Overview
Leveraging Generative AI for Risk Assessment Course Overview
Leveraging Generative AI for Risk Assessment is designed to help finance professionals understand and apply AI-driven tools for modern risk management. The course covers credit, market, and macroeconomic risk assessments, offering practical case studies on how to simulate future scenarios and predict potential financial risks using AI.
Who Should Take This Course?
This course is ideal for finance professionals, risk managers, and data analysts looking to implement AI-driven risk assessment strategies in their organizations.AI Tool Requirement:
This course requires ChatGPT-4o and Claude for hands-on exercises. Free users have limited access, while the paid accounts offer higher usage limits. For enterprise security, use ChatGPT Team, Enterprise, or Azure OpenAI Service.
Leveraging Generative AI for Risk Assessment Learning Objectives
- Understand how generative AI enhances traditional risk assessment methods
- Implement AI-driven models for credit, market, and macroeconomic risk predictions
- Use generative AI to perform scenario analysis and risk forecasting
- Apply AI tools to automate and improve decision-making processes in finance
Prerequisite Courses
Recommended courses to complete before taking this course.
Leveraging Generative AI for Risk Assessment
Led by
Glenn Hopper
Level 3
2h 13min
100% online and self-paced
Field of Study: Finance
Start LearningWhat You'll Learn
Lesson
Multimedia
Exams
Files
Case Study 1: Predicting Borrower Risk Using Generative AI
Predicting Borrower Risk with AI Models
Using Generative AI to Create Synthetic Loan Data
Uploading and Reviewing Synthetic Data with Generative AI
Data Preparation and Exploration
Evaluating Model Accuracy and Predictive Performance
Analyzing Feature Importance for Predicting Loan Default
Insights and Discussion
Testing Model Scenarios and Conclusion
Interactive Exercise: Generative AI for Credit Risk Assessment (For Banks)
Glossary of Key Terms
Case Study 2: AI-Driven Market Risk Assessment Using VaR and CVaR Calculations
Introduction to VaR, CVaR, and VIX for Market Risk
Preparing S&P 500 and VIX Data for Analysis
Setting Parameters and Running Simulations
Calculating VaR and CVaR for Portfolio Risk Assessment
Stress Testing and Validating the Risk Model
Comparing Model Projections with Actual Market Performance
Comparing AI-Driven and Traditional Risk Metrics for Portfolio Management
Interactive Exercise: Generative AI for Market Risk Assessment
Glossary of Key Terms
Case Study 3: Leveraging Generative AI for Macroeconomic Risk Assessment
Introduction to AI-Driven Macroeconomic Risk Assessment
Accessing and Downloading Macroeconomic Data from FRED
Consolidating and Preprocessing Macroeconomic Data for Analysis
Building a Logistic Regression Model for Recession Prediction
Developing and Testing the Recession Prediction Model
Running Economic Scenarios to Test Recession Predictions
Analyzing Model Sensitivity and Implications for Economic Policy
Summary and Next Steps for Enhancing Economic Risk Models
Interactive Exercise: Generative AI for Macroeconomic Risk Assessment
Glossary of Key Terms
Case Study 4: Building an Economic Dashboard in Claude
Conclusion
Qualified Assessment
This Course is Part of the Following Programs
Why stop here? Expand your skills and show your expertise with the professional certifications, specializations, and CPE credits you’re already on your way to earning.
Risk Management Specialization
- Skills You’ll Gain Risk Identification, Regulatory Analysis, Risk Measurement, Risk Mitigation
- Great For: Market Risk Analyst, Credit Risk Analyst, Compliance Officer, consulting, Enterprise Risk Manager, Audit
AI for Finance Specialization
- Skills You’ll Gain AI-Driven Financial Analysis, Excel Automation, and Applied AI Skills
- Great For Financial Analyst, FP&A Analyst, Business Intelligence Analyst, Investment Bankers, Equity Research and more
What Our Members Say
Generative AI
Assessment questions are too simple and too few. The answers are very obvious in the given Multiple choice. Exam rigour should be improved to give credibility to the certificate of such wonderful course. No. of assessment questions should be at least 25. Choice should be tricky and time limit to be imposed for answering. venugopal rajamanuri
Great experience
Very insightful course Pablo Rodriguez Guaba
The course was very interesting and provided full geat knowlege!
Muhammad Zubair
Excellent Course
This course provides excellent case studies that applies AI in producing predictive models for macroeconomic research and portfolio management. For example, the application of monte carlo simulations, the calculation of VaR & CVaR, alongside the use of confusion matrices in predictive applications. Kar Yiu Joshua Tse
Frequently Asked Questions
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