An Empirical Investigation of Artificial Intelligence Instruments for Forecasting Credit Risk in the Digital Age - Kim, Deageon; Lee, Dongoun (International Journal of Intelligent Systems and Applications in Engineering, 2023)
Credit risk is the danger that a bank’s debtors will not fulfil their obligations by skipping payments on their credit cards or loans. Credit risk is the most important and difficult issue confronting bank management. The objective of this study is to examine the potential of artificial intelligence (AI) instruments for forecasting credit risk in the digital age. This research will use an empirical approach to answer the research questions through the collection of data, analysis, and interpretation of the results. This research will be conducted using an empirical investigation to understand the use of artificial intelligence instruments for forecasting credit risk in the digital age. The research process will involve three main steps, including data collection, data analysis, and results interpretation. AI-based instruments can quickly process large amounts of data from multiple sources and accurately identify potential credit risk. Furthermore, these instruments can also be used to identify customer behaviour patterns and inform more accurate decision-making.