THE PROBLEM

Global accounts receivable management company wanted to optimize the collection of overdue balance from loyalty program members.

Around 25000 customers accrue a cumulative debt between 40-45 million USD in overdue payments every year.

The retailer’s receivables management partner wanted to adopt a data driven debtor contact strategy to increase collections without additional manpower costs.

THE SOLUTION

A proprietary self-learning, multi-modeling automatic predictive technology from FIndability.AI was used to assign a ‘Propensity to Pay’ score to each record in the debt portfolio.

The debt portfolio was divided into 7 ‘age buckets’ defined by the debt collection partner.

Follow-up strategy for collections was formulated based on ‘age’ of debt and payment propensity score.

THE SUCCESS

An overall increase of 11% was observed in retailer’s debt collection during the measurement period.

Collection partner’s fee revenue increased by 15%

There was additional manpower costs involved.