Research map / Graph learning / Graph self-supervised learning
Towards Consumer Loan Fraud Detection: Graph Neural Networks with Role-Constrained Conditional Random Field
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use GRC instead of GCN | Alipay auto-loan fraud detection · Alipay auto-loan, 1,000 training samples | F1-Score: 65.21% -> 77.01% | Helped |
| Use GRC instead of GCN | Alipay auto-loan fraud detection · Alipay auto-loan, 2,000 training samples | F1-Score: 68.79% -> 81.32% | Helped |
| Use GRC instead of GCN | Alipay auto-loan fraud detection · Alipay auto-loan, 3,000 training samples | F1-Score: 70.97% -> 82.83% | Helped |
| Use GRC instead of GCN | Alipay auto-loan fraud detection · Alipay auto-loan, 12,000 training samples | F1-Score: 79.07% -> 85.56% | Helped |
| Add CRF role constraint (ablation) | GRC · Alipay auto-loan, 12,000 training samples | F1 score: 83.83% -> 85.56% | Helped |
| Add edge-attribute neighbor aggregation (ablation) | GRC · Alipay auto-loan, 12,000 training samples | F1 score: 83.68% -> 85.56% | Helped |
| Add relation attention (ablation) | GRC · Alipay auto-loan, 12,000 training samples | F1 score: 84.34% -> 85.56% | Helped |
| Add time-slot attention (ablation) | GRC · Alipay auto-loan, 12,000 training samples | F1 score: 83.44% -> 85.56% | Helped |
Closest papers by meaning
- Context-aware Graph Neural Network for Graph-based Fraud Detection with Extremely Limited Labels (AAAI 2025 · similarity 0.84)
- DiG-In-GNN: Discriminative Feature Guided GNN-Based Fraud Detector against Inconsistencies in Multi-Relation Fraud Graph (AAAI 2024 · similarity 0.83)
- Dynamic Neighborhood Modeling via Node-Subgraph Contrastive Learning for Graph-Based Fraud Detection (AAAI 2025 · similarity 0.83)
- A Submodular Optimization Approach to Accountable Loan Approval (AAAI 2024 · similarity 0.82)
- Dynamic Graph Learning with Static Relations for Credit Risk Assessment (AAAI 2025 · similarity 0.82)
- Revisiting Graph-Based Fraud Detection in Sight of Heterophily and Spectrum (AAAI 2024 · similarity 0.81)
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