• Journal of Distribution Science
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• v.13 no.10
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• pp.51-56
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• 2015

Purpose - This study examines Chinese P2P investment decision processes from a behavioral economics approach. Research design, data, and methodology - We analyze the online P2P investment product purchase decisions of 241 respondents in China, March 2015 to May 2015. T-tests were conducted to determine whether the framing effect influenced investor investment preferences. The Association Rule was used to identify the framing effect of respondent demographic characteristics on joint decisions regarding stable or risky investment products. Results - There are significant differences between the two groups (positive framing and negative framing) and their product-choosing behavior. In the positive framing group, female investors, young investors, investors with non-financial occupations and with limited or no experience, preferred stable P2P investment products. In contrast, in the negative framing group, investors with extensive investment experience preferred risky investment products. Conclusions - The framing effect influences investor choices in online P2P investment products. It is necessary to implement comprehensive supervision and full information disclosure regarding P2P investment products. P2P investment websites can also adopt different marketing strategies according to investor gender and age.

• Journal of the Korea Society of Computer and Information
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• v.22 no.6
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• pp.141-147
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• 2017

Along with the recent growth of Fintech industry and low interest rate basis, one of the alternative investment technique for expecting higher investment profit, P2P loan using P2P financial system is greatly increasing. P2P loan can be referred to as a type of Crowdfunding that the law of Crowdfunding (adopted to revised Capital Market Act) enacted on January 25th 2016 only allows investment type Crowdfunding so that it can be used as a tool of raising fund for startup and venture companies. Also, it is true that Korean government could not make any legislative foundation related to P2P loan. At this moment, those online platform companies mediating P2P loan are not included as financial companies, expected to cause various legal arguments. Financial Services Commission has released a guideline in February of this year saying that limit of P2P loan is 10 million Korean Won per arbitrating company and 5 million Korean Won per borrower. However, what is more important is to make a law supporting this institutional system. If legislation on P2P loan is implemented without care, it may disturb growth of the field but it may result in the damage of investors if not clearly defined by law. As this is the case, first, "revision of execution regulations for loan business" should take place as soon as possible to intensify inspection of loan companies by registering them to Financial Services Commission. Second, saving customer fund separately in the their organization. Third, making law on protecting investors such as regulating exaggerative advertisement. Fourth, to have transparent and fair public announcement system, standardized agreement and guideline describing clear understanding on autonomous public information publication of P2P loan online platform business and information on the borrower.

• Knowledge Management Research
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• v.19 no.2
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• pp.109-132
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• 2018

Recently, new financial services related to FinTech has gained attention more and more. Online P2P financial services transactions such as FinTech require careful examination of the constituents of information systems as an investment is made based on the information presented on the online platform without direct face-to-face contact. The purpose of this study is to find out the success factors of online P2P Lending service among FinTech. To serve the purpose, we build IS (information system) success model, and then use Kano model and fuzzy analytic hierarchy process (Fuzzy-AHP) to find out factors for the success of online P2P Lending service. In particular, this study uses Kano model to classify information system satisfaction factors and to calculate the satisfaction coefficient. The Kano model, however, has a drawback of evaluating single criterion. Therefore, we use multi-criteria decision-making technique such as Fuzzy-AHP to derive the relative importance of the factors. The analysis results show different results depending on the analysis technique. In the Kano model, most of the information system factors are a one-dimensional quality attribute. The satisfaction coefficient is highest for personalized service, followed by the responsiveness of service, ease of using a system, understanding of information, usefulness of information' reliability. The service reliability is the highest in dissatisfaction coefficient, followed by system security, service responsiveness, system stability, and personalized service. The results of the Fuzzy-AHP analysis shows that the usefulness of information quality, the personalization of service quality, and the security of system quality are the significant factors and the stability of system quality was a secondary factor.

• Knowledge Management Research
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• v.21 no.3
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• pp.229-247
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• 2020

In the remarkable growth of P2P financial platform in the field of knowledge management, only companies with big data and machine learning technologies are surviving in fierce competition. The ability to analyze borrowers' credit is most important, and platform companies are also recognizing this capability as the most important business asset, so they are building a credit evaluation system based on artificial intelligence. Nonetheless, online P2P platform providers that offer related services only act as intermediaries to apply for investors and borrowers, and all the risks associated with the investments are attributable to investors. For investors, the only way to verify the safety of investment products depends on the reputation of P2P companies from newspaper and online website. Time series information such as delinquency rate is not enough to evaluate the early stage of Korean P2P makers' credit analysis capability. This study examines the credit analysis procedure of P2P loan platform using artificial intelligence through the case analysis method for well known the top three companies that are focusing on the credit lending market and the kinds of information data to use. Through this, we will improve the understanding of credit analysis techniques through artificial intelligence, and try to examine limitations of credit analysis methods through artificial intelligence.

• Industry Promotion Research
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• v.7 no.4
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• pp.109-119
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• 2022

In recent years, China's Internet finance industry is hot. There is no doubt that Internet finance has been fully integrated into China, forming a new form of financing, and rapidly becoming a new channel for investment and financing in China, shouldering the responsibility of inclusive financing and building China's real economy. However, with investment, there are risks. Based on the panel data of China's Internet financial platform, this paper uses the random effect model to study the influencing factors of Internet financial risks, and draws three conclusions: (1) The user funds and platform funds of the financial platform will be managed separately by the bank, which can effectively reduce the risk of financial transactions on the Internet; (2) The risk of Internet financial transactions can be effectively reduced by avoiding the concentration of platform funds in the hands of a few borrowers through regulatory policies; (3) The liquidity control of funds effectively reduces the risk of Internet financial transactions. Based on the conclusions, we propose optimization strategies for regulatory policies to achieve the healthy and sustainable development of Internet finance.