The Status and Prospects of P2P Internet Finance
From the end of 2015 to the early 2016, China's Internet finance entered an era of government regulation. During this period, the government closed down several large counterfeit Internet financial companies, and disclosed their illegal means of operation and illegal acts. Pessimistic people feel that Internet finance has entered a long winter. On the contrary, optimistic people feel that the real spring of the Internet finance is coming. In any case, people want to learn more about the characteristics and risk management of Internet finance industry. Therefore, this article analyzes the essence of P2P Internet financial risk from the perspective of information economics, and puts forward a theoretical model of information flow risk control of P2P Internet finance to analyze the current situation of P2P loan industry. Finally, this article points out the development prospect and the basic trend of Internet finance.
The Risk of P2P Loan and the Theory of Information Economics
Prior to the existence of the Internet, the predecessor of P2P loans was called private lending and its main function is to lend loans within a family or between families in the event of a shortage of money. It can be regarded as a pure off-line model of P2P loans. The on-line model of P2P-loans initially came into being under the condition of e-commerce lending. For example, Alibaba has developed a P2P loan to finance its small- and micro- business owners in Taobao. Since Alibaba is well aware of the cash flow and operating conditions of businesses in Taobao, the risk of such a pure on-line loan model is relatively controllable. However, as the lender’s repayment capacity is unknown, other P2P loan companies do not use pure on-line models. Therefore, most of the P2P loan companies take the model of combining online and offline loan processes, by using online lending process to reduce management costs and the offline management of the loan process to minimize the risk of bad loans.
As with the risks of other credit operations, the risk of P2P loan can be analyzed by the theory of information asymmetry of economics and the theory of agent’s moral hazard. Information asymmetry theory is that the two sides of the transaction differ on the degree of awareness of risks. For example, for the borrowers’ repayment capacity, the borrowers themselves must know more than the lenders. Agent’s moral hazard theory refers to the fact that the interests of the borrowers were intentionally or unintentionally neglected in order to facilitate the loan transaction. Especially in large P2P loan companies, their employees, dispatched units or branch offices, are likely to give up or weaken risk control for short-term benefits.
While the core issue of all financial companies is how to control risk, the risk of P2P lending is greater than that of traditional financial firms. This is because banks usually predominate the loans businesses with low risks, while the other loans which cannot be obtained from the banks will enter the P2P loan business. Therefore, the risk management of P2P loans is more complicated than that of traditional banks. This article will focus on the particularity of P2P loan risk. Another emerging research area related to risk control is derived from the signal theory of ecological study. Signal theory mainly studies the characteristics of signal transmission and signal screening. Signaling model is that with observable behaviors, the market entities can transmit the exact information of commodity value or quality. Screening model indicates that market entities can identify the authenticity of information by various means.
This article aims to use the existing concepts of information economics to understand P2P Internet finance. For example, information asymmetry theory and agent risk theory make it more easily for us to understand the inevitability of various financial risks, and signal theory makes it easier for us to understand the value of large data credit.
Analysis of the Sources of P2P Loan Risks
The sources of P2P loan risks are divided into the following four categories. The first category is that the lender is defrauded due to the lender's greed and ignorance. For example, under the guise of P2P loans, Yizubao which has been closed deceived tens of thousands of people with a huge amount of money. From the perspective of information economics, this is due to information asymmetry between the lender and the intermediary. The solution is to reduce the degree of information asymmetry. One way is to require the participation of financial lawyers for large-sum loans, but this will increase the cost of lenders and agents. Another way is that the regulators should understand and control the business processes of these agencies so that Ponzi scheme or other illegal operations cannot survive.
The second type of P2P loan risk comes from agencies. As mentioned above, Yizubao is a vicious agency risk. Fake agencies are extremely malicious, including the creation of several companies to create fake cash flow, covering their Ponzi scheme. Involving huge social risks, these agencies will cheat thousands of lenders out of their money. There are two kinds of agency risks. The short-term agency risk will end up with absconding because of poor management. The long-term agency risk leads to the borrowers’ economic losses due to its weak risk control ability and high rates of bad loans. Such agents are vulnerable to major economic fluctuations.
The third type of risk relates to the borrowers. The security of P2P loans ultimately depends on the borrower's integrity and repayment capabilities. To avoid this risk, one approach is to check the credibility of the borrower's credit history. Another kind of borrower risk is the lack of repayment capability. To avoid this risk, the lenders should know the borrowers’ reason of borrowing and their current operating conditions, which requires an in-depth investigation of the borrower's family background, operating conditions, and local economic conditions.
The fourth type of loan risk is related to the regulator or the regulatory body. The government has two functions: one is to identify the illegal agencies and eliminate the black sheep; the second is to help legal agencies to improve their capability to resist risks. The relevant departments of the government can propose regulations for P2P loan companies, as well as for punishing and closing illegal institutions. To help P2P loan companies improve their risk-resistance capability is a long process, which can be carried out directly by the government, or indirectly through the P2P loan guild.
