Decision Optimisation: How to use your data and analytics to optimize debt restructures and collection treatment strategies
On the back of the COVID-19 pandemic, many organizations face increasing volumes of debt in arrears, and a higher share of financially stressed customers. In early collections, this requires stronger segmentation, focus of manual activities on relevant customers and a higher degree of automation when treating medium and low risk customers. Customers in financial stress require payment plan changes that balance affordability with risk considerations, and most importantly, are sustainable and do not break after a couple of instalments.
Decision Optimisation provides a strong method to analytically determine the optimal collection treatment for each customer, under given constraints such as operational capacity, budget and performance targets. In this session, we demonstrate how decision optimization allows to develop
an optimal treatment strategy for early collections, minimizing end of month balances under capacity constraints
an optimal restructure strategy for customers in financial hardship, considering policy constraints and balancing alternative financial
goals
We’ll show how Decision Optimization allows to understand tradeoffs between competing goals, such as operational costs and portfolio performance, and to simulate the impact of constraints, such as changes to capacity or policy rules.