Background and Challenges
In the financial industry, risk control is a core business for banks and other financial institutions. Traditional risk management models rely on manual reviews and rule-based engines, which often suffer from inefficiency, high false-positive rates, and an inability to counter emerging fraud methods. A large commercial bank sought to introduce an intelligent risk control system to improve loan approval efficiency, reduce non-performing loan ratios, and enhance anti-fraud capabilities.
Huibi Information’s Solution
Shanghai Huibi Information Technology Co., Ltd. (hereinafter referred to as “Huibi Information”) developed an intelligent risk control solution for the bank based on its independently developed AI-powered risk control platform. Key modules include:
- Big Data Credit Analysis
Integrated internal bank data (e.g., transaction records, credit scores) and external data (e.g., social media activity, e-consumption behavior) to build comprehensive user profiles.
Employed machine learning algorithms to accurately assess clients’ repayment capacity and credit risk. - Real-Time Fraud Detection
Utilized deep learning models to monitor abnormal transactions in real time (e.g., frequent transfers, logins from unusual locations) and automatically trigger risk alerts.
Combined graph computation technology to identify organized fraud, such as “promotion abuse rings” or money laundering networks. - Automated Credit Approval
Used natural language processing (NLP) to automatically parse applicant documents (e.g., income verification, credit reports), reducing manual review time.
Implemented a dynamic scoring mechanism to adjust risk strategies based on market changes, improving approval accuracy.
Results Achieved
- 80% improvement in approval efficiency: AI system completes preliminary assessments within 10 minutes, compared to 1–3 days for manual reviews.
- 35% reduction in non-performing loans: The intelligent risk control model significantly reduced approval rates for high-risk loans, optimizing asset quality.
- 95% fraud detection accuracy: The AI model outperformed traditional rule-based engines in identifying novel fraud tactics.
The bank highly endorsed Huibi Information’s solution and plans further collaboration to refine the intelligent risk control system.