Simulation of Expected Loss Model of Financial Assets Impairment Based on Data Mining Algorithm
Ziqi Liu · 2023
In the face of increasingly complex financial market and risk environment, financial institutions need to accurately evaluate the expected loss of asset impairment in order to formulate effective risk management strategies. The traditional statistical model has some limitations in dealing with large-scale financial data and complex correlation, so this study adopts data mining algorithm to construct the expected loss model. In this study, firstly, the basic principles and common methods of data mining algorithms are introduced, including Apriori algorithm and improved Apriori algorithm. Then, an expected loss model of financial assets impairment based on data mining algorithm is proposed, and the simulation experiment is carried out using actual financial data. The experimental results show that the improved Apriori algorithm has obvious advantages in computing time and can process large-scale financial data more efficiently. Compared with the actual data, our model can accurately predict the expected impairment loss of financial assets, and shows good stability and robustness in different market environments.