Modeling customer payment behavior and forecasting receivables : company case

Abstract

Nowadays it has become crucial for companies to closely monitor their working capital levels because of the critical role it has in business operations. Sales receivable are a key component of working capital and their estimation is equally important. In this thesis two statistical models are built, based on 3-years historical company data. One of the models is Kaplan-Meier, a customer-based model which models customer payment behavior and outputs the probability that the customer will pay the amount owed, if it has not paid until today. Modeling customer payment behavior enhances collections management on decision-making and it also assists sales department in making timely delivery stops. The second model is a SARIMAX model that predicts outstanding sales receivable amount at a certain date in the future. Reliable estimations of sales receivable from this model result in more accurate working capital estimation which in turn helps in determining the necessity for short-term external financing.