The client needed to validate its existing fraud practices for better detection of claims fraud and create a holistic risk profile framework for proactive detection of potentially fraudulent claims.

Solytics developed a comprehensive risk profile model by:

1. Data sampling, data cleansing, and data analysis to unearth hidden transaction patterns.

2. Aggregating static, transaction, and link scores to assess impact of changes in fundamental attributes like transaction volume on risk score

3. Calculating risk score changes and applying tolerance limits for risk classification.

- Improved ability to identify fraud profiles.

- Provided new performance metrics to evaluate the risk profile model.

- Offered analytical insights for future model use.