A Credit Conflict Detection Model Based on Decision Distance and Probability Matrix

Considering the credit index calculation differences, semantic differences, false data, and other problems between platforms such as Internet finance, e-commerce, and health and elderly care, which lead to the credit deviation from the trusted range of credit subjects and the lack of related information of credit subjects, in this paper, we proposed a crossplatform service credit conflict detection model based on the decision distance to support the migration and application of crossplatform credit information transmission and integration. Firstly, we give a scoring table of influencing factors. Score is the probability of the impact of this factor on credit. Through this probability, the distance matrix between influencing factors is generated. Secondly, the similarity matrix is calculated from the distance matrix. Thirdly, the support vector is calculated through the similarity matrix. Fourth, the credit vector is calculated by the support vector. Finally, the credibility is calculated by the credit vector and probability.

Information Disclosure in China’s Rising Securitization Market

E-commerce and FinTech are currently booming in China. The growing consumer market is accompanied by internet finance, by which consumers can easily borrow money from financial institutions online. As a result, the growing risks of financial institutions are of concern to the government and regulatory bodies. Consequently, the securitization market in China is seeing rapid growth that could affect financial stability. Applying FinTech and emerging technologies in securitization might be an effective way to protect against these risks. This paper studies the question of whether China needs a higher standard of information transparency in order to protect against its risks against the background of digital transformation. We analyzed the determinants of securitization in the Chinese banking sector, relying on data on banks for two periods: pre-2017Q4 and post-2017Q4. The main findings of the paper demonstrate that the application of FinTech in China’s banking industry resulted in less information asymmetry. The risk exposure was the most significant determinant in general. Higher risk exposures increased securitization transaction volumes, which reflects securitization with adverse selection problems between the originator and investors. Liquidity and profitability, as important determinants indicating the moral hazard problem, also affected securitization pre-2017Q4, but liquidity and profitability were found to be unimportant determinants after the application of FinTech (the post-2017Q4 period). Moreover, this study finds that the effects of the adverse selection and moral hazard problems varied in different types of banks. Overall, our findings suggest that the Chinese securitization market needs a higher standard of information transparency.

The Future Development Trend of P2P Online Lending Industry under The Financial Regulatory Policy and The New Situation

As an innovative Internet financial service mode, person to person (P2P) network lending has rapidly promoted the development of Inclusive Finance in China. However, in the development process of P2P network loan, there are also some problems, such as platform role deviation, institutional function alienation, industry credit difficulty and so on, which lead to a large number of phenomena, such as suspension of business, refund, difficulty in cash withdrawal and running away. Faced with this dilemma, the regulatory authorities began to carry out strict supervision on the industry and guide the benign exit and transformation of the industry. In view of this situation, this paper will predict the future development direction of China’s online lending combined with the financial regulatory policies and the future trend of Internet Finance under the new situation.

Development Status, Causes of Risks, and Risk Supervision Suggestions on Internet Finance in China

As a useful supplement to China’s financial system, the development of internet finance has promoted the innovation of financial model and injected strong vitality into the financial market. Internet finance provides customers with more convenient and fast financial services, effectively alleviates financial exclusion, and reduces information asymmetry. It is of great significance to promote the marketization of interest rate and the development of inclusive finance in China. However, internet financial risk events occur frequently, posing a serious challenge. Therefore, this research analyzes the causes of internet financial risks, and provides suggestions on internet financial risk supervision, so as to promote a healthy development of the internet financial industry in China.

Prevention of Internet Financial Risks in the Era of Digital Economy

As a pillar in the development of China’s economy, the financial industry plays a key role in the production and life of residents. Along with the widespread application of the internet, internet finance has gradually emerged as required by the times, and in the achievement of the collection and extraction of big data, related analysis and exploration technologies have been emphasized more. However, in the context of big data technology, there are still risks of unsound laws, inadequate business publicity, user information security, and capital liquidity in internet finance. Under this digital economy era, this article attempts to discuss these risks, which need to be prevented from establishing a good internet financial system, strengthening interindustry exchanges and cooperation, building a unified internet financial information supervision platform, as well as optimizing the internet financial credit reporting system, so as to promote a healthy and sound development of the whole financial industry.