Providing software solutions since 1976
Providing software solutions since 1976
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'IT to help non-life cos cut fraud, improve claims
ratio'
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March 29, 2004
Non-life insurers, plagued with high losses under motor and health insurance, can improve their claims ratio by using information technology. In developed markets, customer intelligence solutions have helped insurers to predict claims, detect frauds and tighten up their under writing practices. In the US , AAA Mid-Atlantic, which provides auto insurance, was able to cut its claims frequency by 20%. It put together a grading model that predicted risk for potential customers, thereby matching appropriate price to each segment. Again, the US defence department has used data mining to uncover double-billing fraud, amounting to millions of dollars under the Civilian Health & Medical Program of the Uniformed Services. In India , the health and motor businesses are the fastest growing. These also happen to be segments with the highest losses. Claims ratios have been inching towards the 100% mark. The high claims may be partly attributed to the high level of soft frauds and inflated bills. Steve Wylie, principal, financial services group SAS Institute, told ET that claims prediction is the number one topic of interest among insurers. Particularly, in the case of motor insurance, where the incidence of fraud was around 20%. In India , the key issue that insurers face is how to increase marketshare and remain profitable. In the non-life sector, the concerns about profitability are higher because of imminent detariffing. This could trigger off a rate-war as companies scramble to build up marketshare. Insurance companies are data-rich but information-poor,” Mr Wylie said. “Using insurance intelligence solutions, they could take this data and use it as a platform for intelligent solutions.” For instance, if an insurance company receives a $1000 claim for damage to a car’s bumper, the system would immediately pop-up warning flags. This would enable the company to immediately act upon the claim by sending an investigative team. Mr Wylie adds that the solution works on the 80:20 principle which means that 80 of the solution is based on pre-built set of models that are used internationally while there is 20% adaptation for the local market. The customer intelligence software involves predictive models that is often used in sales. For instance, it would inform a retailer that a customer who purchases a greeting card is very likely to buy chocolates based on past data. The technology is also used by insurers for determining life time value of a customer and helps them target the right customer. |
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