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Debt Recovery Process Optimization

Equipped with our solution, built on a behavioral model, our client - a leading debt collection company - improved the efficiency of its recovery process by 20%.

Modern debt collection methods are based on processes combining legal and arbitral measures. The efficacy of arbitral recovery is generally the determining factor impacting the success of companies operating in the debt collection industry.

The right selection of debt collection methods is a crucial element of the arbitral recovery process. The cost and efficiency of a method are two main criteria debt collectors consider when deciding on which procedures to implement.

Project Description & Client Benefits

Starting with a thorough investigation of our client’s existing procedures, we gained a better understanding of the nature of the problem and devised a non-standard approach utilizing a behavioral model, and then designed, developed and implemented a new solution.

The new system assesses the data and then determines the specific steps that the operator should take to maximize the chances of recovering debts within the set budget. After implementing the tool, we trained our client's team so that they could take full advantage of the new functionalities and work on its further improvement and development.

After implementing the new solution, our client saw an improvement in process efficiency by approximately 20%. This change increased their debt recovery rates, which translated into a significant reduction in operating costs and an increase in revenues.

Industry: FinTech

Project Category: AI, data analytics, software development

Lead Member: QuantUp

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