Large Data era: "Data + finance" model quietly rising

In the large data age, the application of large data in the financial field is becoming more and more common, but it is worth noting that the information structure of big enterprise and small micro enterprise is different significantly. Business norms of large enterprises, the information disclosure is more sufficient and the credibility is high, the information quality audit is relatively easy, therefore is suitable for the traditional credit audit method based on the financial statement and the mortgage asset quality, but the small micro-enterprise's management level difference is big, the market information disclosure is few, moreover our country many small micro-enterprises lack Authentic financial statements, so audit small micro-enterprise qualification, the search for small micro-enterprise information to pay a higher human and material costs, many banks have put forward many innovative ways, for example, to see the small micro-enterprises "three" (water meters, electricity meters, tax forms).

If the information structure is not improved, the effective way to cover the risk is to raise the interest rate and guarantee the mortgage. Under the condition that the current interest rate is not fully marketable and the mortgage collateral is deficient, the marginal cost and the service enterprise have little difference when using the traditional credit technology to carry on the small micro-finance. In a situation where the supply of credit remains scarce, banks have the incentive to raise the threshold of credit to force high-risk clients out of the market, which is why the "28 law" and the bank's credit rationing for small-business clients. Banking services 80% low-end customers to bring a small profit, it is better to drive this segment of customers out of the market, fully support 20% of high-end customers.

Big data is trying to break the deadlock over the difficulty of balancing costs and benefits. The core advantage of the combination of large data and credit business is to reshape information structure and reduce business costs. The development of e-commerce platform and social network has accumulated huge amount of data, and the logic and regularity information obtained from the mining of large network data is more authentic than the enterprise data published in reality.

The combination of large data and financial industry---------------------------internet finance is completely different from credit intermediary mode, even from the angle of matching capital supply and demand efficiency. Take Ali finance for example, including the platform merchant's historical transaction data, the credit record, the customer appraisal and so on internal data, as well as the tax record, the customs record and so on external data "The Big Data", has subverted the information asymmetry pattern between the bank enterprise. With the improvement of information structure, financial institutions can clearly identify the qualification of enterprises, and the information asymmetry is solved. Incentives for financial institutions to provide credit services to quality small micro-clients, the basis for "credit rationing" has ceased to exist. At the same time, the computing power of the electronic system to reduce the marginal cost of customer expansion to almost zero, "28 law" was the premise of the disappearance, in the big data era, financial institutions have the opportunity to from 80% of low-end customers to obtain valuable value.

Change incentive incompatibility in risk management

In China's traditional financial institutions, there is also a problem of incentive incompatibility in the risk management of small micro financial business. In the process of the continuous reform and development of the banking industry, the commercial banks generally strengthened the credit risk restraint mechanism, but the matching incentive mechanism was not established, therefore, the Customer Manager generally exists "credit is not as good as loans, more loans than less loans" "Cherish credit Psychology." Not only that, because the cost of continuous supervision after the loan is too high, the client manager lacks effective explicit incentive to control the risk, which leads to the increase of the social total default rate of the small micro-enterprise loan, and correspondingly gives the bank small micro-finance business default risk Big bad anticipation. If combined with the adverse selection and moral hazard that may arise in the case of asymmetric information, banks will choose to tighten the supply of credit to small micro-enterprises, resulting in uneven credit markets in small micro-enterprises.

In the big Data age, the change of information structure, the direct drive risk control idea changed radically. The original requirement is to compensate for the loss of coverage risk (whether it is high interest rate or mortgage guarantee requirement), now it becomes the ability to continuously assess and monitor the enterprise's steady operation, create cash and repay, and focus on "hard information" (balance sheet, etc.), and now it becomes the focus of "soft information" (Business and transaction data, documents, etc.). From the dependence of human resources to the reliance on electronic systems, the incentive incompatibility of risk management is no longer a constraint to the development of small micro-finance. The change of credit concept accords with the idea of solving the financing problem of small micro-enterprises.

Moreover, the system processing and real-time monitoring based on large data mining significantly shorten the business process, improve the efficiency of credit business, and have the flexibility to meet the characteristics of small micro-enterprise loan demand "short, frequency and fast". For example, Ali Financial launched the "daily interest, along with the loan" credit products, relying on the strong protection of information technology, not only solve the short-term financial needs of customers, but also effectively improve the speed of capital turnover, through financial innovation for the enterprise added value.

Open with real data

China's potential large data resources are very rich, from telecommunications, finance, social security, real estate, medical, credit system and other departments to E-commerce platform, social networking sites, covering a wide range. However, the data disclosed at this stage is only partial and fragmented, especially for the Social Credit system, which is critical to the evaluation of small micro-enterprises, which is still a regional fragmentation and a low level of transparency. Therefore, the high cost of obtaining information has undoubtedly hindered the development of small micro-finance.

Taking the typical Peer-to-peer model as an example, the transaction flow and mechanism of Peer-to-peer loan platform in our country are in line with the international advanced level, but it often faces the dilemma of insufficient public information in credit evaluation. Under the protection of sound, perfect and open credit system as well as the maturity market, the US Peer-to-peer platform can completely outsource the credit evaluation module. The information ecology is the key restricting factor that decides the Peer-to-peer organization to be able to exert in the future.

The availability of data is a prerequisite for the application of large data, and the authenticity of the data is also of critical importance. Under the background of China's current tax system, the financial statements formed by small micro-enterprises in order to evade taxes or to win preferential policies cannot reflect the business situation of the enterprises. Not only that, speculative financial fraud in the credit market has played a "bad currency away from the good currency" effect, will be financially sound, honest business enterprises gradually squeezed out of the market. The mass production and disorderly flow of the invalid data seriously disturbed the normal order in the large data age, and also had a bad effect on data mining.

In the era of large data, the "Data + Finance" model has been quietly emerging, especially in the financial field, gradually become popular with the existing solutions to small micro-enterprises financing problems are similar in nature, are to create a low-cost, fully symmetric market structure. Only the social public data information is truly networked, open and shared, the system and mechanism to encourage the real data production can be established, and the wide application of large data in the financial field will have a more suitable ecological environment.