Rural Internet Finance: Openness and Cooperation Lead the Future
Recently, the People's Bank of China and nine other ministries and commissions issued the "Guiding Opinions on Promoting the Healthy Development of Internet Finance" (hereinafter referred to as the "Opinions"). The introduction of the "Opinions" has legitimized Internet finance and also provided a guarantee for its survival of the fittest and innovative development.
The main reasons for the current slow development of rural finance lie in the following two aspects: First, for financial institutions, the risk control method for small rural loans is the same as the risk control method used by commercial banks for industrial and commercial enterprises. There is not much difference in operating procedures or cost between handling a 100,000 yuan loan and handling a 1 billion yuan loan. Banks are therefore unwilling to do microcredit. In addition, farmers lack loan collateral, making it difficult to meet banks' risk control requirements. Second, for farmers, traditional financial institutions have high loan interest rates and cumbersome procedures, and cannot meet their loan needs for small amounts and high frequency. Moreover, traditional financial institutions have few rural branches and traditional practices, so their service results are unsatisfactory.
In fact, according to the experience of India and Bangladesh, as well as the conclusions of Professor Mao Yushi's surveys in Shanxi and other places, farmers' credit is very good, with a bad debt rate not exceeding 3%. Rural finance has enormous development potential. At present, Internet companies that have seen this huge market space have already rushed into this blue ocean, and the service transformation of traditional rural financial institutions brooks no delay.
Due to the characteristics of the Internet, Internet + finance can easily make up for the problems of financial institutions having few rural branches and lacking financial services, but the Internet itself cannot automatically meet the requirements of banks' risk control systems. How to solve the difficult problem of risk management and control in lending funds is basically unsolvable by relying on the banking system itself. Only openness and cooperation are the key to solving the problem!
At present, there are mainly three types of agriculture, rural areas, and farmers service enterprises in society, including agriculture, rural areas, and farmers service providers represented by Cun Cun Le, Dabeinong, New Hope, and Noposion; e-commerce enterprises represented by Yimutian, Huinong.com, JD.com, and Taobao; and Internet finance enterprises represented by CreditEase, Ant Financial, Kaixindai, and Yilongdai. These enterprises have for many years been deeply rooted in rural production, circulation, and consumption, and have accumulated massive amounts of farmer transaction data. This data has now become an important asset for enterprises - big data resources.
For rural financial institutions, when their own data is insufficient to support farmers' credit assessment requirements, and when the cost of relying entirely on offline manual verification for each loan is too high to bear, seeking external data support to establish an Internet credit assessment mechanism is the way to solve the problem. That is, through Internet connections, funds and credit are separated, realizing another social division of labor in the field of rural finance.
Taking Dabeinong Group as an example, the "Nongyin Loan" it provides is a high-quality rural Internet finance product that separates funds from credit. Dabeinong is a well-known agricultural high-tech enterprise in China. It has built China's most complete pig farming service ecosystem, providing a comprehensive closed-loop service including feed, animal health products, vaccines, breeding pigs, biological feed, seed industry, and plant protection. With the help of Nongxin Cloud and Nongxin Mall, it collects various types of users' electronic transaction data, forming user big data resources, thereby building a user credit assessment system. Nongyin Loan is an Internet finance product launched against this background. Based on customers' transaction data and accumulated credit, it cooperates with financial institutions such as China Everbright Bank, China Guangfa Bank, and China Merchants Bank. The financial institutions provide funds, while Dabeinong provides customers and customer credit assessment, and requires that customer loans be used for specified purposes and paid to designated suppliers, thereby also controlling this financial product within a closed loop, controlling loan risk, and ultimately both parties sharing the loan returns. The "Nongyin Loan" model provides an excellent case of an agriculture, rural areas, and farmers service enterprise providing financial services and separating funds from credit.
In addition, there are currently the hottest Alibaba MYbank and Tencent WeBank. Both banks similarly claim not to take deposits, but instead, through highly cooperative methods with peers, position themselves as connection platforms, carry out credit services based on big data resources accumulated within their own systems, and connect financial institutions with small and micro enterprises or individuals. Taking Alibaba as an example, with the pattern of "everything related to me," the Alibaba Group has broadly laid out in various industries. Its investment map spans culture and entertainment, IT technology, e-commerce, mobile social networking, logistics, O2O, financial services, and other fields, involving more than 70 enterprise groups. It can be said that it is difficult for any individual in society not to have a "relationship" with Alibaba, and once connected with it, data and credit accumulation will occur. Therefore, it can be imagined that in the future MYbank will become a social connector and credit center. Any bank through it can find any individual with fund needs, thereby forming a force that changes the social financial landscape.
In the future, it is hoped that financial institutions can cooperate more with agriculture, rural areas, and farmers service enterprises, open their respective data, and cooperate in carrying out big data analysis to form more comprehensive user credit analysis results, letting large agriculture-related service enterprises become professional credit production platforms. Rural financial institutions, as professional fund operators, can jointly develop the rural financial market with them, thereby satisfying the country's financial poverty alleviation needs and also satisfying enterprises' profit needs. In this regard, cooperation between Yimutian and Postal Savings Bank of China, and between Dabeinong and China Everbright Bank, China Merchants Bank, and others, has explored a relatively successful model.