Exercise 1: Model Validation Planning Prompt Engineering

Objective:

Learn to craft effective prompts for developing comprehensive model validation plans.

Background:

Model Validators are responsible for planning and executing independent validations of financial models. A key challenge is developing thorough validation plans that address all relevant risks and regulatory expectations.

Exercise:

1. Scenario:

You need to develop a validation plan for a new credit scoring model that uses machine learning techniques to assess consumer loan applications.

2. Basic Prompt Example:

How should I validate a credit scoring model?

3. Prompt Improvement Activity:

  • Identify the limitations of the basic prompt
  • Add specific details about the credit scoring model
  • Include context about regulatory expectations
  • Request a structured validation plan with specific testing approaches
  • Ask for documentation requirements and validation scope

4. Advanced Prompt Template:

I am a Model Validator at a [size] financial institution developing a comprehensive validation plan for a new credit scoring model with these characteristics:

Model details:
- Purpose: Consumer loan application risk assessment
- Methodology: [specific ML algorithm, e.g., gradient boosting, random forest]
- Input data: [application data, credit bureau data, transaction history, etc.]
- Output: Credit score (0-1000) and approval recommendation
- Model developer: [internal team or vendor]
- Implementation status: [development complete, pre-implementation]
- Model risk rating: High (due to materiality and complexity)

Regulatory context:
- Applicable guidance: [SR 11-7, OCC 2011-12, etc.]
- Recent examination findings: [any relevant regulatory feedback]
- Internal model risk management framework requirements
- Peer validation practices for similar models
- Emerging regulatory expectations for ML models

Please help me develop a comprehensive model validation plan by:

1. Outlining a structured validation approach that includes:
   - Validation scope and objectives
   - Independence considerations
   - Required expertise and resources
   - Validation timeline and milestones
   - Documentation requirements
   - Stakeholder communication plan

2. Recommending specific validation activities for:
   - Conceptual soundness assessment
   - Process verification and implementation testing
   - Outcomes analysis and benchmarking
   - Ongoing monitoring requirements
   - Developmental evidence review
   - Data quality and data processing validation

3. For each validation activity, provide:
   - Detailed testing procedures
   - Sample size considerations
   - Statistical techniques to employ
   - Common issues to look for
   - Documentation requirements
   - Acceptance criteria

4. Addressing specific ML model considerations:
   - Feature importance and selection validation
   - Model explainability assessment
   - Bias and fairness testing
   - Model stability and robustness evaluation
   - Hyperparameter optimization review
   - Model complexity and overfitting assessment

5. Recommending approaches for:
   - Findings classification and severity assessment
   - Issue remediation tracking
   - Validation report structure and content
   - Model approval conditions
   - Ongoing monitoring requirements
   - Periodic revalidation planning

Format your response as a structured model validation plan that I can use to conduct a thorough validation of our credit scoring model while meeting regulatory expectations.

5. Evaluation Criteria:

  • Does the prompt clearly describe the credit scoring model and its characteristics?
  • Does it provide context about regulatory expectations?
  • Does it request specific validation activities across all key areas?
  • Does it address ML-specific validation considerations?
  • Does it ask for findings classification and reporting approaches?

6. Practice Activity:

Create your own advanced prompt for model validation planning related to:

  1. A CECL (Current Expected Credit Loss) model
  2. An anti-money laundering transaction monitoring model
  3. A market risk VaR (Value at Risk) model

Exercise 2: Model Testing Prompt Engineering

Objective:

Develop skills to craft prompts that help design effective model testing procedures and analyses.

Background:

Model Validators must design and execute testing procedures to assess model performance and limitations. A key challenge is developing comprehensive testing approaches that identify potential model weaknesses.

Exercise:

1. Scenario:

You need to design testing procedures for validating a new IFRS 9 / CECL expected credit loss model for a commercial loan portfolio.

2. Basic Prompt Example:

What tests should I run on a CECL model?

3. Prompt Improvement Activity:

  • Identify the limitations of the basic prompt
  • Add specific details about the CECL model
  • Include context about portfolio characteristics
  • Request structured testing procedures across model components
  • Ask for statistical techniques and acceptance criteria

4. Advanced Prompt Template:

I am a Model Validator at a [size] financial institution designing comprehensive testing procedures for validating a new IFRS 9 / CECL expected credit loss model with these characteristics:

Model details:
- Portfolio: Commercial loans ($X billion, Y industries, Z geographies)
- Methodology: [PD/LGD/EAD components, discounted cash flow, etc.]
- Segmentation approach: [industry, risk rating, collateral type, etc.]
- Forecast period: [reasonable and supportable forecast horizon]
- Economic scenarios: [number of scenarios, weighting approach]
- Model developer: [internal team or vendor]
- Implementation status: [in parallel run, recently implemented]

Testing constraints:
- Available data: [historical data periods, limitations]
- Benchmark models: [existing models, industry benchmarks]
- Time and resource limitations: [validation timeline]
- Technical environment: [testing platforms, tools]
- Subject matter expertise: [available team skills]

Please help me design comprehensive model testing procedures by:

