By using predictive analytics for insurance fraud detection, a leading insurance company reduces P&C claims fraud by 23%. The client experienced major revenue losses due to the highly evolved fraudulent claims. The business entities urgently needed a more intelligent data analytics solution that could raise red flags and identify fraud practices and claims.

The client aimed at implementing predictive analytics for insurance to:

• Detect fraudulent claims and reduce revenue loss
• Analyze extensive real-time data, raise red flags, and identify fraudulent claim bills

The predictive data analytics solution designed by Payoda could sift through huge volumes of real-time data, identify false bills, raise appropriate red flags, perform data analytics and generate visualization reports. This helped the client reduce P&C claims fraud by 23% and enabled a cost saving of 12.38%.