Predictive Model for Risk Assessment in Share Market Using AI in Finance

In the ever-growing landscape of the share market, a more complex and flexible way of assessing risk is essential. Traditional risk assessment systems usually fail to capture the market's complicated dynamics, resulting in inefficient investment decisions. The inherent drawbacks of existing systems, such as their limited ability to evaluate large datasets and respond to changing market conditions, highlight the need for a more modern solution. The suggested system uses machine learning algorithms, deep learning techniques, and ensemble methods to maximize AI's potential. This lets a thorough look at historical data and critical economic indicators. The results of extensive testing and validation show a significant improvement in accuracy of 92.5%, precision of 91.8%, recall of 93.2%, F1 score of 92.5%, and overall reliability compared to existing systems. The model's adaptability and efficacy in detecting market risks represent an evolution in risk assessment, providing investors with a more educated and data-driven approach to navigating the complexity of the share market.