Insurance companies often struggle with accurately predicting claims, resulting in financial uncertainty and inefficiencies in underwriting and claims management. To address these challenges, we developed a claim prediction model designed to enhance risk assessment, streamline underwriting processes, and improve claims management. This approach included aligning with business strategies and regulatory standards, defining key data parameters and segmentation criteria, and analyzing historical data to distinguish valid from fraudulent claims.
The solution also featured a robust scorecard based on characteristic analysis, supported by detailed data exploration, advanced data mining for improved accuracy, and continuous validation to ensure reliability. The model significantly enhanced the insurer’s ability to forecast claims, reducing financial risk, optimizing claims processing, improving underwriting efficiency, and increasing customer satisfaction.
