From 100 billion to 1 billion, the personal credit market is also so large

Internet finance has gone from being hot to returning to rationality (by the name Fintech: Fintech's financial technology). It has also spread the word credit, risk control, and so on. It is like suddenly realizing that financial products are at risk. As part of the financial foundation, credit information is an important means to reveal risks and prevent fraud. With the increase of non-traditional data such as e-commerce consumption and social networks, Big Data credit has become a new word advertised by mutual gold companies. How big is that big data credit?

According to Jiang Qingjun, the digital credit report CEO, there is no clear definition of big data credit. More is a word created by the actual demand. â€œMost of the big data credit companies now provide basically. Big Data Risk Control Service Company." He said:

â€œTraditional credit data is standardized and structured data, and it is difficult to claim big data. Big data is only ordinary data that may be related to risk. Big data credit companies generally have the ability to acquire or analyze big data. Risk Management Services Company."

This is because most credit institutions (such as P2P lending companies) in the non-banking credit industry require credit control services for credit companies, including anti-fraud, various types of external data sources, negative credit information, and credit risk scores. , as well as pre-lending, mid- and post-risk management consulting. These requirements can be met by the risk control measures that incorporate big data technologies, and big data credits have also been accepted.

Even so, the role of big data in risk assessment is hard to say how significant. According to Jiang Qingjun, there are two main reasons for this:

One is the lack of data, that is, the actual data associated with the performance of personal credit in the data is very weak, and the modeled data is not enough. Although there are many data dimensions collected in e-commerce, social networking and other fields, in most dimensions, there are fewer available data and the data is relatively lacking.

Second, the risk assessment of big data is not a long time, and it is far from mature. There is not enough accumulated talent and experience. The most mature method at present is still the traditional assessment method represented by FICO.

However, he also believes that the risk assessment of big data belongs to the trend of the development of the industry, and there are corresponding preparations for counting credits.

From 1 trillion to 1 billion personal credit market

Quanzhou Credit Co., Ltd. is a private credit company. The management team is all from Shanghai Credit Co., Ltd. It also participated in the early exploration of the personal credit industry in China. The company mainly serves non-bank credit institutions, such as online lending institutions, P2P platforms, and consumer finance companies. Current customers include Renren Credit, Microfinance Network, Zhengda Wealth, and everyone's wealth, Jieyue United, block boxes, and letters. More than 300 credit service agencies including Fushou.

In addition to the classic credit information such as institutional credit information sharing services , the digital credit service also provides credit application anti-fraud assessment, credit risk scoring model development consultation, external data source connection, and Internet big data client authorization collection and other big data credit services . At present, many organizations have joined the anti-fraud platform and completed about 20 external big data sources.

However, despite being in the industry, Jiang Qingjun seems to have less good expectations for personal credit market. He stated that the scale of commercial value of the credit market has a strict proportional relationship with the total amount of the credit market, and made a rough estimate for Lei Fengnet (searching for the "Lei Feng Net" public number) :

The size of personal credit market is about 5% of total personal credit income. Excluding banking credit services, the scale of non-banking loans is about trillions. Apart from the portion of mortgage loans, credit loans with the strongest demand for credit services are less than 1 trillion.

The gross profit corresponding to the scale of 1 trillion loan is about 100 billion yuan, and the profit of 100 billion yuan can be distributed to the credit service agency with a maximum of approximately 5 billion yuan. Because credit service agencies can divide the service income they receive, it is part of the bad debts of loans. It is essentially helping credit institutions to reduce bad debts, but it does not receive more than part of the rewards of bad loans themselves (of course, there are also rewards for preventing bad debts for credit institutions, but There will be no change in magnitude.) Therefore, the sales revenue of 5 billion yuan, calculated according to the gross margin of 20%, will generate a net profit of about 10 billion yuan for the entire credit information service industry.

Even if calculated by 100 personal credit bureaus, the income per household is only 10 million. This does not take into account that the credit agencies themselves will also do credit checks. Jiang Qingjunâ€™s conclusion is that the credit market â€œwill either be too good for everyone or not be able to surviveâ€.

Can do a charity organization

What kind of credit is it?

According to Jiang Qingjun, â€œThe starting point of counting credits is to believe that credit services are the key path for promoting social credit levels,â€ and the company â€œmay end up being blamed on a public interest organizationâ€. He told Lei Fengwang that in fact the credit collection agencies can be public welfare, and the nature of public welfare is more favorable to the social credit system, but at present they â€œhave no ability and conditions to qualify for a charity credit agencyâ€.

At present, the credit services of commercial banks have been relatively complete, but there are still some market opportunities for credit services in the area of â€‹â€‹non-bank credit and social credit. Credit information companies can also provide corresponding risk control services for customer fraud and dishonesty. Therefore, we want to first obtain living space through commercial practices and provide credit information sharing platforms and risk control services for non-banking credit institutions.

There is a view that the current credit market data source is the key. However, according to Jiang Qingjun, if the credit information refers to the sharing of industry credit information, there is only one data source, namely, the credit customer credit history provided by the credit institution. At this time, the core is the credibility, service capabilities, and professionalism of the credit bureau. The data itself is not the primary issue for the sharing platform. He also believes that "sharing credit information has an irreplaceable value."

The title map comes from The Atlantic