New Publication on Optimal Credit Collections in Management Science

The research was conducted in collaboration with Prof. Weber’s former student, Prof. Naveed Chehrazi (UT Austin), and Prof. Peter Glynn (Stanford University). Using a repayment-process model from Chehrazi and Weber (Management Science, 2015) the new paper provides a complete solution to the problem of optimal dynamic account treatment. The authors show that optimal treatment tends to increase the asset quality of delinquent debt, in the sense that the expected return increases and the return uncertainty decreases.

Abstract

Based on a dynamic model of the stochastic repayment behavior exhibited by delinquent credit-card accounts in the form of a self-exciting point process, a bank can control the arrival intensity of repayments using costly account-treatment actions. A semi-analytic solution to the corresponding stochastic optimal control problem is obtained using a recursive approach. For a linear cost of treatment effort, the optimal policy in the two-dimensional (intensity, balance)-space is described by the frontier of a convex action region.