AI Prompt : Trade Finance Cost Calculation for Maize Export Deals

                    You are an expert in trade finance costing and agricultural exports. Your task is to **calculate the total cost of trade finance** for a [commodity] export deal worth [deal_value] across the following regions: [regions] during [timeframe].

Context:
- The transaction is LC-based (unless specified otherwise).
- Include pre-shipment and post-shipment finance components where applicable.
- Consider typical charges applicable in each region.

Focus on:
- Itemized cost components (interest, discount/LC fees, confirmation fees, bank charges, document/inspection fees, insurance, FX hedging, compliance costs).
- Clear formulas and assumptions (rate, base, tenure/days).
- Region-specific variations (India vs US vs EU).
- Sensitivity (how cost changes with rate/tenure).
- Final total cost and effective APR % of the deal.

Output in this exact structured format for consistency:

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### **Structured Output Format**

1. **Cost Breakdown Table (per region)**  
Use a markdown table with columns:  
**Region | Cost Component | Formula | Assumptions | Estimated Cost (USD)**  
Rows: Include at least:
- Pre-shipment interest
- Post-shipment interest/discount
- LC issuing fee
- LC confirmation/advising fee
- Bank handling/doc fees
- Inspection/quality/phytosanitary fees
- Insurance (cargo)
- FX hedging cost (if applicable)
- Compliance (AML/KYC/sanctions screening admin cost)
- Other (courier, notarization, stamping as relevant)

2. **Totals Table**  
**Region | Subtotal (Finance Costs) | Subtotal (Non-Finance Costs) | Total Cost | Effective Cost % of Deal**

3. **Summary (150?250 words)**  
A concise synthesis explaining:
- Key cost drivers and where traders tend to overspend.
- Regional differences (e.g., LC confirmation more expensive for certain corridors).
- Practical ways to reduce cost (optimize tenor, digital docs, negotiate fees, risk-sharing).
- Brief sensitivity note (e.g., +1% interest or +30 days tenor impact).

Ensure figures and assumptions are aligned with your latest knowledge cutoff. If precise local rates are unknown, clearly mark assumptions and offer typical ranges.