With the update of scientific and technological means in recent years, there have been some application practices of big data credit reporting in the mutual gold industry. Hu Xin introduced that the mutual financial industry currently mainly collects four types of data: user behavior data, financial credit data, communication data and e-commerce data, and conducts marketing, product design, anti-fraud and credit evaluation before lending. , Borrower management after loan.
The construction of big data and credit information system is the focus area of Narada Think Tank. Recently, Narada Financial Research Institute held a closed-door seminar on “Breaking Information Island Technology Drives Credit” in the big data credit reporting industry, inviting a number of senior figures from academia and the industry to discuss in-depth issues in the industry. Many guests at the scene expressed their expectation that through the use of big data, credit reporting will not only “catch bad people”, but also allow all “good people” to enjoy more convenient and effective financial services.
Big data promotes changes in the credit information system
At the beginning of this year, Baihang Credit, the first market-oriented credit reporting agency in China, was officially launched, marking the initial formation of a “government + market” double round between the private credit reporting agency and the Credit Reference Center of the People’s Bank of China (hereinafter referred to as “central bank credit reporting”). driven development model.
Since its inception, Baixing Credit Information has been positioned to develop in a dislocation with the central bank’s credit information. “The customers of the central bank’s credit investigation are mainly large commercial banks, that is, traditional businesses; while Baihang’s credit investigation mainly faces Internet financial business or emerging Internet business.” Li Jiaxian, head of the Baihang credit investigation team, introduced. .
Li Jiaxian said that Baihang Credit has signed cooperation agreements with more than 700 emerging small and micro financial institutions, and now Baihang has collected data covering about 40 million borrowers. “At this rate, we expect to fully cover the user population of Internet finance by the end of this year, with the number exceeding 100 million.”
For this change in the credit information system, Li Jiaxian believes that the maturity of big data technology has subverted the traditional concept of credit reporting. “The boundary of modern credit information needs to be redefined, and Baixing Credit Information is trying to create an ecosystem.” He looks forward to this.
Information asymmetry is the biggest demand point in the industry
The emergence of Baihang Credit Information has greatly boosted the confidence of practitioners in the mutual finance industry. What pain points have been solved in small and micro finance? How can mutual financial institutions use big data credit information to do a good job of risk control? In this regard, Hu Xin, executive vice president of Wanhui Group, pointed out that since most mutual financial institutions are engaged in inclusive finance business, this group of people has a great demand for borrowing, but the central bank’s credit investigation is not covered. For the mutual gold industry, risk control is more difficult.
Regarding this difficult issue, Li Jiaxian believes that insufficient information on borrowers and insufficient judgment basis make the approval rate of online lending institutions low. “We always keep a bunch of ‘blacklists’ and limit ourselves to ‘catching bad people’. In fact, the real meaning of credit reporting is to prove that he is a good person. I also firmly believe that most people are good people.”
With the update of scientific and technological means in recent years, there have been some application practices of big data credit reporting in the mutual gold industry. Hu Xin introduced that the mutual financial industry currently mainly collects four types of data: user behavior data, financial credit data, communication data and e-commerce data, and conducts marketing, product design, anti-fraud and credit evaluation before lending. , Borrower management after loan.
However, the data of a single mutual gold company is limited after all. Hu Xin is full of expectations for Baihang Credit Information, “As a semi-official organization, Baihang Credit Information is willing to receive P2P data, which is inspiring and beneficial to the industry. Therefore, the mutual gold industry is very active and proactive in connecting data to Baihang. Industry. Excellent companies in the industry hope to stay warm and tide over the difficult times together.”
Tang Mingqin, Dean of the School of Credit Management, Guangdong University of Finance, also believes, “Many of China’s mutual financial problems are actually credit reporting problems. There is information asymmetry between mutual financial platforms and between borrowers and lenders. This is the biggest problem in the industry. demand point”.
The division of private information and shared information
For the expansion of credit data dimensions, Wei Li, an associate professor at the School of Management of Sun Yat-Sen University and a specially-appointed expert on the Guangdong Provincial Local Financial Risk Monitoring and Prevention Platform, insisted on supporting his opinion. He believes, “In addition to financial information, other social credit information can also be used as a Credit judgment basis, this is a breakthrough point.”
Lan Yun, director of the Guangdong-Hong Kong-Macao Greater Bay Area Blockchain Application Promotion Center and director of the Internet + Big Data Development Center of the Guangdong Decision-making Consulting Research Base, raised concerns about this, “There must be a clear information belt between private information and shared information. He suggested that “all online and offline behaviors of individuals should be classified, scored according to the nature of privacy and sharing, and all behaviors should be weighted from 0 to 1 and given a proportion. This is a data model. It can be done.”
Lin Jianguang, vice president of the large enterprise division of Tongdun Technology, added, “To be honest, only a part of the data of third-party companies is legal now.”
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