Method of Risk Identification and Regulation
The four types of loan risks described above can be regulated through traditional means as well as various modern methods. The latter includes big data credit, big data regulation, industrial self-discipline and supervision of public opinions. Big data credit, as the latest information technology, is to collect personal information from various sources to calculate and score. At present, in China, besides Ant Financial Services Group, the People’s Bank of China also provide traditional personal credit files, Sesame Credit, Tencent Credit, and other six personal credit information providers provide personal credit information Big data credit, as a supplement to traditional banks and governments, can provide credit information of people who have no history of banking borrowing, so that every borrower has his or her own credit information, which help borrowers and agencies to make sound lending decisions.
Big data regulation refers to the governmental supervision on the operations of agencies by collecting relevant data. This method can be seen as the expansion and innovation of e-government. There are two main functions of this regulation: one is that certain company's illegal operations can be found promptly by the government so that Ponzi scheme cannot continue; the second is to guide and support legitimate operation of standard companies.
Industrial self-discipline refers to mutual supervision and helps between companies in the same industry. China Internet Finance Association was established on March 25, 2016 in Shanghai. The main function of the association is to formulate management rules and industry standards according to the type of business. It is a national self-discipline organization in the Internet financial industry2. In addition, enterprises in the same industry can jointly develop the credit system and share the borrower’s blacklist, which can increase the borrower's default cost and improve moral standards of the whole society. On the "Cloud Computing and Big Data Integration Development" forum in the 2016 International Big Data Expo, Rongyou Wealth mentioned that large data and cloud computing can "play a big role in the screening of loan customers, amount setting, approval efficiency, and credit management"3. But data cannot determine everything. To achieve Internet financial security, we must also rely on big data and off-line risk control system and let them supplement each other. Big data can improve the quality of lending decisions4, while the off-line risk control system can reduce the proportion of bad debts.
The analysis and supervision of public opinions on Internet financial risk is an emerging financial phenomenon. In general, public-opinion analysis needs relevant information such as regulatory information, guided information, complaints and so on. The data can be collected from various sources, such as news, blogs, forums and some other social media. Through the statistical analysis of these data, the trend of Internet financial risk can be deducted and relevant policy-oriented advice can be provided for the government, enterprises and individuals.
In order to improve the control ability of P2P loan risk, this article proposes a P2P model based on information asymmetry theory and agent moral hazard theory from information economics (the risk control model of loan information flow is as follows). The purpose of this model is: (1) to protect lenders from being easily deceived; (2) to prohibit agencies from operating Ponzi scheme; (3) to help standard agencies improve their business level; (4) to help borrowers acquire a reasonable amount of loans; (5) to minimize rates of bad debt, and (6) to support regulators to work efficiently.
The risk control model of information flow of P2P loan in the figure includes nine main entities: the lender, intermediary agencies, the borrower, credit information companies, risk-control organizations, banks, lawyers, regulators, and industrial associations. The thick arrows in the figure mark the information chain that most of the P2P companies have already achieved. The thin arrows mark the information chain that only a few P2P companies have already achieved. The broken line arrows indicate that most P2P companies have not yet formed information chains. The following is some basic information:
(1) Credit companies should provide personal credit information to agencies. Credit companies include traditional credit companies, such as banks, as well as new big data companies.
(2) The risk-control institutes should provide financial guarantee information to intermediary agencies. The risk-control institutes can be a subsidiary of intermediary agencies (such as Yirendai), or a franchise of the intermediary agencies (such as Rongyou Wealth). In any case, intermediary agencies must share the same economic interests with risk-control agencies in order to avoid or weaken the agents' moral hazard. For example, the risk-control agency of Rongyou Wealth is also a franchise of the company.
(3) The intermediary agency should recommend qualified borrowers to lenders. The lender's decision is based on the credit information and financial guarantee provided respectively by the credit company and risk-control agency. At the same time, the intermediary agency can get the borrower’s information through special approaches. For example, the agency and the borrower can together go to the bank to print the borrower’s personal banking information.
(4) Once the borrower delays payment, the risk-control agency must timely take the recovery procedures and reflect the recovery condition to the intermediary agency and the lender.
(5) The intermediary agency should timely provide information to the regulatory institute, including the information of financial flow and bad debt rate.
(6) The intermediary agency should update and provide industrial standard information to industrial associations, including borrower blacklist and other relevant information.
(7) Financial information chain between banks and related entities mainly refer to loan information. Such information can effectively reflect the business level of an Internet finance company.
(8) Legal information chain between the lawyer and the relevant entity mainly refers to loan contract. Such information can effectively reflect the development of new businesses of the Internet financial center.
The above model is a theoretical model. Technically, some companies in the industry have already achieved some of the above functions. But they still need time for improving technology and management. In any case, the model can be used to demonstrate and explore the Internet finance, especially the status and solutions of P2P financial risk control.
