Confidential. This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation's express consent. © 2011 Fair Isaac Corporation Canadian Insurance Outlook Analytic-Driven Solutions for Insurance Breakout Session: Claims Processing and Fraud Management January 14, 2011

© 2011 Fair Isaac Corporation. Confidential. 2 2 Agenda »Improving Claims Processing »Claim Processing Challenges »Applying Rules-Based and Analytic Capabilities »Sample Case Studies »Open Discussion

© 2011 Fair Isaac Corporation. Confidential. 3 Business Challenges Insurance Claims Processing »High operational costs »Balancing Effectiveness vs. Customer Satisfaction »Rapidly increasing cost of medical care putting pressure on premium and tax rates »Significant Fraud Losses »Lack of business agility to respond to market demands »Limited “expert resources” to handle complex or suspicious claims

© 2011 Fair Isaac Corporation. Confidential. 4 Use of Predictive Analytics And Business Rules »Collect only the relevant information to properly assess the claim at FNOL »Identify claim fraud early as early as possible, and continuously monitor claim for fraud »Leverage information collected during FNOL and other customer lifecycle interactions to determine claim treatment »Match case to claim and investigative professionals based on claim characteristics and skill sets »Auto-adjudicate acceptable claims with little to no human intervention Power Speed, Accuracy and Efficiency

© 2011 Fair Isaac Corporation. Confidential. 5 Traditional, Linear Claims Management Process Adjudication Claims Management Process Payment Process Reserving Claim-Level Fraud Detection FNOL Claims Validation Task Mgmt. FNOLAdjudication Payment Processing Blaze Advisor Claims Validation Analytics Claim-Level Fraud Detection Blaze Advisor Analytics Reserving Blaze Advisor Task Management Initial claim score Initial claim reserves Validate & Segment inbound claims Optimize treatment of claim based on: »Validation »Fraud Score »Reserves Analytics Claim-Level Fraud Detection Blaze Advisor Analytics Reserving Blaze Advisor Task Management Blaze Advisor Task Management Re-score claim Analytics Claim-Level Fraud Detection Re-score claim Update reserves Blaze Advisor Analytics Reserving Update reserves Optimize treatment of claim based on: »Validation »Fraud Score »Reserves Optimize treatment of claim based on: »Validation »Fraud Score »Reserves Move Key Claims Activities Forward to FNOL… …And Repeat These Activities Throughout the Process

© 2011 Fair Isaac Corporation. Confidential. 6 Business Rules and Analytics Leveraged Throughout Claims Management FNOLAdjudication Payment Processing Workers Compensation AutomobilePropertyLiabilityInland MarineLife & Health Product Rules Repository and Rule Flow Manager Centralized rules repository for storing and managing all rules needed by the process participants (claims adjusters, investigators, agents, etc.) Legacy Applications Service calls to back-end claims processing and payment processing systems Rule RepositoryPredictive Analytics Fraud Detection/ Reserving Regular and repeated scoring of claims to detect aberrant behavior and subtle fraud schemes. Claims Management Process

© 2011 Fair Isaac Corporation. Confidential. 7 Blaze Advisor Rule Service(s) How Blaze Advisor Works FNOL Core Application: Requires Decision Service(s) Rules, Strategies, Models e.g. “Flag or Audit: 3 rd Rear Collision Incident in 110 day window” e.g. “Process claim for policyholder J. Doe »FNOL Application Interfaces Automation challenges »Adjuster assignment? »Threshold for fraud? »Complaint management? »Reserve considerations? Analyst Rule Control Define Deploy Rule Repository Enabling Efficient Management of Claim Rules and Predictive Analytics

© 2011 Fair Isaac Corporation. Confidential. 8 Intelligent Data Collection and Claims Validation Description of Services »Business rules provide data validation review on all entered data at customer interaction point to preempt data entry error or invalid data values »Leverage business rules to generate dynamic / reflexive questioning for call center operations or customer facing websites (e.g. based on credit-based insurance score or point-of-sale score) »An automated capability allows segmentation and triage of inbound claims, thereby allowing categorization and prioritization based on multiple variables »FNOL decision service would pass collected data and invoke the prospective fraud scoring service Customer Claim Decision System Rule Repository FNOL Decision Service Adjudication Payment Processing FNOL BRMS Claims Validation Claims Management Process

© 2011 Fair Isaac Corporation. Confidential. 9 Fraud Detection Throughout the Claims Process Description of Services »Claims fraud scoring service will utilize predictive models tuned to a carriers book of business to score claims for the likelihood of fraud »Claims fraud scoring service will be invoked at FNOL and on a regular (weekly, etc.) basis as transaction/treatment data accumulates over the life of the claim »Link Analysis will validate a claim’s possible link to entities involved in previous fraudulent claims »Based on discrete scores rules will execute claims assignment, task creation, alerts, etc. Claim-Level Fraud Scoring Offline Modeling EnvironmentScoring Service Adjudication Payment Processing FNOL Analytics Claim-Level Fraud Detection Analytics Claim-Level Fraud Detection Analytics Claim-Level Fraud Detection Claims Management Process Claim Decision System Rule Repository Fraud Decision Service

