To hold onto market share and achieve their growth goals, many process millions of quotes every day via aggregators and their own websites. The cloak of anonymity provided by the internet and this high volume business model have been a gift to fraudsters. Delivering results in sub-seconds, Radar can be configured to reflect an insurer’s risk tolerances and can be applied to any line of insurance business. The high volume fraud screening tool draws on the widest range of external data sources, enriching the insurer’s internal data in order to verify the applicant’s identity, confirm prior claims history and validate the information they provide about themselves and their vehicle or property.
Data sources applied as standard include household, motor and personal injury claims, identity verification, linked addresses, vehicle verification, and property attributes providing a comprehensive holistic view and insurers can flex the solution to specify the incorporation of additional data sets.
CRIF will analyse how an insurer uses data in the underwriting process before applying sophisticated predictive indicators to tailor the outputs from Radar, which are automatically integrated in the insurer’s underwriting engine. Incorporating machine learning, these predictive indicators can evolve and adapt to reflect the behaviours of fraudsters and dynamically block them.
Insurers can specify the level of data detail they require from the solution and have the option of using the service real time at point of quote or by batch file transfer for post-sale validation. Available via web services, RADAR requires minimal investment by insurers in their technology infrastructure. Sara Costantini, Director at CRIF Decision Solutions said: “Latest statistics from the ABI record only 212,000 cases of detected application fraud in 2014 and this is widely acknowledged as only the ‘tip of the iceberg’.
In its interim report, in March this year, the Government’s Insurance Fraud Task Force tasked the ABI and BIBA with updating industry guidance on application fraud. “Improving the screening of risks is very clearly on the industry’s agenda and so we talked to our insurer customers to understand their challenges and needs. Based on their feedback we have developed a high performance, volume screening tool which can be configured to the risk tolerances, underwriting rules, data sets and level of detail an individual insurer requires. The inherent flexibility and machine learning capability delivers a solution which can evolve with an insurer’s business and counter fraud strategies.
We are very excited by the intrinsic application fraud detection prospects for our insurer customers and the subsequent operational savings that will be delivered.”
