Bankaların Kredi Tahsilat Operasyonlarının Çok Amaçlı Optimizasyon Yöntemleri İle Optimize Edilmesi

Abstract

The banking sector is one of the most important sectors in modern economies. Acting as an intermediary in the transfer of funds between savers and investors, this sector is considered the key driver behind the higher growth rates of economies in the modern era compared to earlier periods. For this sector to function more effectively, it is vital for it to fully and timely collect its receivables. The receivables that banks fail to collect in a timely manner are known as Non-Performing Loans (NPL). Reducing the amount of NPL is a fundamental requirement for banks to sustain healthy operations. The key to reducing NPL lies in collecting them in a shorter period and at a higher rate. Banks are already employing various methods to increase their collections. While some of these methods involve quantitative analysis, the process largely relies on the experience of personnel working in this field. In this study, a numerical method is proposed for banks to enhance the collection of NPL. This method, consisting of two stages, utilizes path optimization techniques to create individual action paths for customers who are delayed in repaying their debts in the first stage. In the second stage, the process is optimized by solving an assignment problem to determine the action paths for all customers in the NPL Pool, consisting of customers who have delayed payments to the bank. Furthermore, our study provides a solution proposal for the dynamic version of the problem. Each stage of the proposed solution method is analyzed using datasets and computer programs. Consequently, a method and its implementation have been developed that banks can adapt to their own data sources and immediately utilize.