Application of artificial intelligence in automated financial risk management systems

Abstract

The purpose of the research is to apply artificial intelligence in automated financial risk management systems in order to increase the accuracy, efficiency and effectiveness of management decision-making in the financial sector. As part of the research, a model for predicting the credit risk of bank customers has been developed, which allows assessing solvency based on historical data and modern machine learning methods. The object of the research is automated financial risk management systems operating in the banking and financial sector. The subject of the research is algorithms and models of artificial intelligence that can be integrated into automated financial risk management systems in order to increase the accuracy of forecasts and identify risky customers. The research method is modeling using machine learning tools, in particular neural networks and ensemble learning methods. The result of the research is the creation of an effective credit risk forecasting model that demonstrates a high level of classification accuracy and the ability to adapt to changing input conditions.