As an integrated, one-stop risk control service platform, Bai Rong Credit Decision Approval System is based on the technical concepts of big data and risk control cloud of Bai Rong financial services, combined with new sciences such as machine learning and artificial intelligence algorithm, and helps customers to realize life-cycle risk control including pre-lending audit, in-lending monitoring and post-lending management from different levels such as data rules, loan review rule set and risk control model, so as to reduce the risk operation cost, improve the quality of post-lending assets and protect customers.
Bai Rong credit approval system not only supports the whole process management, but also can realize modular and flexible configuration according to customer needs, including anti-fraud system, pre-loan approval system, loan monitoring system, big data acquisition system and other modular products. Customers can choose combination module, single module or full-process system service.
At the same time, Bai Rong Decision Approval System can realize efficient data interaction with customers' original business approval system, external system and data platform, and effectively improve the approval efficiency.
Application Scenario/Crowd Bai Rong Credit Approval Decision System can provide services for credit products with consumption scenarios, such as auto finance, consumer finance, medical beauty staging, education staging, tourism staging, and credit products without consumption scenarios, such as wage loans, offline cash staging, online cash staging and other corporate customers related to credit business. All these credit structures can use Bai Rong's credit approval system; The main customers who use the system are credit institutions that do not have their own credit approval system, but need to improve the credit management process through the credit approval system.
In the loan stage, by integrating the data in the customer bank and the Bai Rong loan module, we can monitor the borrower's credit deterioration, debt changes and contact status, and identify and quantify risks according to risk management rules and strategies. If there is a trend of credit deterioration, we will push the risk warning message to customers at the first time, judge the overdue probability according to the credit behavior scoring model, realize continuous monitoring and forward-looking management of risks, and effectively prevent the occurrence of risks.
In the post-loan stage, big data collection has a subversive change to the traditional collection mode. Fully tap the personal asset value of overdue customers with the help of big data technology, and identify the potential risks and value of personal credit customers through early collection model and late collection model. This can help customers solve the chronic diseases of overdue and ineffective management and control, reduce the cost of outsourcing collection, realize the forward risk management and control, and realize early detection, early management and control, early collection and timely stop loss.