Commodity Trade Finance Risk Prediction Through Logistics Transaction Graph Inference

Commodity trade finance supports industrial enterprises in purchasing metals, chemicals, coal, petroleum products, agricultural raw materials, and other bulk goods. However, this financing mode is exposed to risks from false warehouse receipts, duplicated pledges, abnormal logistics records, price volatility, weak buyer credit, and inconsistent trade documents. Traditional risk models often evaluate the borrower alone and fail to verify whether financing is supported by real commodity flow and repayment capacity. This study develops a logistics transaction graph inference model for commodity trade finance risk prediction. The model builds a heterogeneous graph linking borrowers, sellers, buyers, warehouses, logistics providers, warehouse receipts, invoices, purchase contracts, collateral records, commodity prices, and repayment behavior. A graph neural encoder captures transaction credibility, while a knowledge reasoning module identifies suspicious paths such as repeated warehouse-receipt pledging, circular trade, abnormal delivery gaps, and price-driven collateral shrinkage. The dataset contains 31,800 borrowing enterprises, 118,000 trading counterparties, 760 warehouses, 1.96 million invoices, 580,000 logistics records, 86,000 warehouse receipts, and 7,640 confirmed trade-finance risk cases over 34 months. The proposed method reduces median warning time before financing deterioration from 62 days to 22 days. It identifies 9,480 suspicious logistics-transaction chains and 1,920 duplicated warehouse-receipt pledge structures. Graph aggregation reduces manual document review from 27,500 trade batches to 5,840 relation-linked investigation cases. The inference engine completes portfolio assessment in 12.9 minutes and processes 2.14 million transaction edges during each full update. The findings indicate that logistics transaction graph inference can improve commodity trade finance risk prediction by connecting credit risk with verifiable trade, logistics, and collateral evidence.

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