Využití datové analytiky k výpočtu limitů pro úvěry klientů

This diploma thesis is focused on analysis of personal data belonging to the customers of banking institutions and on impact of such data on customer’s solvency. The first goal of this diploma thesis is to identify the crucial personal attributes that may have an impact on the resulting customer’s ability to pay back their loans. The second goal is to develop a simple web application which allows the user to manage their customers, and to calculate and predict the customers’ expected solvency. To achieve these goals, the author of this thesis had a personal meeting with a high ranked bank employee, who helped identify the most important personal attributes that impact the customer’s solvency. Subsequently, such attributes and their impact on customer’s solvency have been analysed and the resulting data have been used as the data basis for a full stack application developed within this thesis. Said application has been programmed using the latest and most frequently used frameworks, plugins and tools that make the development as easy, quick, robust, and effective as possible. One such framework, used for the development of said application, has been Spring boot. The original aim of this thesis was, however, to analyse methods used to calculate the loan limits of individual customers, and to propose possible improvements of these methods and calculations to further minimize the risk that the banking institutions would approve inadequate loans to possibly problematic customers. Unfortunately, the author of this thesis was unable to acquire the necessary data while writing this diploma thesis. The reasons that the data were not acquired, are mainly the General Data Protection Regulation (GDPR) and internal regulations of banks. As such, the aim of this thesis needed to be focused on individual personal attributes of a customer and their solvency.