Accident compensation schemes collect significant information on their claimants, on the services they are being provided and on the interactions between various parties long the way. Historically this information has been used in a limited way. With the assistance of new technologies, many of the restrictions imposed by traditional methods of data mining/data analytics can be overcome and new learnings on the factors impacting on claim outcomes can be obtained. This paper uses real examples to demonstrate how accident compensation analytics can be taken to the next level.
About the Authors
Aaron Cutter is a Principal of Finity and the leader of Finity’s Accident Compensation and CTP practices. He has particular expertise in accident compensation schemes and has provided advice to government insurers including WorkSafe Victoria, Transport Accident Commission, the ARPC (Federal terrorism risk insurer) and VMIA. Read more about Aaron here.
Katie Palin is a consultant at Finity who specialises in advanced statistical modelling and data mining techniques. She works across many areas including personal lines pricing, accident compensation, and customer insights. Prior to joining Finity, Katie held a number of positions within multinational banking corporations based in Sydney, Dubai and Singapore where she gained experience in credit risk modelling, portfolio segmentation, and customer analytics.Download presentation Download the paper