The present study proposes a novel customer-to-virtual-product-to-customer (C2VP2C) mode of a loan default penalty model for Internet financial platforms (IFPs) in the Chinese market. The C2VP2C mode ...is developed based on the traditional peer-to-peer (P2P) business model and introduces IFP virtual products to risk control and loan matching. A loan default penalty model and a punishment mechanism of IFP borrowers in the C2VP2C mode have been developed. Firstly, the transaction mode and operational process of the C2VP2C mode of IFPs were established and three levels of loan matching space were constructed. The study established a penalty model for delinquent borrowers to assess their willingness to repay, and investigated the penalty intensity for defaults. The results show that a greater the penalty coefficient would result in more serious penalties, and with the delay of the repayment, the penalty coefficient showed less changes. The proposed method has important practical value and scientific significance for reducing the default rate of IFP borrowers and improving the loan repayment rate.
The paper proposes the farmers credit optimization decision model and applications based on common risk guarantee fund. By considering two conditions of with default risk and without default risk, ...the individual rationality of bank and farmer is designed, respectively, and the mathematical formulas for calculating the risk loss ratio of bank loans under the guarantee fund are established and discussed innovatively, respectively. A nonlinear optimal model based on risk compensation fund is established in the paper. By mathematical proof, the optimal bank credit decision mechanism is studied. By the analysis of numeric experiments of two cases of with default risk and without default risk, the expected income and invest income are varied by the changing of farmer project success probability and default probability, and the relationship of loan interest, farmer expected income and invest income is studied. The research has scientific guiding significance and practical application value for farmers' credit decision making.
•Based on WOE evidence weight, IV value, extreme learning machine model,etc., a credit quality rating method of borrower is proposed.•The credit quality scoring model of borrowers based on extreme ...learning machine is established.•The borrower's credit quality rating algorithm is designed. It applied to the sample data of 7706 borrowers in renren loan.
Through evaluating the weight of evidence method and calculating the information value (IV), this article proposes a method to evaluate the credit qualities of borrowers based on the extreme learning machine, the fuzzy c-means (FCM) algorithm, and the calculation of a confusion matrix. Through screening credit rating indexes, we established a credit scoring model of the borrower. In addition, we constructed formulas to determine the probability of default and default loss rate. The model also classifies the credit qualities of borrowers. In addition, we designed a selection algorithm for the borrower's credit quality rating index, and a borrower's credit quality rating algorithm. This paper collects sample data of 7706 borrowers of Renren loans from the Internet. The credit scores of the borrower, the default probability, and the default loss rate of each type of borrower are calculated, and the repayment status of borrowers are analyzed. We divided the borrowers into 7 grades and 5 grades by calculating a confusion matrix. The experimental results show that the overall accuracy of the credit scoring model is 98.5%, in which the accuracy for non-default samples is 98.9%, and the accuracy for default samples is 88.3%. The accuracy of the established credit quality rating model proved to be relatively high, and it can provide important reference values and scientific guidance for banks, financial institutions, and major financial platforms. It can also judge and predict default behavior.
A social reputation loss model for loss of social reputation upon borrower disconnection on internet financial platforms is proposed. Firstly, the characteristics of on-line social networks of the ...borrowers are analysed from P2P platform, Chat platforms, QQ platform, one-click help platform, etc. Secondly, the characteristics of offline social networks of the borrowers are analysed in terms of blood, geographical, business, academic, heart, and ethnic relationships. Thirdly, from the six main factors, such as amount of default funds, disconnection time point, status of joint guarantee performance, project success probability, the amount and severity of network punishment, the impacts on the social reputation of lost-link borrowers are evaluated. Then, by quantifying these six main influencing factors, we establish a social reputation loss model on the lost-linking borrowers in P2P platform, and explore the relationship between borrower disconnection time and social reputation loss. The work proves that the social reputation loss of borrowers gradually decreases with the delay of disconnection time and other mathematical propositions. Finally, the applications of the model are discussed. The impacts of dynamic changes of the project success probability, disconnection time and amount of network punishment on the social reputation loss of borrowers are analysed. Through this study, an innovative calculating method for the loss of social reputation of borrowers who are out of touch on internet financial platforms is given.
