Kaustubh 'AI In Risk Management'MBA.pptx

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1. “Artificial Intelligence In Risk Management” By : Kaustubh Mani Tripathi BBA+MBA 5YR. (IPM) Enrollment no : U2333033

2. Outline Introduction Overview of AI application Limitation of traditional risk management Benefit of integrating AI in risk management AI-Powered Risk Monitoring and Prediction Ethical Considerations in AI-Powered Risk Management Case Study The Future of AI in Risk Management Conclusion Questions Thank you

3. Introduction to Artificial Intelligence in Risk Management Explore the transformative potential of AI to enhance risk management practices and unlock new opportunities for organizations. 09/08/2024 Kaustubh Mani Tripathi (2 nd Semester) 1

4. Overview of AI Applications in Risk Management Predictive Analytics Forecast risks and identify emerging trends using AI models. Anomaly Detection Rapidly identify unusual patterns that could signal fraud or threats . Automated Monitoring Continuously monitor risk indicators and alert on potential issues. Regulatory Compliance Automate compliance checks and reporting to reduce human erro r. 09/08/2024 Kaustubh Mani Tripathi (2 nd Semester) 2

5. Limitations of Traditional Risk Management Manual Processes Traditional risk management relies heavily on manual data collection which is time-consuming and prone to human error . Outdated Systems Risk management systems often lack the flexibility capabilities needed to keep pace with the rapidly evolving risk landscape . Siloed Approach Fragmented risk management practices across different departments can lead to a lack of holistic risk visibility and coordination. 09/08/2024 Kaustubh Mani Tripathi (2 nd Semester) 3

6. Benefits of Integrating AI in Risk Management Enhances Predictive Capabilities - AI identifies emerging risks and trends for proactive mitigation. Improves Efficiency and Productivity - Automates repetitive risk tasks, freeing up resources for strategic initiatives. Enables Real-Time Risk Visibility - AI-driven systems provide instant insights for faster decision-making. 09/08/2024 Kaustubh Mani Tripathi (2 nd Semester) 4

7. AI-Powered Risk Monitoring and Prediction 1 Real-Time Risk Monitoring AI algorithms detect anomalies and emerging threats in real-time. 2 Predictive Analytics Machine learning models forecast potential risks and recommend preemptive strategies. 3 Automated Reporting AI-powered dashboards generate comprehensive risk reports for streamlined decision-making . 09/08/2024 Kaustubh Mani Tripathi (2 nd Semester) 5

8. Ethical Considerations in AI-Powered Risk Management 1 Algorithmic Bias Ensuring AI models do not reflect human biases in risk assessment. 2 Data Privacy and Security Protecting sensitive customer and financial data used by AI systems. 09/08/2024 Kaustubh Mani Tripathi (2 nd Semester) 6

9. Ethical Considerations in AI-Powered Risk Management 3 Transparency and Explainability Enabling stakeholders to understand the logic behind AI-driven risk decisions. 4 Responsible AI Governance Establishing ethical frameworks and oversight for deploying AI in risk management. 09/08/2024 Kaustubh Mani Tripathi (2 nd Semester) 7

10. Data-Driven Decision Making: A Case Study 1 Data Collection Comprehensive data collection from diverse sources. Data Analysis Uncovering hidden insights with advanced analytics and machine learning. Informed Decisions Making strategic decisions based on data-driven insights. 3 2 09/08/2024 Kaustubh Mani Tripathi (2 nd Semester) 8

11. The Future of AI in Risk Management . Predictive Analytics Advanced AI models for forecasting risks 1 2 Autonomous monitoring Self - learning system for real – time risk detection. 3 Prescriptive strategies AI – drives recommendation for optimal risk mitigation. 09/08/2024 Kaustubh Mani Tripathi (2 nd Semester) 9

12. Conclusion Artificial intelligence plays a crucial role in enhancing risk management practices. Organizations leveraging AI technologies gain a competitive edge in identifying and mitigating risks. Continuous innovation and integration of AI in risk management are essential for future success. 09/08/2024 Kaustubh Mani Tripathi (2 nd Semester) 10

13. Any Questions ? 09/08/2024 Kaustubh Mani Tripathi (2 nd Semester) 11

14. Thank You . Thank You for your Time and Attention!! 09/08/2024 Kaustubh Mani Tripathi (2 nd Semester) 12