Application of Big Data Credit Information and Risk Control in Enterprise Big Data

Application of Big Data Credit Information and Risk Control in Enterprise Big Data

The Internet demographic dividend zone has passed, the cost of obtaining customers has increased, and the requirements of users for products have also increased. High-value and low-cost services are the current trend. Among them, enterprise service is committed to improving efficiency and reducing costs for enterprises in production, sales and communication, and is favored by more and more capital.

With the penetration of artificial intelligence into the industry and the sharp increase of data volume, more and more enterprise service products are using artificial intelligence, big data and other related technologies to provide smarter services. As the training "grain" in the artificial intelligence model, big data occupies an important position. How to mine and use enterprise data is an important way to do a good job in enterprise service. The sources of enterprise big data mainly include the following aspects:

A digital documents within the enterprise, such as personnel data and paper data.

B enterprise's self-produced data, such as customer data, office data, production and operation data, social data, e-commerce data, payment data and supply chain data. It is precipitated by OA, ERP and CRM systems within the enterprise;

C. Enterprise credit data

Government public data-such as credit information publicity data of commercial enterprises, data of untrustworthy executors and executors, judgment documents, court announcements, tax data, movable property financing data, bidding, judicial auction data, patent trademarks, administrative penalties and other data. Internet public data-such as news data, recruitment website data, and housing disclosure data.

Overview of credit report

1. Definition of credit investigation

The word "credit investigation" originated from "Eight Years of Zuo Gong". "A gentleman's words are trustworthy and have signs, so his resentment is far greater than his body". Among them, "collecting by faith" means that you can verify the credibility of your words, or you can collect and verify credit. Modern credit investigation is an activity of collecting, sorting, saving and processing the credit information of natural persons, legal persons and other organizations according to law, providing credit reports, credit evaluation, credit information consultation and other services to help customers judge and control credit risks and carry out credit management.

2. Policy/technology/market environment analysis

policy

Our society has gradually changed from an acquaintance society to a stranger society, and credit risk and credit crisis have also appeared, so it is urgent to speed up the construction of credit system. However, in the administrative process, the mechanism of "trustworthy encouragement and disciplinary action against dishonesty" has not been fully established. Although the "Regulations on the Openness of Government Information" has made specific provisions on the disclosure of government information, in the process of implementation, the disclosure of government information is not comprehensive, and the lack of some credit information weakens the integrity of credit information and is not conducive to the formation of accuracy.

technology

Secondly, the Internet era has long been recognized by everyone. A large amount of data left by enterprises and individuals on the Internet has brought data foundation for credit investigation, and with the development of big data, cloud computing and artificial intelligence, it has provided technical support for intelligent credit investigation.

market

In addition, China's market economy system has not been established for a long time, and the credit awareness and social credit environment of the whole society are still relatively weak. Acts of breaking promises for economic benefits occur from time to time. This is due to weak credit awareness and low cost of breaking faith. As an important part of finance, credit investigation is the core of risk control. With the rapid development of Internet finance and the adaptation to the Internet, the big data credit reporting mode has emerged, and it is urgent to establish a perfect credit reporting system to protect the development of credit reporting.

3. Domestic and international credit investigation modes

China's credit investigation is in the primary stage, and there are mainly the following international credit investigation modes at present.

A. market orientation. In the United States, Equifa, Experian and TransUnion provide services for loan and credit enterprises according to the laws and operating mechanisms of market economy. Britain is the birthplace of P2P, and the online lending platform represented by Zopa facilitates both borrowers and lenders to complete the transaction according to the risk and interest rate level, so that both borrowers and lenders can benefit from it, which plays the role of credit intermediary to some extent.

B. Government-led, China, German. Taking China as an example, the credit information system of the People's Bank of China is mainly led by the government, which authorizes the creation, collection, maintenance and integration of credit information of some enterprises and individuals in China. At present, it has covered the data of banking institutions, courts, telecommunications, social security, microfinance and other institutions, and the number of individuals and enterprises has maintained a growing momentum. From 864 million natural persons and 20.68 million enterprises and other organizations in April of 20 15 to 926 million natural persons and 237 100 enterprises and other organizations in May of 20 17, there are nearly140,000 people in Chinese mainland, and the number of enterprises and other organizations is also increasing. There is still a lot of room for growth in the coverage of the credit information system.

C. Trade associations * * * enjoy, trade members and share data, and establish a credit * * * sharing center with trade associations as the core. Organizations that join the association can enjoy the data and provide some data support, thus expanding the data sources of the association.

D. Mixed development, taking South Korea and India as examples, with mixed development of government and market.

4. Credit product model

The product model of credit information industry mainly includes the credit information of enterprises and individuals divided by business model, credit information, business credit information, employment credit information and other credit information divided by service objects. Some credit information services for different clients are completed by one institution, and some are completed by independent enterprises with upstream and downstream credit information agencies. According to the scope of credit information, it can be divided into regional credit information, domestic credit information and transnational credit information.

