Department of Mathematics

Ford Motor Credit Company

Proposed Project for the MSU Industrial Math Students

Auto Loan Take Up Rate Model

Background: Price revenue management is increasingly being employed in the financial industry to set interest rates and terms for consumer loans. A successful revenue management program optimizes price (interest rate) by formally incorporating the behavioral response of consumers into the pricing decision. The goal is to establish the optimal trade-offs between volumes and return, while at the same time achieving company objectives for portfolio risk and composition. Accurate and robust volume response models are critical to portfolio optimization, but they present an ongoing challenge in practice as economic and competitive conditions can change rapidly in the marketplace. This analysis needs to be done in different marketplaces.


Phase I: Statistical analysis on the variables.

Phase II: Contract Level Demand Models and Evaluation: Build models to forecast purchase to approval rate. Purchase is standard retail purchase. The predictors include customer characteristics, contract characteristics, price (APR charged) and other variables. The models will predict the likelihood that an approved loan application will become a contract.

The goal in this phase is to build two logistic models segmented by tier, term and fico band: one uses the APR as one of the independent variables; the other uses the monthly payment as one of the independent variables. Evaluate the two models and find elasticity at each point. If time permits, other models can be explored as well.


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