Risk Management and Credit Evaluation System for DHgate Foreign Trade Order Data in Spreadsheets-OK Spreadsheet-The best and new spreadsheet

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Introduction

Efficient risk management and credit evaluation are critical to ensuring the stability of foreign trade operations. This article explores how to organize and analyze DHgate's foreign trade order data in spreadsheets to build a robust risk assessment model. By integrating factors such as customer credit history, transaction amounts, and payment methods, we propose a scoring mechanism to evaluate client credibility, identify potential risks, and minimize transaction losses.

Data Organization in Spreadsheets

The foundation of effective risk management is well-structured data. Key steps include:

Storing order history, client details (e.g., registration duration, past complaints), and payment records in standardized tables.
Categorizing columns for critical fields: Order_ID, Client_Rating, Transaction_Amount, Payment_Method, and Delivery_Status.
Using Pivot Tables or VLOOKUP


        Risk Assessment Model Construction
        A dynamic scoring system evaluates clients based on weighted factors:
        
            
                Risk Factor
                Weight (%)
                Metrics
            
            
                Credit History
                40%
                Past late payments, refund requests
            
            
                Transaction Amount
                30%
                Order value relative to historical average
            
            
                Payment Method
                20%
                Escrow usage vs. direct transfer
            
            
                Order Frequency
                10%
                Sudden spikes in purchase volume

The final risk score is quantified as: Score = Σ(Weight × Factor_Value)

Risk Factor	Weight (%)	Metrics
Credit History	40%	Past late payments, refund requests
Transaction Amount	30%	Order value relative to historical average
Payment Method	20%	Escrow usage vs. direct transfer
Order Frequency	10%	Sudden spikes in purchase volume

Credit Evaluation Implementation

Leverage spreadsheet functions to automate scoring:

Use IFSUMIFS
Assign tiers (A/B/C/D) via =IF(Score>80,"A", IF(Score>50,"B","C"))
Color-code tables using Conditional Formatting for visual risk alerts.

Proactive Risk Mitigation

Recommended actions include:

For Tier C/D Clients:
Large Orders:50% from historical patterns.

Monitor real-time dashboards tracking metrics like % of Late PaymentsDispute Rate.

Conclusion

Integrating structured data analysis in spreadsheets with a weighted risk model enables DHgate sellers to proactively manage credit exposure. This system enhances decision-making, reduces financial risks, and supports sustainable growth in cross-border e-commerce.

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