- Identify practical applications of LLMs in credit risk workflows, including borrower analysis and credit report preparation.
- Understand how LLMs can assist in analysing financial and qualitative borrower information.
- Recognize how LLMs can support the preparation of credit risk reports and credit memos.
- Understand how prompting techniques can be used to obtain structured outputs from LLMs for credit analysis tasks.
- Recognize the benefits and efficiency gains from using LLMs in credit risk analysis.
- Design integrated workflows combining ML-based scoring models with
LLM-generated narrative reports for end-to-end credit risk analysis. - Provide practical examples illustrating the application of AI technologies
across the credit risk assessment lifecycle.