Case Study on Risk Discrimination Gains with EXL

This case study details how a Fortune 500 financial institution addressed the challenge of extracting insights from unstructured transaction data by implementing EXL Transaction Insights. The primary objective was to transform raw data into actionable intelligence to enhance the creditworthiness model. The solution enabled the categorization of over 90% of transactions into more than 300 categories, providing insights into customer spending habits. Additionally, the creation of over 2,000 predictive variables allowed for a nuanced risk assessment of applicants. The collaboration with EXL led to the development of a sophisticated credit default model, improving underwriting procedures. The outcomes included systematic approvals for applicants with strong financial profiles and declines for those exhibiting financial distress. Overall, the implementation of EXL Transaction Insights resulted in a 15% improvement in risk discrimination, leading to a more efficient underwriting process and better portfolio performance.