1. © 2014 Fair Isaac Corporation. Confidential. This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation’s express consent. Insurance Analytics Pathways for 2015 and Beyond Karen Pauli Research Director CEB TowerGroup Scott Horwitz Senior Director FICO

2. Agenda © 2014 Fair Isaac Corporation. Confidential. ► Welcome ► Business Drivers ► Analytics and Data ► Analytic Spend and Adoption ► Questions 2

3. © 2014 Fair Isaac Corporation. Confidential. Meet Karen Pauli, CEB TowerGroup Karen is a Research Director in the Insurance practice at TowerGroup. She covers a wide range of topics in property and casualty insurance, specializing in distribution, underwriting, claims, predictive analytics, core systems, and business optimization. 3

4. © 2014 Fair Isaac Corporation. Confidential. Insurers are looking for every advantage they can get to remain competitive and compliant, and analytics are a key part of their arsenal. 4

5. 5 © 2014 CEB. All Rights Reserved. ROADMAP FOR THE PRESENTATION Analytics Spend & Adoption Business DriversAnalytics and Data

6. 6 © 2014 CEB. All Rights Reserved. INSURANCE BUSINESS, STRATEGIC, AND TECHNOLOGY PRIORITIES Source: CEB Analysis Business Drivers Evolving individual sales and service expectations Changing distributor business models Contentious scope and authority of insurance regulators Global dependence on volatile regional economies Intensified competition for critical skill sets Strategic Responses Democratize the operationalization of the voice of the customer Build a holistic enterprise-wide data strategy Rationalize IT portfolio to align to agile sourcing strategy Define standards for favoring agility over precision Redefine traditional insurance roles and structures Top 10 Technology Initiatives for Insurance Life & Annuity and Property & Casualty Create a horizontal enterprise analytics and models layer Intermediate IT and business cloud utilization Facilitate real-time decisioning with collaboration technology Integrate consumer and distributor portals with back-end technology Leverage increasing variety of core system delivery options Create a device-agnostic mobile infrastructure Top Life & Annuity Technology Initiatives for Insurance Manufacture risk solutions with integrated actuarial systems Optimize the value of CRM across diverse distribution channels Top Property & Casualty Technology Initiatives for Insurance Integrate big data streams into day-to- day operations Expand telematics applications beyond personal auto

7. 7 © 2014 CEB. All Rights Reserved. INSURANCE BUSINESS, STRATEGIC, AND TECHNOLOGY PRIORITIES Business Drivers Evolving individual sales and service expectations Changing distributor business models Contentious scope and authority of insurance regulators Global dependence on volatile regional economies Intensified competition for critical skill sets Strategic Responses Source: CEB Analysis Top 10 Technology Initiatives for Insurance Life & Annuity and Property & Casualty Top Life & Annuity Technology Initiatives for Insurance Top Property & Casualty Technology Initiatives for Insurance

8. 8 © 2014 CEB. All Rights Reserved. EVOLVING INDIVIDUAL SALES AND SERVICE EXPECTATIONS Channel Preferences for Using or Accessing Financial Products and Services North American Consumers, 2010 and 2013 2010 n = 1,850; 2013 n = 2,713 Source: CEB 2011 and 2013 Customer Experience Surveys Consumers’ expectations for sales and service are changing, exemplified by a rapid change in channel preferences. -4% +8%

9. 9 © 2014 CEB. All Rights Reserved. CHANGING DISTRIBUTOR BUSINESS MODELS Agency Specialization Percentage of Survey Respondents Reporting an Increase in Specialization, by Revenue Group, 2010 and 2013 Source: IIABA’s 2013 Best Practices Study Distributor business models are shifting and show an increase in the specialization of independent agents and brokers.

10. 10 © 2014 CEB. All Rights Reserved. CONTENTIOUS SCOPE AND AUTHORITY OF INSURANCE REGULATORS Global Insurance Regulation Illustrative Example, Solvency Regulation Requirements, U.S. Impact Source: CEB Analysis Insurers feel the strain of conflicting regulatory bodies in the U.S. and internationally. State RMORSA Risk Management and Own Risk Solvency Assessment Model Act State law requiring insurers to implement an enterprise risk management framework by January 2015 International Solvency II Implementation date: 2016 Risk-based approach to capital requirements for insurers, three pillars: 1)Quantitative risk-based capital requirements; 2)System of governance; 3)Supervisory reporting and disclosure of information Federal FIO Modernization Report Released December 2013 Includes recommendations for: Material solvency oversight decisions of a discretionary nature Improved consistency of solvency oversight at the state level

11. 11 © 2014 CEB. All Rights Reserved. COMPETITION FOR CRITICAL SKILL SETS INTENSIFIES Q: How concerned are you about the availability of key skills as a business threat? Percentage of Respondents, 2011 and 2012 n = 1,330 Source: PwC 15 th and 16 th Annual Global CEO Surveys A global scarcity of skill sets drives competition amongst all global industries for talent, and significantly impacts insurers’ ability to attract and retain top talent.

