Objectives to cover:

• Introduction – Overview of AI-driven risk management in financial institutions.
• Evolution of AI in Risk Management – Advancements in AI technologies transforming risk assessment.
• AI Applications in Risk Management – Key use cases like fraud detection, credit risk, and market forecasting.
• Enhancing Predictive Analytics – Leveraging AI for accurate risk prediction and mitigation strategies.
• AI in Decision-Making – Improving financial decision-making through automation and data-driven insights.
• Regulatory Compliance and AI – Using AI for stress testing, scenario analysis, and regulatory adherence.
• Challenges and Ethical Considerations – Addressing bias, cybersecurity, and ethical concerns in AI models.
• Future Trends in AI Risk Management – Emerging innovations like quantum computing and explainable AI.
• Conclusion – The growing role of AI in shaping the future of financial risk management

Reference:  Harvard style