1. Recommending specific tests for the PD (Probability of Default) component:
   - Discriminatory power assessment
   - Calibration accuracy testing
   - Stability analysis
   - Sensitivity to economic factors
   - Segmentation effectiveness
   - Forecast accuracy evaluation
   - Benchmarking approaches

2. Recommending specific tests for the LGD (Loss Given Default) component:
   - Historical recovery rate analysis
   - Collateral valuation assessment
   - Time to recovery assumptions
   - Discount rate appropriateness
   - Cure rate validation
   - Stress scenario impact
   - Industry comparison

3. Recommending specific tests for the EAD (Exposure at Default) component:
   - Utilization rate analysis
   - Commitment conversion factor validation
   - Prepayment assumption testing
   - Facility type comparison
   - Stress condition behavior

4. For the overall ECL calculation:
   - Economic scenario reasonableness
   - Scenario weighting methodology
   - Management adjustment evaluation
   - Aggregation methodology
   - Period-to-period volatility
   - Sensitivity analysis
   - Back-testing approaches

5. For each recommended test:
   - Detailed testing procedure steps
   - Required data and inputs
   - Statistical techniques to employ
   - Sample selection methodology
   - Acceptance criteria and thresholds
   - Common issues to watch for
   - Documentation requirements

Format your response as a comprehensive model testing plan that balances thoroughness with practical execution constraints.

5. Evaluation Criteria:

  • Does the prompt clearly describe the CECL model and portfolio characteristics?
  • Does it provide context about testing constraints?
  • Does it request specific tests for each model component?
  • Does it ask for detailed testing procedures and acceptance criteria?
  • Does it balance thoroughness with practical execution considerations?

6. Practice Activity:

Create your own advanced prompt for model testing related to:

  1. A fraud detection model
  2. An asset-liability management model
  3. A credit card balance response model

Exercise 3: Model Validation Documentation Prompt Engineering

Objective:

Learn to craft prompts that help develop effective model validation documentation and reports.

Background:

Model Validators must document their validation activities and findings. A key challenge is creating clear, comprehensive documentation that meets regulatory expectations and supports model governance.

Exercise:

1. Scenario:

You need to develop a comprehensive model validation report for a recently validated stress testing model.

2. Basic Prompt Example:

What should I include in a model validation report?

3. Prompt Improvement Activity:

  • Identify the limitations of the basic prompt
  • Add specific details about the stress testing model
  • Include context about validation activities performed
  • Request a structured report outline with section content
  • Ask for effective approaches to document findings and conclusions

4. Advanced Prompt Template:

I am a Model Validator at a [size] financial institution developing a comprehensive validation report for a stress testing model with these characteristics:

Model details:
- Purpose: Capital adequacy assessment under stressed scenarios
- Scope: [balance sheet projection, PPNR, credit loss, etc.]
- Methodology: [statistical, simulation, expert judgment]
- Regulatory context: [CCAR, DFAST, ICAAP, etc.]
- Model risk rating: High (due to materiality and regulatory scrutiny)
- Model owner: [business line or function]

Validation activities performed:
- Conceptual soundness assessment
- Process verification and implementation testing
- Outcomes analysis and benchmarking
- Sensitivity testing and stress scenario analysis
- Developmental evidence review
- Data quality assessment
- Ongoing monitoring evaluation

Validation results:
- [X] findings identified (Y high, Z moderate, W low)
- Key areas of concern: [brief description]
- Strengths identified: [brief description]
- Overall conclusion: [conditional approval, approved with conditions, etc.]

Please help me develop a comprehensive model validation report by:

1. Providing a detailed report structure with:
   - Executive summary approach and key components
   - Detailed section outline
   - Appropriate appendices
   - Supporting exhibits and visualizations
   - Cross-referencing approach
   - Glossary and technical terminology handling

2. For each major section, recommend:
   - Specific content to include
   - Level of technical detail appropriate for different audiences
   - Effective presentation of complex testing results
   - Data visualization approaches
   - Common pitfalls to avoid
   - Regulatory expectations to address

3. For documenting findings:
   - Classification and severity framework
   - Root cause analysis approach
   - Impact assessment methodology
   - Remediation recommendation structure
   - Timeline and ownership documentation
   - Follow-up and closure process

4. For the executive summary:
   - Key messages to highlight
   - Risk-based conclusion framework
   - Limitations and uncertainties to disclose
   - Conditions for approval
   - Ongoing monitoring requirements
   - Effective communication of technical concepts to senior stakeholders

Format your response as a comprehensive model validation report framework that meets regulatory expectations while effectively communicating validation results to different stakeholders.

5. Evaluation Criteria:

  • Does the prompt clearly describe the stress testing model and validation activities?
  • Does it provide context about validation results and findings?
  • Does it request a detailed report structure with section content?
  • Does it ask for approaches to document findings and conclusions?
  • Does it consider different stakeholder communication needs?

6. Practice Activity:

Create your own advanced prompt for model validation documentation related to:

  1. A fair lending model validation
  2. A vendor model validation
  3. A model validation for a recently remediated model