Using Business Analytics within the insurance claims process reducing the loss ratio by 2 to 5%

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1 make connections share ideas be inspired Using Business Analytics within the insurance claims process reducing the loss ratio by 2 to 5% David Hartley Director of Insurance Solutions, EMEA

2 Insurers under pressure Lower commissions Outsourcing Reduced workforce Lower cost distribution channels Streamlined processes

3 The Effect? Most insurers have chased down costs and expenses People Processes Technology Is there much left to chase? So effectively managing the claims process becomes even more important and visible within many insurers

4 Supporting the Claims process Claims leakage Additional costs incurred by the insurer beyond those necessary to fulfil its obligations under the insurance contract Fraud where the insurer shouldn t have paid the claim Failure to recover excesses/deductibles from policyholders Failure to recover amounts reclaimable from 3rd parties Unintentional overpayment of claim Excessive claims administration costs, inefficiencies etc. Failure to decline claims that are not covered Customer retention Complaints Renewal price sensitivity Historically insurers have built this cost into the final premiums charged to individuals or businesses but there is a competitive advantage in being able to reduce these costs

5 Using Business Analytics Complement existing processes (not replace) Using historical data to ensure that no opportunities to more effectively manage leakage are missed Can also significantly improve overall claims efficiency ensuring that Straight Through Processing can be applied to those claims which really warrant it Using existing data to predict the future outcome for an individual claim or claimant

6 Loss Reserving Claim Segmentation & Assignment Injury / Treatment Management Business Analytics Across the Claims Value Chain Notification Set-Up & Coverage Assignment Investigation Evaluation Negotiation / Disposition Medical Management Litigation Management Business Analytics Opportunities. Fraud Propensity Subrogation / Recovery Identification / Propensity to Recover Customer Attrition Propensity Workforce Productivity / Performance Attorney Representation / Litigation Propensity Process Adherence / Compliance

7 Industry Issue Claims Fraud Globally estimated that between 5 to 10% of all claims include some element of fraud Most insurers now a board level topic Keen to protect reputation but also to stop repeat and organised fraud rings

8 Claims Alerts

9 Detail Screens

10 Provider Network with suspicious claims

11 Claims Fraud - Why Business Analytics? More suspicious cases identified Including both previously undetected fraudulent networks and extensions to already identified fraud We discovered that 5% of its claims pay-outs were fraudulent, and these can now be corrected and prevented in the future." Assistant General Manager, Market Leader, Southern Europe Reduction in false positive rates Significant improvement in quality of suspicious cases past for investigation 84% of the claims flagged as possibly fraudulent, turned out to be fraud. A 69 % uplift in suspicious claim detection compared with the old system.." SIU Manager, Major Tier 1 USA Insurer Improved investigation efficiency Each referral taking 1/2 1/3 the time to investigate What used to take me most of a day, now takes 10 minutes. SIU Manager, Major Tier 1 USA Insurer

12 Industry Issue Claims Recoveries In many countries where there is the ability to recover claims costs from another insurer then ensuring that no opportunities to recover are missed is a significant issue Legal term is subrogation Figures on claims recovery leakage are hard to come by but global view suggests that it is in the order of 15+%

13 Frontal damage with low likelihood of recovery Rear shunts with high likelihood of recovery Rear shunts with 3 or more claimants

14 Claims Recoveries Case Study Major European P&C Insurer Well established Recoveries Process Deployed SAS analytics at FNOL Recoveries at FNOL increased from 23% to 27% across motor book Annual saving now in order of 13m CHF Analytics now an integrated part of their process

15 Industry Issue Large Bodily Injury Claims Significant issue in many European countries Growing issue BUT if such claims can be identified quickly then possible to offer early settlement significantly reducing total cost of claim

16 Large BI Claims Case Study Major European P&C Insurer Used 3 years of open/closed claims, payments and policy data Deployed SAS analytics both at FNOL Alert claims handlers with score and correct script in real time Annual saving estimated to be 23m CHF Analytics now an integrated part of their process

17 Industry Issue Customer Complaints Claims are the shop window of the insurance company Need to maintain reputation against holding claims leakage to minimum Understand likelihood of lapsing

18 Customer Complaints Case study

19 Customer Complaints Case Study Within 24 hours of FNOC we can predict with a 90% accuracy whether that customer will leave Allows for positive actions to prevent lapses in cases where the insurer wants to keep the client Estimates from one insurer suggest that annually this could be worth 10m CHF

20 Analytics can help reduce the loss ratio and expense ratio too Increase claims fraud detection 3-5% of claims payment saved? 23m CHF in claims avoidance? On-line application fraud detection Manage large BI claims 23m CHF reduction in claim size? 7m CHF in cost savings? Better call centre forecasting Increase Recoveries 13m CHF of additional recoveries? Manage complainants 10m CHF of lost premium saved?

21 make connections share ideas be inspired