A large private-sector bank was expanding its digital personal loan business through multiple sourcing partners. While acquisition volumes grew, default rates began to rise. In the absence of a dedicated digital framework, the bank relied on a traditional personal loan scorecard that did not reflect the behavioral, data, and partner-specific realities of digital lending. Leadership needed a way to scale acquisition without importing disproportionate risk across heterogeneous partners.
Digital acquisition presents structural complexity. Data availability varies widely across partners, with some applicants offering rich bureau signals and others very limited histories. Early-stage risk must be assessed before approval decisions are made, without slowing digital journeys or over-rejecting creditworthy customers. The bank needed a decision framework that could adapt to these realities while remaining explainable and production-ready.
Dhurin designed a two-stage digital acquisition scorecard framework aligned to data context. Separate but calibrated scorecards were built for bureau-rich and bureau-light applicants, enabling consistent risk interpretation across partners. Target definitions were anchored using roll-rate and capture analysis to focus on meaningful default outcomes. The framework was embedded directly into digital approval workflows to support real-time, partner-aware decisioning.
Risk differentiation at acquisition improved, exposure to high-risk sourcing reduced, and approval confidence increased across partners. Marketing and risk teams gained clearer visibility into channel quality, allowing digital growth to continue with stronger portfolio discipline.
