Countermeasures of Chinese Traditional Commercial Banks to Meet the Challenges of Internet Finance Based on Big Data Analysis—Evidence from ICBC

In recent years, network technology has continued to develop, and Internet finance has rapidly developed into a new business area. Internet credit is one of the important ways for banks to conduct business, and the scale of online credit has continued to expand. Due to the existence of various unpredictable factors, frequent emergencies, and online financial fraud, the overall market risk in the field of online credit has increased, and the rate of non-performing loans has continued to increase. Online financial fraud cases show that online credit risk has become one of the most prominent risks in the operation of commercial banks, which has a direct impact on the stability and development of commercial banks. We can build a bank database system based on big data, introduce professional big data analysis technical personnel, and constantly improve the big data sharing analysis platform, so that commercial banks can use system data more fully and effectively, and facilitate relevant business personnel to use big data technology for analysis and calculation. Big data is constantly produced, which provides basic materials for online credit risk assessment. Big data analysis technology is gradually mature, and it has the necessary conditions for online credit risk assessment. Based on the theories and technologies related to big data analysis, this paper comprehensively evaluates the online credit risk in the form of example data analysis, thereby effectively reducing the online credit risk coefficient.

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Application and research of Big data analysis in commercial Banks

2020 International Conference on Big Data and Social Sciences (ICBDSS) ◽

10.1109/icbdss51270.2020.00025 ◽

2020 ◽

Author(s):

Shuwei Sun ◽

Dingjie Hu ◽

Zhaofei Zhou ◽

Xingyou Hu ◽

Qi Shao

Keyword(s):

Big Data ◽

Data Analysis ◽

Commercial Banks ◽

Big Data Analysis

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Internet Financial Risk Early Warning Based on Big Data Analysis

10.54216/ajbor.030103 ◽

2021 ◽

pp. 48-60

Author(s):

Noura Metawa ◽

◽

Saad Metawa

Keyword(s):

Big Data ◽

Data Analysis ◽

Prediction Accuracy ◽

Financial Risk ◽

Big Data Analysis ◽

Risk Prevention ◽

Supervision System ◽

Finance Industry ◽

Risk Warning ◽

Internet Finance

Internet financial risk prevention is an important area for financial risk prevention. In recent years, a series of vicious high-risk events, such as cash lending and P2P platform running, have caused a great negative impact on the reputation of the Internet financial industry, which has aroused great concern from all walks of life. Based on big data analysis technology, this paper constructs an improved algorithm model, and carries out high-precision risk warning for China's Internet financial risk. The forecast data is basically consistent with the actual situation, and the prediction accuracy reaches 90%. It can be seen that the improved model based on the decision tree algorithm has higher prediction accuracy for Internet financial risk warning. This paper systematically sorts out the risks of China's Internet finance from two dimensions: risk type and main risk. And pointed out that the current Internet finance industry in China has a large overall compliance risk, and insufficient infrastructure construction leads to fraud risks. Separate industry supervision has a regulatory vacuum, arbitrage risks are more obvious, and China's financial consumer quality is not high, Internet financial institutions Improper exemption is risky. On this basis, it is proposed to speed up the construction of a multi-integrated Internet financial risk prevention system including the internal risk control system, the industry association self-discipline system, the government administrative supervision system and the effective social supervision system.

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