First of all, the defraud risk and poor management risk of intermediary agencies can be solved by the information chain between the agency and supervisory institute. With this chain, the supervisory authority can use artificial intelligence to find out illegal operation of the intermediary agency. In addition, the government may also stipulate that when the number of investments exceeds a certain amount, the investment lawyers must get participated. The government can also provide professional investment services to the public, so that people can choose a better P2P loan companies to make investment.
The information chain between the credit information company and the intermediary agency and the information chain between the risk-control institute and the intermediary agency can be respectively used to reduce the double risk from "selected borrowers" and "regulated lenders". If these two risks can be controlled, a good agency can attract more lenders and borrowers, and further enhances its scale and ability to resist risks. The government's supervisory institute can also control the bandwidth and quality of information chains to reduce operation risks of intermediary agencies, thus stabilizing China's financial markets and providing sufficient funds for SMEs. This is of great importance for public entrepreneurship and innovation.
Information Flow of P2P Internet Finance and Big Data Technology for Credit Investigation
Since 2013, the rapid development of Internet finance has created new trends in the risk control of financial institutions. The risk control of traditional financial institutions such as commercial banks is based on the credit report from the Central Bank and judged by professional managers using qualitative methods. But in this way, customers will be easily missed and the classification and customization of personal services is not enough. Meanwhile, with a limited amount of customer information, lack of risk control experience, and weak control methods, many emerging Internet finance institutes have high rates of overdue and bad debts. However, there are also new commercial opportunities. People leave a lot of data "footprint" as they engage in e-commerce and Internet finance, making big data become a major means of risk control for both traditional and emerging financial institutions.
The above information flow shows the potential chains of information flow between various stakeholders and organizations in the ecological system of Internet finance. Through analysis of the signals of personal behaviors by artificial intelligence, personal credit evaluation can be obtained, which generates a new method called big data credit investigation.
Big data credit investigation can supplement traditional credit investigation from at least three aspects. First, with thousands of parameters, the mathematical model of big data makes credit evaluation more accurate than ever. This is because big data covers more behavioral signals than traditional method, thus improving signal transmission and signal screening capabilities. Secondly, more in-depth understanding of the borrower can be achieved because of the diversity of behavioral signals. Finally, since the time parameter is incorporated in the mathematical model, the timeliness of credit evaluation standard is thus improved.
Information Flow of P2P Internet Finance and Blockchain Technology
Partial realization or completion of information flow of P2P Internet finance requires a lot of managerial and technological improvement. The economic value of financial information flow
s depends on the reliability and cheapness of the efforts made in cross-company and cross-industry information flow. Therefore, the realization of financial information flow must be a decentralized distributed system, which is a major challenge to the traditional centralized management system of information technology. Fortunately, the blockchain technology derived from Bitcoin provides a possible direction for solving this problem5.
On June 27, 2016, blockchain technology was selected as one of the ten new technologies 2016 by the World Economic Forum. At the technical level, the blockchain can be transformed into a decentralized and fully distributed database. Users in this system can see every transaction and how it starts and how it is conducted. But the details are encrypted and only available to relevant people. The blockchain technology ensures the security of data and solves trust problems between nodes on untrustworthy networks.
In this article, the operational environment of financial information flow matches well with the characteristics of blockchain technology. First of all, information flow of P2P Internet finance covers a lot of relatively independent information system and is a management center without information network. Therefore, the management system of financial information flow must be distributed. At the same time, because a large number of personal and business information is included in the financial information flow, the relevant information must be encrypted and support reasonable function of regulatory institutes.
As for the Internet finance that covers P2P networks, the focus of debate should not be on whether Internet finance can exist or not, but what the government should do to help Internet finance grow and become robust Since ancient times, banks and private lending have always complemented each other. Now in the era of Internet, banks and Internet finance should also peacefully coexist. Banks use the “reservoir model”, which combines the two functions of financing and lending. While the Internet finance uses the “matchmaker model”, whose main function is to improve the efficiency and security of private lending. As a result, Internet finance can be used to provide more personalized and specialized financial services, as well as more charitable services and inclusive financial services.
Zhao J. Leon
Visiting Professor of College of Business, City University of Hong Kong
Member of the academic committee of Zijin Media Think Tank.
Chang Jiang Scholars Program in 2009
Note: This article is an excerpt from "The Status and Prospects of P2P Internet Finance-Analysis and application of the Theoretical Model of Information Flow", originally published on the "People's Forum·Academic Frontier" in February 2017.
4Jiaqi Yan,Wayne Yu,and J. Leon Zhao (2015),How signaling and search costs affect information asymmetry in P2P lending: The economics of big data, Financial Innovation. https://jfin-swufe.springeropen.com/about/editorial-board.
5 Marc Pilkington, Blockchain Technology: Principles and Applications, Research Handbook on Digital Transformations, edited by F.Xavier Olleros and Majlinda Zhegu.Edward Elgar, 2016.