12. 12 © 2014 CEB. All Rights Reserved. GLOBAL DEPENDENCE ON VOLATILE REGIONAL ECONOMIES Fluctuations Across Economies Percent Change in GDP over Corresponding Period of Previous Year, Advanced and Emerging & Developing Economies, 1998–2012 Source: Insurance Information Institute, Bloomberg, Aon Benfield Economic Interdependence US Impact of 2011 Thailand Floods, Illustrative International financial markets are now tightly interconnected, and, as economies fluctuate, insurers of all sizes with insured entities and supply chain dependencies spread across the globe face a significant risk management challenge. Thailand Floods, 2011 Total Insured Loss (USD millions): $15,315 Impact on US Business: Technology and Auto Manufacturers & Suppliers Hewlett Packard: 3.5%+ decline in 2011 revenue Ford: $80 million loss Source: IMF Decrease in Thailand manufacturing output due to factory closures Approximately 1,007 (billions THB) in economic losses in manufacturing

13. 13 © 2014 CEB. All Rights Reserved. ROADMAP FOR THE PRESENTATION Analytics Spend & Adoption Business Drivers Analytics and Data

14. 14 © 2014 CEB. All Rights Reserved. MORE INFORMATION, MORE INFORMATION WORK Estimated Rise in Global Data Volumes, 2010–2015 Indexed to 100 “Big data” is quickly becoming a reality as information volumes grow by 60% annually, and 36% of all work time is devoted to information collection and analysis. 36% Collecting and Analyzing Information 64% All Other Work 60% CAGR Time Spent Collecting and Analyzing Information Percentage of Total Knowledge Worker Work Time Drivers of Democratized Decision Making n = 4,941 knowledge workers. Source: “All Too Much” The Economist, 27 February 2010; CEB analysis. Source: CEB analysis. 3 2 1 Decisions are made closer to the market (e.g., product design, channel mix). Decisions are more dynamic and varied (e.g., demand forecasts, discounts). Knowledge workers have access to more information and better tools (e.g., customer segmentation and value analysis). 0 600 1,200 100 160 260 410 660 1,050 201020112012201320142015 Source: CEB analysis.

15. 15 © 2014 CEB. All Rights Reserved. BIGGER DATA, BIGGER NOISE As “big data” gets bigger, it becomes harder, not easier, for employees to extract truly valuable insight from it. Source: Taleb, Nassim, “Noise and Signal—Nassim Taleb,” Farham Street Blog, 29 May 2012, http://www.farhamstreetblog.com/2012/05/noise-and-signal-nassim-taleb/. Yearly Data Low High Daily Data Quarterly Data Hourly Data Minute- Wise Data DataBig Data Volume of Data/Frequency of Data Observations Signal to Noise Ratio

16. 16 © 2014 CEB. All Rights Reserved. REPORTING AND ANALYTICS MATURITY Only 7% of insurance executives report having a mature and optimized process in place for reporting and analytics. How would you assess your company’s maturity level in reporting and analytics? Percentage of Respondents, 2013 n=257 Source: CEB 2013-2014 FSI Technology Survey Reporting and Analytics: Reporting refers to the process of converting data into a normalized, structured, and actionable representation. Analytics refers to the systematic processing of data or statistics to produce insights supporting a business decision.

17. 17 © 2014 CEB. All Rights Reserved. IMPORTANCE OF ANALYTICS FUNCTIONS DOES NOT MATCH EXECUTION CONFIDENCE Over 50% of executives attribute high importance to all analytics functions, but their confidence in execution is low. Importance and Confidence in Execution Attributed to Analytics Functions Percentage of Respondents, 2013 Importance question: How important are each of the following analytics functions to your company’s operations? Confidence question: How much confidence do you have in your company’s ability to perform the following analytics functions? n = 257 Source: CEB 2013-2014 FSI Technology Survey

