Application Study of Intelligent Risk Assessment in Investment Management
DOI:
https://doi.org/10.54097/fcs5v248Keywords:
Intelligent risk assessment, Investment management, Deep learning, Multi-source data fusionAbstract
This study explores the application of intelligent risk assessment in investment management. By analysing the practical effects of machine learning, deep learning and other technologies in risk modelling, the results show that intelligent risk assessment significantly improves prediction accuracy and decision-making efficiency. The research data shows that the accuracy rate of the risk warning model based on the fusion of multi-source data reaches 87.3%, the annualised return of the investment portfolio is improved by 4.2%, and the maximum retraction is reduced by 25%. An intelligent risk control system covering multiple dimensions such as market, credit, and liquidity is constructed in practice, which provides practical risk management methodology support for financial institutions.
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