© 2011 Fair Isaac Corporation. Confidential. 10 Claims Reserving—Closing the Gap Description of Services »Predictive analytic-driven assessments are performed automatically at the individual claim level »Estimated total claim value is provided along with easily interpretable reason codes »Business rules can then automatically segment claims and assign appropriate treatment strategy to the claims based on estimated claim value, reason codes or other criteria Adjudication Payment Processing FNOL Blaze Advisor Analytics Reserving Blaze Advisor Analytics Reserving Blaze Advisor Analytics Reserving Claims Management Process

© 2011 Fair Isaac Corporation. Confidential. 11 Optimal Claim Treatment Strategies Based on FNOL Data, Fraud Scores And Claim Cost Estimates Description of Services »Claim File exceptions can be placed in discrete queues alerting for unique actions »Referrals can be created to other business units (SIU, legal, agents, third parties, etc.) »Business rules can determine and route the claim to the appropriate adjuster or investigator based on unique attributes of the claim »Estimated Claim Value »Geographic Proximity »Adjuster/Investigator Skill Level »Reason Codes »Claims with acceptable fraud scores and estimated claim costs can be auto-adjudicated Adjudication Payment Processing FNOL BRMS Task Management BRMS Task Management BRMS Task Management Claims Management Process

© 2011 Fair Isaac Corporation. Confidential. 12 Simulate Business Impact of New Claim Strategies Create Candidate Rule-based or Code-based Services Blaze Advisor Rule Service(s) How Blaze Advisor Works Blaze Advisor Rule Service(s) Blaze Advisor Rule Service(s) How Blaze Advisor Works Code-based Service(s) Candidate Blaze Advisor Rule Service(s) How Blaze Advisor Works Blaze Advisor Rule Service(s) Code-based Service(s) Current/ Production Current/ Production Results Execute Simulation Comparison Report Generation Input Records Candidate Results

© 2011 Fair Isaac Corporation. Confidential. 13 Adjudication Payment Processing FNOL Analytics Claims Management Process Post Payment Processing Link Analysis Description of Services »Once a problematic claim has been identified, information extracted from that claim can be leveraged to find more fraud »Link Analysis techniques can be used to identify claims that are potentially fraudulent even though they have received a low fraud score »Analytics can score entities involved in multiple claims (such as healthcare providers) and rank order them on likelihood of fraudulent, wasteful or abusive practices Analytics Entity Profiling Find More Fraud Through Link Analysis

© 2011 Fair Isaac Corporation. Confidential. 14 Transforming Claim Processing Client: Aviva, the world’s 5th largest insurance group; the biggest in the UK, serving 50 million customers worldwide Challenge: Double the volume of business without increasing operational costs SolutionResults »FICO TM Blaze Advisor ® business rules management system »IT costs reduced by 20%, a game-changing cultural impact for the organization by empowering the business team »Reduced the number of calls from an average of 8 calls to 1 call to get the right data from customers to make a claims payment decision.

© 2011 Fair Isaac Corporation. Confidential. 15 Meaning Fraud Detection »Regional East Cost Plan »Savings were identified in 3 categories: »Claim-level savings from avoiding improper payments » Averaged $31.05 per claim line reviewed » Approximately $0.31 per claim line in savings across all lines (1% review rate) »Policy and plan issues identified » System/Policy: First year savings identified at $1,410,000 » Contracting: First year savings identify at $803,000 »Entity-level fraud and abuse investigations » Approximately $5.4m over 5 years

© 2011 Fair Isaac Corporation. Confidential. 16 Benefits of Early Fraud Detection First Investigation Old Prevented Activity Old Investigation and Claim Mgmt High Suspicion Level Low Time (weekly) Threshold First Identified First Investigation Old Prevented Activity Early Detection Benefit Old Investigation and Claim Mgmt High Suspicion Level Low Threshold Fraud Detected by FICO Analytics Time (weekly) CURRENT STATE Manual / Rule Based Fraud Detection FUTURE STATE Analytic Driven Fraud Detection

© 2011 Fair Isaac Corporation. Confidential. 17 In Summary... »Collect only the relevant information to properly assess the claim at FNOL »Identify claim fraud early as early as possible, and continuously monitor claim for fraud »Leverage information collected during FNOL and other customer lifecycle interactions to determine claim treatment »Match case to claim and investigative professionals based on claim characteristics and skill sets »Auto-adjudicate acceptable claims with little to no human intervention Leading carriers will leverage the power of business rules and predictive analytics to enable optimal claim performance

© 2011 Fair Isaac Corporation. Confidential. 18 © 2011 Fair Isaac Corporation. Confidential. 18 Open Discussion

© 2011 Fair Isaac Corporation. Confidential. 19 Discussion Topics »Mechanisms employed to improve Claims processing efficiencies »Moving claims activities forward at FNOL—what it means for your organization »Championing a fraud detection solution—your organization’s readiness

Confidential. This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation's express consent. © 2011 Fair Isaac Corporation. 20 THANK YOU January 12, 2011