Risk Analytics Case Study

Business Problem – A Housing Finance Corporation (HFC) offering housing loans to un-served, unreached & under-served market wanted to reduce churn and tightly integrate analytics into its decision making and planning process.  While the HFC had a retention strategy for customers transferring their balances to their competitors, the institution had no solution for prepaying customers (pay-out of the loan in advance with customers own funds).

Approach – The HnC offshore analytics team built a machine learning model to predict the likelihood of a loan account fully prepaying prior to end of loan term.   A comprehensive model development document was produced that included details of the model objectives, data used, model methodology, model testing and planned model monitoring.  The HnC team also provided analytical support to the client in the live-implementation of the model.

Results

Significantly reduced churn of prepaying customers, increasing profitability and cost efficiencies.