accurate. Transparent. Disruptive
  30. 30. Evidence-Based Underwriting 30 Lab Data Medical Journals Biomedical databases Prescription Data Information Exchange Government Agencies Wearable Device Data Genetic Info ? ?
  31. 31. Smoker Propensity Model 31 The model could be used to simplify application process
  32. 32. 32 Automated Underwriting
  33. 33. New data sources and engagement mechanism create opportunities to insure the uninsurable 33 Healthy Behavior Unhealthy Behavior Unhealthy Healthy Controlled Educate & Motivate
  34. 34. The way insurance is sold and engaged is ripe for disruption 34 Trends Risks Opportunities • Emergence of online market places and new ecosystems • Increased adoption of internet & mobile-based channels • Ubiquity of connected devices • Behavior Economics • Gamification • P2P/ Blockchain • Commoditize personal & small commercial risks • Lose ownership of customer relationship • Fail to secure partnership in the new ecosystems Increase loyalty, reach, & differentiation by: • Innovative bundled engagement services • Better customer insight (granular segmentation) and personalized products • Context-based / UBI/ On- demand solutions • Simplification
  35. 35. Swissnex risk dialogue | Matthias Weber | 15 April 2015 What is happening in the insurance industry? 35
  36. 36. Startups are invading insurance tech 36 X3 (2014-2015) In 2014, less than $700M in funding is for insurance tech. By Q3 2015, insurance tech startups have attracted more than three times as much funding. funding. Funding to global insurance tech startups VC investors X7(2011-2015) Less than 50 investors in 2011. Through Q3’15, the number has jumped past 380. Key players in insurance tech space 120+startups, VCs, corporate investors, accelerators source: CBINSIGHTS
  37. 37. Multiple tech giants have moved into insurance 37
  38. 38. 38 Increasing spending on evolutionary innovation Legal & Compliance Customer Management Pricing, Risk Assessment and Selection Distribution and Service Management Innovative Products Claims & Fraud Management Opportunities Source: Global Digital Insurance 2015, Bain 24% in life 27% in P&C Average growth in annualized spending on analytics
  39. 39. Corporate Ventures Innovation Labs/ Centres Startup Deals Partnership Some re/insurers and intermediaries have made bold steps
  40. 40. 40 Disrupt or Not to Disrupt? “I think insurance is in the Stone Age while other people are circling Mars.”–Mark Wilson CEO, Aviva plc, October 2015 “(Insurance) is an industry that has been lagging behind every other industry –it has been paralyzed.Either you understand it and you move towards the forefront of change…or this industry will disappear.”–Mario Greco CEO, GeneraliGroup, May 2015 “Asia Ripe for Life Insurance Disruption” –Jay Walker, founder of Priceline.com “In my previous life as a McKinsey consultant, I advised the top insurance companies on projects that were, at their core, incremental. They were always about increasing the productivity of the agent-based salesforce, or improving the efficiency of paper-based claims operations. In other words, what I was doing was putting the dinosaur on a diet and prodding it with a stick.” –Jennifer Fitzgerald, Founder & CEO, PolicyGenius
  41. 41. 41 Big Data is important for the insurance industry… … because insurance is an information based business! Legal & Compliance Financial Operational Ethical Risks Legal and Compliance Data Business Model Technology Skills Foundation Customer Management Pricing, Risk Assessment and Selection Distribution and Service Management Innovative Products Claims & Fraud Management Opportunities
  42. 42. Organization Key Capabilities to Capitalize Big Data 42
  43. 43. Swissnex risk dialogue | Matthias Weber | 15 April 2015 Thank you 43
  44. 44. 44
  45. 45. Swissnex risk dialogue | Matthias Weber | 15 April 2015 Legal notice ©2015 Swiss Re. All rights reserved. You are not permitted to create any modifications or derivative works of this presentation or to use it for commercial or other public purposes without the prior written permission of Swiss Re. The information and opinions contained in the presentation are provided as at the date of the presentation and are subject to change without notice. Although the information used was taken from reliable sources, Swiss Re does not accept any responsibility for the accuracy or comprehensiveness of the details given. All liability for the accuracy and completeness thereof or for any damage or loss resulting from the use of the information contained in this presentation is expressly excluded. Under no circumstances shall Swiss Re or its Group companies be liable for any financial or consequential loss relating to this presentation. 45

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