Michael Mark Finalist of the 2020 INFORMS Student Paper Competition
The paper “A Reinforcement-Learning Approach to Credit Collections,” co-authored by Michael Mark, a PhD Student at the Chair of Operations, Economics and Strategy, Prof. Naveed Chehrazi (Olin Business School, Washington University), and Prof. Thomas Weber, has been selected as a finalist of this year’s INFORMS Student Paper Competition in the Section on Finance. Michael is scheduled to present the paper at the upcoming INFORMS Annual Meeting, on November 9.
This paper develops a dynamic reinforcement-learning agent capable of finding high-quality policies for the practice of debt collections. At its core, the agent effectively learns how to control a stochastic self-exciting point process in order to maximize an asynchronously obtained reward. Because we use the general formulation of the problem as an agent-environment interaction our results are readily extensible beyond the presented application. Furthermore, with the growing need for interpretable machine-learning models we provide a policy regularization technique which makes learned policies intuitively understandable for human decision makers. Finally, our implementation features a novel “guided exploration" mechanism which improves the agent's performance in hard-to-reach states.