Credit risk management in financial services (original) (raw)

2021, Conference on Developments in Computer Science Budapest, Hungary, June 17-19, 2021

Since Risk management is the identification, evaluation and management of threats to the capital and income of an organization, threats or risks may come from a variety of sources, including financial insecurity, legal liabilities, policy errors, accidents and disasters. In digitised enterprises, IT security threats and data-related risks and risk management strategies have been made a top priority. As a result, the risk management plan increasingly includes companies' identification and monitoring processes, including proprietary corporate data, personal information and intellectual data, for threats to their digital assets, Including private corporate data, customer identity and intellectual property information. Each company and organisation, in the event of unforeseen, harmful events, can cost or cause the company to close permanently. Risk management is still a problem for most of the companies nowadays due to different reasons such as failure to use appropriate risk metrics, mismeasurement of known risks, failure to take known risks into account, and failure in monitoring and managing risks. During our research, we have used a hungarian well-known bank dataset which is OTP bank to analyse the customer specifically companies risks given different features of them. We have used different state-of-art or cutting edge models such as xgboost, catboost and Knn algorithms which are useful for future prediction of risk level associated with the companies. After cleaning the dataset and using the different classification algorithms, we came up with comparably good results which we measured with accuracy evaluation metrics.