- Define key AI and ML concepts and explain their relevance to credit risk assessment for personal and corporate loans.
- Describe the regulatory requirements of the EU AI Act as they apply to high-risk AI systems in credit risk.
- Identify the main ML algorithms and models used for credit scoring, default prediction, and risk pricing.
- Apply practical LLM prompting techniques, including structured outputs and problem segmentation, to credit risk tasks.
- Demonstrate how LLMs can automate credit risk report writing, including borrower descriptions, industry analysis, and financial statement commentary.
- Evaluate the explainability, transparency, and governance requirements for AI models used in credit decisions.
- Design integrated workflows combining ML-based scoring models with LLM-generated narrative reports for end-to-end credit risk analysis.
Machine Learning Models for Credit Risk Assessment
