The Indian finance arm of a global automaker relied on a long-running acquisition scorecard across new, used, and commercial auto loans. Over time, customer mix, product exposure, and portfolio behavior evolved materially. While the scorecard remained operational, leadership needed independent assurance that it was still separating risk reliably under current conditions.
The challenge was not whether the model had worked historically, but whether it could be trusted now. The institution needed clarity on where the scorecard continued to discriminate effectively, where performance had weakened, and how safely it could support automated acquisition decisions without introducing unintended risk.
Dhurin conducted an independent quantitative validation focused on decision relevance rather than statistical exhaustiveness. Model stability, discrimination, calibration, and segment-wise behavior were assessed by comparing predicted risk with realized outcomes over time. Performance was reviewed across products and customer segments to identify drift, sensitivity, and areas requiring constraint or recalibration. Findings were translated into practical guidance on score usage, decision boundaries, and recalibration priorities.
The validation restored confidence in the scorecard’s continued use, defined safe limits for automated decisioning, and identified segments requiring adjustment. The institution gained an audit-ready basis for ongoing governance, allowing the model to remain productive without overstating its reliability.
