Bank credit evaluation system and method based on deep learning
By constructing a deep learning-based bank credit assessment system, which combines multiple datasets and risk models, the system solves the problem of inaccurate credit assessment in traditional methods, achieves accurate prediction of customer credit development trends and risk identification, and generates detailed decision-making recommendations.
Patent Information
- Application Number
- CN202511035251.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-25
- Publication Date
- 2025-11-11
AI Technical Summary
In existing technologies, relying on traditional financial data to assess bank customer credit cannot fully reflect the customer's true situation and risk, resulting in inaccurate credit assessment, inability to identify customer credit development trends, and increased risk exposure.
A deep learning-based bank credit assessment system is adopted. By constructing customer datasets, transaction datasets, work datasets, and historical credit datasets, and combining demand analysis, volatility analysis, and a skills equivalence replacement risk model, customer credit assessment values are generated, taking into account the impact of customers' daily needs, work trends, and economic fluctuations on credit assessment.
It achieves accuracy and comprehensiveness in customer credit assessment, and through dynamic update mechanism and anomaly review, it reasonably predicts credit risk and generates detailed decision-making advice information sheets, thereby improving the accuracy of credit assessment and risk identification capabilities.