Big Data for Insurance Industry A perspective from Swiss Re

Big Data for Insurance Industry A perspective from Swiss Re Fredi Lienhardt, Manager Big Data & Smart Analytics Centre, Swiss Re 01 July 2014, Rüschlikon Picture Copyright: thep urai/shutterstock everything possible/shutterstock

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Why are companies investing so much into "big" data? Swiss Re Big Data & Smart Analytics Centre Big Data im Gesundheitswesen 01 July 2014 3 Picture Copyright: thep urai/shutterstock everything possible/shutterstock

Swiss Re at Glance Insurance Value Chain Examples Challenges and Opportunities Q&A Swiss Re Big Data & Smart Analytics Centre Big Data im Gesundheitswesen 01 July 2014 4

Swiss Re Swiss Re is a leading and highly diversified global re/insurance company 150 years of experience in providing wholesale re/insurance and risk management solutions Headquarters, Zurich We deliver both traditional and innovative offerings in Property & Casualty and Life & Health that meet our clients' needs Armonk, New York A pioneer in insurance-based capital market solutions, we combine financial strength and unparalleled expertise for the benefit of our clients The Gherkin, London Our financial strength is currently rated: Standard & Poor s: AA-/stable; Moody s: Aa3/stable; A.M. Best: A+/stable Swiss Re Big Data & Smart Analytics Centre Big Data im Gesundheitswesen 01 July 2014 5

Swiss Re is broadly diversified by geography and product line Net premiums earned 1 2013 (USD 28.8 bn) by region (in USD bn) and by business segment: 11.5 11.3 6.0 Corporate Solutions 10% Admin Re 5% Americas 40% Europe Asia (incl. Middle East /Africa) 39% 21% L&H Re 35% P&C Re 50% Swiss Re benefits from geographic and business mix diversification and has the ability to reallocate capital to achieve profitable growth 1 Includes fee income from policyholders Swiss Re Big Data & Smart Analytics Centre Big Data im Gesundheitswesen 01 July 2014 6

Rating / Brand Products & Services Capacity Price Insights Swiss Re Insurer Insured Added Value? Share of Wallet Client Retention New Clients Strengthened Brand Swiss Re Big Data & Smart Analytics Centre Big Data im Gesundheitswesen 01 July 2014 7

Big Data is important for the insurance industry because insurance is an information based business! Big Data enables to Customized Products and Segmentation To get a better understanding of our clients Risk Assessment To improve our risk assessment Claims Fraud Detection To improve the fraud detection in Claims Emerging Risks To detect and address new risks Swiss Re Big Data & Smart Analytics Centre Big Data im Gesundheitswesen 01 July 2014 Picture Copyright: 8 thep urai/shutterstock everything possible/shutterstock

Predictive UW for life insurance & critical illness Context The Problem In late 2013, Aviva & RBS successfully launched "pre-approved" life insurance with Swiss Re's predictive underwriting model. They now wish to extend this to Critical Illness We do not know yet now if a predictive model for critical illness will be as strong as for mortality risk. Moreover we want to build-up the predictive modelling skills in Swiss Re Hypothesis An updated & stronger Life model works together with our first ever Critical Illness model in order to enable the "pre-approved" process for both products Approach 1 Data Extraction 2 Predictive Modelling 3 Replicability Swiss Re Overview Insurer UW Data Analytics Propensity to be healthy Bancassurance Banking Data Pre-approved customers Swiss Re Big Data & Smart Analytics Centre Big Data im Gesundheitswesen 01 July 2014 9

Business Model Business value? Business processes? Ethics? Data Availability Adequacy Reliability Compliancy Risk Analytics Multitude of different skills IP Technology Tools Infrastructure Swiss Re Big Data & Smart Analytics Centre Big Data im Gesundheitswesen 01 July 2014 Picture Copyright: 10 thep urai/shutterstock everything possible/shutterstock

So how will data impact the insurance landscape? Swiss Re Big Data & Smart Analytics Centre Big Data im Gesundheitswesen 01 July 2014 11

The L&H insurance angle 1.7.2014 Big Data im Gesundheitswesen Séverine Rion Logean, SwissRe Life & Health R&D Europe

The digitized human being Eric J. Topol, Cell 2014 Swiss Re Big Data & Smart Analytics Centre Big Data im Gesundheitswesen 01 July 2014 13

Digital epidemiology Obesity trend on Twitter, 2013 Swiss Re Big Data & Smart Analytics Centre Big Data im Gesundheitswesen 01 July 2014 14

Data trading? Larry Page, CEO of Google on TED, March 2014 Swiss Re Big Data & Smart Analytics Centre Big Data im Gesundheitswesen 01 July 2014 15

Insurance: a pioneer in health data investigation and evaluation Swiss Re Big Data & Smart Analytics Centre Big Data im Gesundheitswesen 01 July 2014 16

Evidence based data for insurance Challenge: Contract at one point in time for +/-30 y No option for withdrawal form contract Individual data at pre-symptomatic status Importance of epidemiological data! e.g. Cardiovascular risk: Blood pressure Lipid level Medical diagnosis, treatment and prognosis Insurance conditions and premium Swiss Re Big Data & Smart Analytics Centre Big Data im Gesundheitswesen 01 July 2014 17

The obesity paradox Swiss Re Big Data & Smart Analytics Centre Big Data im Gesundheitswesen 01 July 2014 18

As more data is collected, with re/insurers often at the forefront of studies, coverage for those with HIV is being extended across the world Swiss Re Big Data & Smart Analytics Centre Big Data im Gesundheitswesen 01 July 2014 19

Learn from anonymised data pool http://spybusters.blogspot.ch/2012/01/pi-excuse-2012-i-lost-guy-in-crowd-2020.html Swiss Re Big Data & Smart Analytics Centre Big Data im Gesundheitswesen 01 July 2014 20

Learn from anonymised data pool Collection of prospective data (longitudinal observation of cohort over time) FAIR risk assessment (assess probability of a given event to happen) Collect data over a long period of time 'Average' population (no selection) Possibility of segmented informed consent for individuals Importance of data standardisation Also 'messy' data is of value Swiss Re Big Data & Smart Analytics Centre Big Data im Gesundheitswesen 01 July 2014 21

THANK YOU! Swiss Re Big Data & Smart Analytics Centre Big Data im Gesundheitswesen 01 July 2014 22

Appendix Big Data & Smart Analytics Jahresfachtagung 2014 in Wien 19 Juni 2014 23

Swiss Re takes data protection and privacy concerns very seriously by integrating Legal & Compliance checkpoints in our big data portfolio mgmt. process BD&SA Portfolio Management Process Collect Ideas Verify Ideas Opportunities Establish Pilots BD&SA Information and Analytics Requests Service Request Verify Information Information Exploitation Provide Solutions BD&SA Legal & Compliance Checkpoints A B C D Self-assessment Legal assessment Risk mitigation Compliance-by- Design Involvement Level of Legal & Compliance Swiss Re Big Data & Smart Analytics Centre Big Data im Gesundheitswesen 01 July 2014 24

BD&SA Casualty Treaty UW Pilot Context The Problem Hypothesis Limited information on covered risks in Liability Treaty (Traditionally, policy information is provided but little information about insured risks) We fully rely on client's risk assessment (To assess risk ourselves, need properties of insured companies the clients don't give) BD&SA methods can be key to help solving this problem (By closing the risk information gap) Approach 1 Data 2 Predictive 3 Gathering Modelling Scalability Insurer Submission Swiss Re Costing Overview Analytics External Data Swiss Re Big Data & Smart Analytics Centre Big Data im Gesundheitswesen 01 July 2014 25

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