A Retail Intelligent Risk Control Project for a City Commercial Bank
The bank's retail scoring system is designed to support end-to-end credit lifecycle management. It relies on big data, modeling, and analytical technologies to enhance risk control capabilities.
Based on data from core banking, personal loan, credit, APS, and other business systems, build scoring systems for credit card decision management, personal loan decision management, and micro and small business loan decision management.
Developed an external data management platform by partnering with government agencies, internet platforms, and other external organizations. This enabled access to valuable third-party data and continuously expanded data resources across various use cases.
Built a mature AI platform to enhance data extraction, analysis, and processing capabilities. This significantly improved user efficiency and continually increased the accuracy of risk quantification through ongoing model and algorithm optimization
In the mid-lending and post-lending stages, technologies such as big data and behavioral analysis are used to dynamically track and analyze risk behaviors across multiple scenarios, thereby enhancing the quality and efficiency of end-to-end credit management.