18. 18 © 2014 CEB. All Rights Reserved. CENTRALIZE MANAGEMENT, NOT INFORMATION Maximum Impact on Insight IQa of Centralized Models for Information Management Foundational analytic and information management activities benefit from centralization and create sufficiently strong oversight to sustain decentralized information sources. n = 4,941 knowledge workers. a: The maximum impact on Insight IQ is calculated by comparing two statistical estimates: the predicted impact when a knowledge worker scores relatively “high” on a driver and the predicted impact when a knowledge worker scores “low” on a driver. The effect of each driver is modeled using a variety of multivariate regressions with controls. Source: CEB 2011 Insight IQ Diagnostic. Centralized Analytics Team Centralized Knowledge Worker Training Centralized Information Quality Centralized User Support for Analytic Tools Centralized Information Architecture Single Unstructured Information Repository Single Data Warehouse Organizations with a high insight IQ centralize information management and support activities… …which enables them to keep the information itself decentralized. 0.0% 13.0% 0.0% 10.5% 10.4% 6.9% 6.7% 14.0% 7.0%

19. 19 © 2014 CEB. All Rights Reserved. CREATE A HORIZONTAL ENTERPRISE ANALYTICS AND MODELS LAYER Analytics Adoption and Replacement Siloed Approach, Prior Years As critical mass in analytics is reached, insurers need to abandon their siloed approach to analytics adoption and integration and aggregate analytics tools into a horizontal layer of analytics and models that are utilized enterprise-wide. Source: CEB Analysis Marketing and Product Development Analytics Tools Distribution and Sales Analytics Tools Policy Administration Analytics Tools Claims Processing Analytics Tools Infrastructure/Support Analytics Tools Marketing and Product Development Distribution and Sales Policy Administration Claims Processing Infrastructure/ Support Horizontal Enterprise Analytics and Models Layer Predictive Analytics Operational Analytics Consumer and Marketing Analytics Pricing Optimization Integrated Approach, 2014 Historically, insurers had a siloed approach to analytics adoption and integration In 2014, insurers need to create a horizontal layer of analytics and models tools that are utilized across the enterprise

20. 20 © 2014 CEB. All Rights Reserved. ROADMAP FOR THE PRESENTATION Analytics Spend & Adoption Business DriversAnalytics and Data

21. 21 © 2014 CEB. All Rights Reserved. SPENDING ON PREDICTIVE ANALYTICS Forty-three percent of insurance firms expect spending on predictive analytics technology to increase in the next 2 years. n=67 Source: CEB 2013-2014 FSI Technology Survey Expected IT Spend Change by 2015 Percentage of Respondents, 2013

22. 22 © 2014 CEB. All Rights Reserved. STATE OF TECHNOLOGY: PREDICTIVE ANALYTICS Forty-one percent of insurance firms intend to adopt or replace the technology before 2018. n=67 Source: CEB 2013-2014 FSI Technology Survey Current State of Technology Implementation by 2018 Percentage of Respondents, 2013 State of Technology Definitions Does not have it My company does NOT use technology in this area and DOES NOT intend to install the technology by 2018. Adopting Until recently, my company had no technology for this area, but HAS adopted the technology in the past 12 months or WILL by 2018. Have it, no change My company has technology in this area, DID NOT make a major system replacement in the past 12 months, and WILL NOT before 2018. Replacing My company has had technology in this area for over a year, and DID make a major replacement in the past 12 months or WILL make one by 2018.

23. 23 © 2014 CEB. All Rights Reserved. PREDICTIVE ANALYTICS VERY HIGH OR HIGH VALUE; COMPETITIVE ADVANTAGE Technology Value for Company Forty percent of insurance firms affirm that predictive analytics technology provides high or very high value to their company, which is primarily due to the innovative new insights these tools provide. Value Drivers n=67 Source: CEB 2013-2014 FSI Technology Survey

24. 24 © 2014 CEB. All Rights Reserved. PREDICTIVE ANALYTICS MODERATE RISK; INTEGRATION COMPLEXITY Technology Risk for Company Thirty-nine percent of insurance firms affirm that predictive analytics technology poses only moderate risk to their company. Risk Drivers n=67 Source: CEB 2013-2014 FSI Technology Survey

25. © 2014 Fair Isaac Corporation. Confidential. Questions 25

26. © 2014 Fair Isaac Corporation. Confidential. This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation’s express consent. Scott Horwitz scotthorwitz@fico.com Phone Thank You! 26

27. © 2014 Fair Isaac Corporation. Confidential. Learn More at FICO World Related Sessions ► Product Showcase: Multichannel Communication Solutions for insurance ► Putting the Brakes on Fraud, Waste and Abuse with SulAmerica Products in Solution Center ► FICO ® Identity Resolution Engine Experts at FICO World ► Scott Horwitz ► Nitin Basant White Papers Online ► FICO Gartner Newsletter: New Strategies for Fighting Insurance Fraud Blogs ► www.fico.com/blog 27

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