CIOP 2016 Symposium: Turning Digital Transformation into Innovation

1. Turning Digital Disruption into Innovation with Data & Analytics CIOP 2016 Insurance Industry Symposium Pat Saporito, Insurance Analytics Thought Leader & Sr. Dir., Global Analytics COE, SAP November 4, 2016 – New York

2. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 2Public Digital: The 4th Wave of Information Technology 1850 Industrial economy 2020 Digital economy 1990 Internet economy IT economy 1970 $0.36T $12.10T All figures are in Trillions; 1990 international dollars; Source: Department of Economics, UC Berkeley, BAIN 8 MacroTrends Brief. $27.50T © 2016 SAP SE or an SAP affiliate company. All rights reserved. $90.0T Gross world product

3. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 3Public Living in a Digital Economy Last 2 years Last 2 years End of 2020 End of 2020 In 2014 1 ScienceDaily, May 22, 2015 2 Technology Adoption Report on Business Networks, Ardent Partners 3 Internet of Things (IoT) 2013 to 2020 Market Forecast: Billions of Things, Trillions of Dollars, IDC 4 Statista 5 Cisco Global Cloud Index: Forecast and Methodology for 2013–2018, Cisco Systems Inc. 90% Of the world’s data has been generated1 40% Growth in adoption of business networks2 212 Billion “Things” will be connected3 9 Billion Mobile users in the world4 51% Of workloads processed in the cloud5

4. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 4Public SOMETHING INTERESTING IS HAPPENING. New Business Models Alibaba The most valuable retailer, has no inventory. 4 Uber The world’s largest taxi company, owns no vehicles. Airbnb The world’s largest accommodation provider, owns no real estate. Facebook The world’s most popular media owner, creates no content.

5. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 5Public Insurance Industry Disrupters Shaking It Up Trends  Peer to Peer Insurance  Usage Based Insurance  Spot Insurance  Contract/or Management  Aggregators/Quote Engines More InsurTech Sources: CB Insights InsureTech Blog TechCrunch Insurance The Digital Insurer © 2016 SAP SE or an SAP affiliate company. All rights reserved.

6. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 6Public The Analytics Native Analytics DNA • Began as an analytics company; morphed into an insurer • Acquired by Monsanto (seeds) for ~ $1 Bil. • Bayer (insectide) recently made a $62 Bil. Bid for Monsanto! 200+ data scientists analyzing 50 terabytes of weather data/day! The Climate Corporation aims to help farmers around the world protect and improve their farming operations with uniquely powerful software and insurance products. …proprietary technology platform combines hyper-local weather monitoring, agronomic data modeling, and high-resolution weather simulations to deliver climate.com, a solution that helps farmers improve their profits by making better informed operating and financing decisions, and Total Weather Insurance, an insurance offering that pays farmers automatically for bad weather that may impact their profits. Backed by Founders Fund, Khosla, Google Ventures, NEA, Index Ventures and Atomico. © 2016 SAP SE or an SAP affiliate company. All rights reserved.

7. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 7Public The Innovator Invest or Acquire to Innovate ! Insurers are using their venture capital funds to invest in innovation! © 2016 SAP SE or an SAP affiliate company. All rights reserved.

8. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 8Public Data & Analytics as a Core Competency “Analytics R Us”  Business model is based on behavior science.  Uses thousands of analytic models to classify and underwrite risk, adjust claims and help improve member’s health and wellness.  Customer life time value focused  Variety of customer engagement tools and incentives

11. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 11Public Insurance Analytics Evolution Where are you today? Where do you want to be? Pricing & Underwriting Traditional Class Rated Portfolio Analysis Household Analysis, Tier Rating Plans Risk Based Pricing, Ad-hoc or On Demand Rate Reviews Data Poor Quality, Silo’d, Inaccessible Data Data Assembled Across Product Lines/Historical Consistent Enterprise View Knowledge/ Data Mining Atomic Detail Data Wisdom/ Predictive Product Development One Product Fits All Unbundled Coverages Cafeteria/ Menu Approach Customer & Profitability Driven Marketing Product Value Customer Segment Value Customer Lifetime Value Dynamic Value Management Accounting & Finance Unit focused claims mgmt. Integrated, but reactive claims mgmt. Driver based historical claims mgmt. Driver based predictive claims mgmt. Metrics Silo’d, Functional, Lagging Metrics SBU-Strategic Objective linked, historical drivers Strategic & Cross-SBU objective linked, predictive drivers Integrated predictive models & metrics Claims Traditional Planning & Budgeting Driver Based Planning & Budgeting Integrated Planning Predictive Planning Less Advanced More Advanced

12. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 12Public Changing Times Process Yesterday Today Product Design One size fits all; high deductibles; standard policy term length Customized, connected; low deductibles; pay as you go Pricing & Underwriting Limited data; historical regression analysis Big data; advanced analytics enabled; real time Distribution In person, agents, call centers; basic online functions Online, mobile, social; online comparison Policy Administration/ Service, Claims Manual, on-premises administration/claims service Automated, cloud-based, real time

13. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 13Public Underwriting Scoring RiskFraud Claim Fraud Producer Fraud Anti Money Laundering Detection Risk Segmentation Risk & Compliance Customer Segmentation Customer Targeting and Acquisition Customer Service Customer Cross- Sell/Up-Sell Customer Lifetime Value Customer Acquisition Customer Management Marketing Applying advanced analytics in P&C/Life Insurance Producer Segmentation Producer Targeting and Acquisition Producer Service Producer Growth Producer Lifetime Value Producer Acquisition Producer Management Sales Catastrophe Modeling Are your models automated? Are they being applied? Are they embedded into your business processes?

15. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 15Public The Need is There… Ability to Execute is NOT Business Benefits:  Make better informed decisions  Improve business planning  Monitor process performance  Ensure compliance and reduce risk  Improve customer satisfaction IT Benefits:  Improve satisfaction levels from the business  Respond to business requests faster  Reduce manual report generation  Develop critical applications more quickly  Increase effectiveness of IT investments However, less than 30% of information workers use enterprise BI / analytics solutions! 54% of companies see the need for a high-performance analytics strategy to be implemented throughout their organizations…

16. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 16Public Business Intelligence Projects Fail (to meet Expectations) Technology is only One Consideration “Organizations tend to throw technology at BI problems. You can have the right tools, but could still be doomed to failure because of political and cultural issues, an absence of executive support and poor communication and training.” Between 70% to 80% of corporate business intelligence projects fail according to research analyst firm, Gartner.

17. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 17Public Enterprise Analytics: Strategy to Execution Execution Feedback to Strategy Strategy Link & Align Strategy to ExecutionBusiness Driven Strategically Aligned User Access & Usability Improved Decisioning Analytics Strategy & Roadmap Corporate Strategy New Data / Capabilities Real Time Analytics Operational Reporting Exploration & Visualization Predictive Analytics Ad Hoc Reporting Corporate Data Strategy & Metrics Performance Management Governance, Risk & Compliance Business Strategy Analytics Strategy Data Strategy

18. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 18Public SAP Data & Analytics Strategy Framework Objectives Business Needs Business Benefit Technology Organization Background and Purpose Current State and History Objectives and Scope Summary of Needs Envisioned To-Be State Priorities and Alignment Value Proposition of Analytics Expected Benefits – Future State KPI Business Case Information Categories Architecture and Standards Applications and Tools Governance Structure Program Management Roadmap and Milestones Measurement Education / Training Support • Digital must be part of your overall business-driven strategy • Operationalized by an Analytics Competency Center

19. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 19Public Digital Evolution or Revolution?  Changing Customer Expectations  Changing Risk Exposures  New Partners  New Competitors – including digital start ups  New Business Models

21. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 21Public Digital (R)EVOLUTION? Extend the addressable market and ecosystem New digitally enabled insurance products Today Tomorrow Core insurance business New non-insurance offers New digitally enabled premium services Core insurance business  Property & casualty insurance  Life insurance  Health insurance  Banking  Property & casualty insurance  Life insurance  Health insurance  Banking  Telematics (e.g., Pay as you drive (PAYD); Pay as you live (PAYL)  Simple Insurance  Context based offerings and next best offer  Smart Pricing  Retargeting  Infotainment  More advanced digital sales support for brokers and agents  Financial coaching; tire change; collection and delivery service; retirement planning; eCall, …  Ecosystem; partner offers (e.g., tires) Use case examples © 2016 SAP SE or an SAP affiliate company. All rights reserved.

23. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 23Public Digital core Omnichannel network The Internet of Things network Service and supplier network Workforce network Front office Middle office Back office Real Time Data Platform Property Life Health Real Time Data & Analytics – Engine for Digital Transformation! Digital Framework for Insurers Personalized experience Reduce FTE costs Engaged partners & suppliers Optimized risk management Operational AgilityDigital Orchestration Analytic Transparency

24. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 24Public Smarter Insurance Demonstration Sign In Customer: Bernd Clever • Age: 35 • Marital status: single • Profession: Management Consultant • Existing insurance: car, legal expenses, life, private health • Hobbies: skiing, tennis, golf, Formula One racing fan • Other characteristics: frequent traveler Smarter Insurance

25. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 25Public Smarter Insurance Demonstration Scenario 1: Auto Insurance - Tire Change It’s winter and in his state /province he has to install snow tires by a certain date.  The app reminds him to make an appt. to change his tires..  Smart Offers: It also offers him 4 auto related offers: • tire purchase options (with discounts!); • tire insurance quote; • winter safe driving class; • advance purchase tickets for Formula 1!  He can brag about scoring his Formula1 tickets via Facebook or other social media! How does this compare to how you interact with your customers today? Are you relevant? Smarter Insurance

26. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 26Public Smarter Insurance Architecture: No Touch, Real Time Hybrid – Cloud & On Premise Analytics CORE APPLICATIONS ECOMMERCE APPLICATION(S) PLATFORM C O N N E C T CONFIGURATION PORTAL C O N N E C T MARKETING PORTAL CRM Sales/Service New Bus Acquisition, Cross-Sell/Up-Sell, Renewals/ Winbacks Integration into existing (customer) portals CLOUD New analytics capabilities, build natively in the Cloud ON PREMISE Extend, leverage, scalable on-premise capabilities MARKETING SUBMIT/QUOTE POLICY BILLING CLAIMS REINSURANCE Customer Data App/Quote Data Policy/Coverage Data Premium/ Commission Data Claims data Reinsurance Data SALES Agent/Sales Data PARTNER DATA 3rd PARTY/ PUBLIC DATA

27. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 27Public Digital Transformation Roadmap Define a Digital Strategy • What does digital mean to your organization? Your customers? Your partners? • How does digital relate to your strategic plans/initiatives? • What are digital Opportunities? Risks? Conduct a Pilot • Conduct pilot with existing / new capabilities • Test capabilities needed to support pilot. • Conduct next pilot Review your Digital Capabilities & Culture • Data management • Analytics • Data bases/ platform • Business Processes • Skills & Behaviors • Agility

29. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 29Public Critical Success Factors  Executive Leadership  Business Driven Data Strategy  Organization Structure (People, Processes, Technology)  Data Driven Culture & Democratization  Analytics Sandbox/Innovation Center

30. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 30Public Next Steps • Business Intelligence/Analytics Strategy Assessment • Review your existing people, process and technologies overall and specifically for digital • Digital Transformation “Design Thinking” Workshop • Define and prioritize your digital opportunities • Digital Transformation Pilot • Apply digital capabilities for pilot

31. © 2016 SAP SE or an SAP affiliate company. All rights reserved. 31Public Thank you! Pat helps companies form, evolve and leverage a business-driven analytics strategy to improve business performance. Prior to SAP, she held business development roles at Teradata and META Group (now part of Gartner). Pat is a recognized insurance industry thought leader; she is a frequent contributor to Best Review Technology Insights column and has been on the faculty of the Int’l. Institute for Analytics, co-founded by Tom Davenport. She is the author of “Applied Insurance Analytics” and a contributor to “Analytics in Healthcare and the Life Sciences”, both published by Pearson/FT Press. Profile Available on Amazon Pearson /FT Press & other channels in print and/or digitally Download 1st chapter (industry overview) free Patricia Saporito Sr. Director, BI Global COE for Analytics SAP Labs, LLC New York, NY +1 (201) 681-9671 pat.saporito@sap.com Blog: www.patsaporito.com SAP Digitalist! Blog www.digitalistmag.com/ SAP Analytics Strategy Self Assessment Tool https://sap-bi-strategy-assessment.com/ Hasso Plattner Institute for Design Thinking at Stanford Univ. http://dschool.stanford.edu/ The Digital Insurer Forum www.the-digital-insurer.com/