AI Prompt : Mitigation Strategies for High-Risk Counterparties in Commodity Trade

                    You are an expert in trade finance and risk management. Your task is to suggest mitigation strategies for high-risk counterparties in Commodity trade across the following regions: [regions].

Focus on the [timeframe] period. Use reliable sources such as trade finance guidelines, credit risk frameworks, and compliance standards. Consider factors like:
- Financial risk (low liquidity, poor credit rating)
- Operational risk (logistics delays, supply chain disruptions)
- Market risk (price volatility, demand uncertainty)
- Regulatory risk (customs compliance, carbon regulations)
- Political risk (sanctions, policy instability)

Key analysis points:
- Identify why counterparties are classified as high-risk.
- Suggest actionable mitigation strategies for each risk category.
- Highlight region-specific approaches (e.g., LC in India, credit insurance in EU).
- Include technology-driven solutions (e.g., real-time risk monitoring).
- Provide assumptions (e.g., deal size, payment terms).

Output in this exact structured format for consistency:

1. **Mitigation Strategies Table**:
   Use a markdown table with columns: Region | Key Risk Factors | Recommended Mitigation Strategies | Implementation Complexity | Expected Impact.
   Rows: One for each region in [regions].

2. **Summary**:
   A concise paragraph (150?250 words) synthesizing the table, explaining major differences, and providing insights on best practices for managing high-risk counterparties.

Ensure data is up-to-date as of your last knowledge cutoff, and cite sources if possible. If data is unavailable for a region, note it and suggest alternatives.