5. Credit industry chain

The credit industry chain includes upstream data producers, midstream credit reporting agencies and downstream credit reporting information users, among which the operation mode of midstream credit reporting agencies mainly includes collecting data, processing data and selling products. Data providers mainly include financial institutions such as banks, government departments, industrial and commercial enterprises and individuals, which involve almost all aspects of people's lives. The data obtained by the credit bureau from the data provider is processed by a certain model to get the credit rating result, and then the service is output. The users of credit report mainly include real estate developers, recruitment enterprises, P2P platforms and financial institutions. And most of them occur in the scenes of individual buying houses and cars, personal micro-loans, corporate credit, bond transactions, etc.

face a problem

1. Credit supervision and legal perfection need to be improved, government information disclosure needs to be strengthened, and credit laws and regulations are not perfect;

2. The computing power of data processing algorithms needs to be improved. With the combination of big data and credit reporting, higher requirements are put forward for data processing, analysis and modeling, so as to better tap the information value of enterprises.

3. The problem of credit information security is serious. Although the country has been issuing policies to protect credit data, the security of private data of individuals and enterprises is facing very severe challenges, which has given birth to the development of a huge black industry and brought about financial fraud, telecom fraud, online fraud, Trojan horse virus stealing private data for trading profits and other illegal and criminal activities.

7. The difference between big data credit reporting and traditional credit reporting

1. The coverage group is more abundant. With the popularity of the Internet and the vigorous development of Internet finance, more people or enterprises will leave data on relevant platforms and expand the groups covered by credit information.

2. The data sources are more extensive, and the data sources of traditional credit reporting are relatively single, but big data credit reporting will integrate public and semi-public data from the Internet, cooperative data from third parties and free data, and the data sources will become more extensive.

3. Dig deep into the value of data. With the application of big data and artificial intelligence in the credit reporting industry, machine learning, NLP, text extraction and other technologies have deepened the mining of enterprise data.

Industrial application of enterprise credit data

1. Credit risk control, the core of finance is risk management. At present, government credit publicity organizations, such as National Enterprise Credit Inquiry Network, China Credit Enforcement Network, China Credit Enforcement Information Network, Court Network and Credit China, publicly inquire about data, and provide credit financial institutions with information inquiry, credit report and monitoring services before, during and after lending.

2. Financial leasing, which provides monitoring services for financial leasing companies before and after financing, improves staff efficiency, and goes deep into various business departments through the group account system to improve work quality and efficiency.

3. Credit rating, based on multidimensional data such as business, legal affairs, news, management and debt. The credit rating of enterprises is universal.

4. Supply chain finance, around the core enterprises, manages the capital flow and logistics of upstream and downstream small and medium-sized enterprises, transforms the uncontrollable risk of a single enterprise into the controllable risk of the whole supply chain enterprise, obtains all kinds of information in a three-dimensional way, and controls the risk at the lowest financial service.

5. Others, such as recruitment, business research and law firms.

Future prospect of enterprise credit reporting

1. Enjoy the data * * *

As the core asset of the credit risk control industry, data is also the cornerstone of building a credit society. Excessive isolation or excessive enjoyment is not conducive to the development of the industry. Therefore, how to achieve * * * win-win and privacy protection on the basis of data enjoyment, break the data island, open up the data channels of various platforms, and let different data come together to jointly build a credit information system is the future development trend.

2. Mining data values

With the continuous development of big data credit information technology, credit information products will develop from initial information mining to deep mining. The first kind of mining refers to the integration and classification of the relevant data around the enterprise through crawling storage, third-party API interface or data cooperation, and simply presents them in the form of information reports and pictures. Deep mining is to combine the collected data with the professional knowledge of credit investigation to build products such as risk identification and quantification, rule engine, enterprise association diagram, data visualization and so on. And dig deep into the data, so as to deepen credit products and services and improve the professionalism of credit products. For example, when an enterprise has negative information on the network, it can quickly identify risks and give early warning to other enterprises, and quantify the early warning level according to the risk situation.

3. Provide vertical and sub-domain services

With the continuous expansion of the credit information market, some credit information agencies have begun to focus on a certain segment or a certain business link based on their own characteristics and advantages, providing targeted and customized credit information products and services. For example, provide crawler technology, one-stop crawling, cleaning, integration and warehousing; News and public opinion monitoring service; Provide enterprise customer service, screen superior customers for financial institutions and realize precise marketing; Provide corporate financial services, such as wealth management, financing, payment, credit, etc.; Provide C2B and B2B equity investment matching platforms, etc.