Aftermarket Service Network Inference for Financial Risk Assessment in Equipment Manufacturing Enterprises

Abstract

Equipment manufacturing enterprises often rely on long product lifecycles, maintenance contracts, spare-part supply, warranty obligations, leasing arrangements, and customer service networks. Financial risk may emerge when equipment failure rates increase, warranty costs rise, service response slows, or major customers delay payments. Traditional credit models rarely incorporate aftermarket service signals, although they can reveal hidden operational and cash-flow pressure. This study proposes an aftermarket service network inference model for financial risk assessment in equipment manufacturing enterprises. The model builds a knowledge graph linking manufacturers, equipment products, service stations, spare-part suppliers, customers, maintenance tickets, warranty claims, leasing contracts, invoices, and repayment records. A graph neural encoder captures service-network dependency, while rule-guided inference detects risk chains involving abnormal warranty concentration, spare-part shortage, delayed maintenance settlement, high customer complaint density, and weakening service coverage. The empirical dataset contains 22,600 equipment manufacturers, 184,000 equipment product records, 38,400 service stations, 2.73 million maintenance tickets, 410,000 warranty claims, 96,000 spare-part supply links, and 5,620 confirmed financial-risk events over 46 months. The proposed method reduces median risk-identification time from 94 days to 36 days compared with a statement-based credit model. It discovers 4,980 service-related financial stress paths and 1,740 customer-payment risk chains linked to repeated equipment failures. Graph aggregation compresses 12,300 service alerts into 2,860 enterprise-level review cases. Full quarterly assessment is completed in 8.4 minutes. These findings show that aftermarket service network inference can provide earlier and more interpretable financial risk signals for equipment manufacturing enterprises