The Effects of the Sharing Economy: How Does Internet Finance Influence Commercial Bank Risk Preferences?

Qiao, Haishu; Chen, Meilin; Xia, Yue

doi:10.1080/1540496x.2018.1481045

Cited by 22 publications

(15 citation statements)

References 30 publications

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“…In addition to the regression and classification model of overdue loans, some domestic scholars use other perspectives to study overdue risks. Guo and Shen [20,21] combined with game theory and information economics methods such as refined Bayesian equilibrium, the moral hazard supervision model is established to measure and control default risk, and the optimal probability is deduced by using optimization mathematical method [4,22]. In view of the overdue risk of the four major characteristic factors (borrower characteristics, property characteristics, loan characteristics, and regional characteristics) affecting the construction of housing mortgage loan, Wang et al [23] adopted logistic regression, factor analysis and discriminant analysis to analyze the overdue risk, and successfully applied the theoretical results to the prediction of financial risk.…”

Section: Related Workmentioning

confidence: 99%

Research on Risk Prediction Model of Internet Finance Based on Cloud Computing

Liu

2022

Journal of Mathematics

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With the rapid development of the Internet, the traditional Internet financial risk prediction methods can no longer meet the needs of individuals and enterprises, so the concept of cloud computing arises at the historic moment. Cloud computing has subverted the traditional financial risk prediction method and has been widely studied and applied for its distributed, dynamic and autonomous characteristics. How to efficiently and reasonably schedule the resources of cloud data center and improve the accuracy of financial risk prediction is the focus of current research. How to quantify financial risk and financial risk early warning is one of the urgent problems to be solved. Under the framework of cloud computing, this paper combines the feature extraction and data weighting to study the user’s basic attribute data and a large number of downloaded APP types. After that, linear regression with penalty is used to construct the prediction model to improve insolvency. The accuracy of customer default judgment can realize local optimization, so as to improve the prediction and control of hidden risks of customer commercial bank loans and greatly reduce the default risk of bank loans.

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Section: Related Workmentioning

confidence: 99%

Research on Risk Prediction Model of Internet Finance Based on Cloud Computing

Liu

2022

Journal of Mathematics

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“…In an article published in a financial and accounting research journal, the researchers proposed that the advantages of big data can be used to transform the financial information system and improve the level of financial informatization [17]. Relevant scholars have further studied the transformation direction of enterprise group financial management in the era of big data, starting from analyzing the financial problems that appear in the continuous development of enterprise groups, and put forward the conclusion that making full use of the advantages brought about by big data can help enterprise groups successfully achieve financial management [18].…”

Section: Related Workmentioning

confidence: 99%

Organizational Construction of Financial Management Application Platform Based on Commercial Random Matrix

Tao¹,

Wang

Yang

2022

Mathematical Problems in Engineering

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As one of the basic tools of statistical analysis, random matrix theory builds a bridge for the study of microscopic and macroscopic properties of complex networks. The eigenvalues of the adjacency matrix of the complex network after mapping correspond to the energy spectrum in the random matrix theory, so the characteristics of the complex network are concentrated in the volatility of the eigenvalue sequence. The eigenvalues of complex networks are analyzed through random matrix theory to find the relationship between their structure and properties. This paper discusses the design and realization of the comprehensive application platform of group enterprise financial management. Based on the current situation of the development of financial management software in domestic and foreign group companies, the thesis gives the goals and tasks of the platform research and design. The enterprise financial management platform has made a business and technical architecture design and has made an in-depth analysis and design of modules such as fund management, budget management, statement management, and accounting management. This paper finds that the critical point threshold makes the results of network community division below this threshold poor, and the results above this threshold are good. Furthermore, the tipping point threshold for the NYSE network is significantly lower than that of the CSM network. This paper further analyzes the dynamic cross-correlation matrix and examines the time-dependent changes in the number of outliers, the number of communities, the degree of network modularity, and the degree of decentralization of industry composition under the condition of two market critical point thresholds. From the magnitude of fluctuation, it is found that the NYSE network is much more stable than the CSM network, which may also be related to the basic characteristics of the two markets, because the capital chain relationship is much more stable than the supply chain relationship.

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“…These related dimensions focus on the differences between these platforms, not their similarities – the antithesis of a unifying theory. The diverse forms of alternative exchange and consumption strategies include collaborative consumption (Botsman & Rogers, 2011), sharing (Belk, 2014), swaps (Albinsson & Yasanthi Perera, 2012), barter (Birch & Liesch, 1997), online and offline markets (Albinsson & Yasanthi Perera, 2012), P2P rentals (Albinsson & Yasanthi Perera, 2012), P2P finance and crowdfunding (Bachmann et al, 2011; Qiao et al, 2018), member‐based sharing/rentals (Bardhi & Eckhardt, 2012), giveaways (Albinsson & Yasanthi Perera, 2012; McKenzie, 2015) and pay‐it‐forward networks (Chiang & Takahashi, 2011). Based on this context we propose the following research question:…”

Section: Introductionmentioning

confidence: 99%

Communities of benefit exchange – A new taxonomy of alternative consumption practices

Bajaj

Ogden

Steel

et al. 2021

J of Consumer Behaviour

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The consumer landscape is changing, with traditional behaviours, channels and models of commerce evolving rapidly. This has resulted in an increasingly disruptive landscape for businesses. One example is the growth of communities of consumers who collaborate through diverse and non‐conventional channels (often focused on specific needs or interests) to engage in information seeking and giving, socialisation, resource sharing and trade. This emerging field of research presents challenges due to the diverse and fragmented theory base available to explore, explain and analyse the phenomena we position in alternative consumption literature. In this paper, we address this challenge in the form of a Communities of Benefit Exchange (CoBE) taxonomy of exchange dimensions detailing purpose, nature of gain and benefit, channel and level of interaction and entity structure evident for consumers who participate in this practice.

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The Effects of the Sharing Economy: How Does Internet Finance Influence Commercial Bank Risk Preferences?

Cited by 22 publications

References 30 publications

Research on Risk Prediction Model of Internet Finance Based on Cloud Computing

Research on Risk Prediction Model of Internet Finance Based on Cloud Computing

Organizational Construction of Financial Management Application Platform Based on Commercial Random Matrix

Communities of benefit exchange – A new taxonomy of alternative consumption practices

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