Financial institutions face problems such as high marketing costs and low conversion rates. How to achieve precise marketing, reduce marketing costs, and improve conversion rates.
Data Silos
There are problems with the lack of shared data and unified data standards between institutions and within each internal business. The challenge is to break data silos and fully unleash the value of data.
Credit Risk
Facing problems such as endless fraudulent schemes and difficulty assessing risk due to missing data, the challenge is to quickly and accurately identify risks and reduce bad debt rates.
Technological Bottlenecks
Mining big data not only requires the application of advanced technology but also rich industry experience.
Solution
Accurate Marketing
Multi-Dimensional And Full-Scenario Coverage, Achieve Precise Contact
“Wallet radar”, full coverage of consumption scenarios, recognize and evaluate customer consumption habits, output risk ratings, interest willingness ratings, and wealth capacity ratings.
Data Standardization
Establish Standards And Define Standards
Establish standards and define standards to unify the analysis and processing of data from various institutions and make "dead" data "alive."
Intelligent Data Analysis
Build an intelligent data analysis pipeline to help customers integrate and apply data at a low cost and quickly around the problem of data silos and release the commercial value of data.
Data Modeling, Out-of-the-Box Data Analysis Service
The application of low-code data modeling technology transforms scattered data into data analysis sets, providing out-of-the-box data analysis services through APIs, automated processes, and more.
Risk Score Model
Risk Assessment Model
An advanced risk scoring model combines machine learning algorithms and traditional logistic regression model algorithms to evaluate the possibility of customers' first three periods of overdue payments and payment willingness, with a score range of 0-900 points, and higher scores indicate lower risks.
Performance Evaluation
Characterize customers' performance behavior characteristics from two dimensions: performance capability and stability, comprehensively and effectively measure customers' willingness and qualifications, help institutions understand customers' performance characteristics, and effectively distinguish customer groups.
Consumption Capability Assessment
Based on the integration and analysis of customers' recent transaction and consumption behaviors, evaluate the customers' consumption capability, activity level, potential, and other related characteristics, help institutions enhance their understanding of customer consumption capability information, more accurately measure customer qualifications, and reduce the credit risk of institutions.
Identification Of High-Risk Customer Groups
Identification of High-Risk Customer Groups
Identify high-risk individuals in the credit behavior of targeted customer groups of institutions, in order to supplement the market demand for compliance blacklisted products. It is recommended to reject credit applications from identified customers.
Pre-loan Risk Warning
In the pre-loan access pre-credit phase, effectively intercept fraud and credit-type high-risk customers without changing any risk control strategies or processes. It can effectively screen out...while the access rate is almost unchanged.
Full Process Application Scheme
Customer Case
A consumer finance company serves the entire credit lifecycle management process by using the XK retail credit lifecycle marketing and risk management program to acquire and manage customers. They have built a mature artificial intelligence platform to enhance their data extraction, analysis, and processing capabilities, improving users' analysis efficiency. By continuously optimizing models, algorithms, and other means, they enhance risk quantification accuracy.
In the pre-lending and post-lending stages, they dynamically track and analyze risky behaviors across multiple scenarios using technologies such as big data and behavioral analysis, improving the quality and efficiency of credit lifecycle management. This also enhances the risk control ability of the company's employees and promotes improvements in various aspects of subsequent marketing and risk control.
Through this project, the consumer finance company's Changsha branch achieved its annual work goals in just six months, with a consumer credit investment of 430 million yuan, adding 5,375 new customers and maintaining a non-performing loan ratio of 0.3%.
Shanghai ICP Preparation No. 沪ICP备2021019186号-1