It’s the basic premise of promoting the healthy development of rural finance and strengthening macro-prudential supervision to measure the systemic risk of rural finance accurately. We establish the ...dynamic factor CAPM and make an all-round and multi-angle quantitative study on the systemic risk of rural finance in China by constructing Macro–micro index system and using machine learning to reduce the dimension of high-dimensional data. Our results show that the dynamic factor CAPM of using Macro–micro big data can evaluate systemic risk of rural finance more comprehensively and systematically, and machine learning performs well in processing high-dimensional data. In addition, China's rural financial systemic risk is stable compared with the Shanghai and Shenzhen main markets, but it is also susceptible to macro and micro influenced factors. Finally, it is pointed out that the early warning system of rural financial systemic risk could be constructed at macro and micro level, respectively.
This article innovatively builds the infrastructure of farmer credit rating index system into a multilevel unidirectional network structure. First, according to the logical structure of the ...three-level credit rating index system, a four-level unidirectional network is constructed, and the credit rating calculation formulas of all indexes at the four-level network are established. Furthermore, the special cases of the credit rating formula with the first- and second-level farmer credit rating index system are discussed. On this basis, it is extended to a credit rating index system with more than four levels, and the corresponding credit rating formula is established. Finally, the general formula of credit rating formula of the farmer credit rating index system from first level to multilevel is obtained. In order to solve the problem of farmers' credit rating, this paper also designs a linear segmentation classifier to classify the results of multilayer unidirectional network, establishes the rules of farmers' credit rating and the unidirectional network linear segmentation evaluation model of farmers' credit rating, and discusses the properties of bank credit based on farmers’ credit rating. Finally, the model established in this paper is applied to the credit rating of farmers in A County, Guangdong Province in China. When the credit rating of 160 farmers is carried out, the evaluation results are in line with the actual credit rating of farmers in A County, with an accuracy of 100%. This research has the maneuverability to carry on the scientific credit rating to the countryside. This study has important method guidance and operability for rural credit rating.
The paper designs and invents internet of things platform of One-Key for Help APP based on the mobile intelligent terminal (MIT) for the risk response of one-key for help, information for help, SMS ...for assistance, phone for support, map phone for advantage, voice message for help and video for aid. For Government Emergency Rescue Department (GERD), the platform is preset with China’s 110 police system, 119 fire alarm system, 120 emergency center system, 122 traffic incident system, as well as the government emergency rescue department(GERD), social public welfare rescue organizations(SPWRO), families and friends’ call for help, and is designed emergency call for help and rescue methods according to the regional scope such as nearby people, communities, cities, provinces and the whole country, to realize the call for help from individual to government, groups, kinship, region, etc.. This paper also defines single-risk identification, multiple risk environment and designs the risk identification & one-key for help algorithm. The One-Key for Help APP of IOT platform is applied for an actual case The APP platform can be used in several country or region and any city or village around the world. The One-Key for Help APP platform can be used in any country or region and any city or village in the world. A person only needs to register the APP and becomes used no matter what individual is in, wherever there is a mobile Internet, the concerned individual can use the One-Key for Help APP platform to send out the emergency information to their respective family, friends or GERD when they are in distress at any point of time. The APP has advanced functions and simple operation, which has scientific guidance and practical value for preventing all kinds of social emergencies.
In this paper we will show that noise can make a given system whose solutions grow exponentially become a new system whose solutions will grow at most polynomially. On the other hand, we will also ...show that noise can make a given system whose solutions are bounded become a new system whose solutions will grow exponentially. In other words, we reveal that the noise can suppress or expresses exponential growth.
Positive results are derived concerning the long time dynamics of numerical simulations of stochastic differential equation systems with Markovian switching. Euler–Maruyama discretizations are shown ...to capture almost sure and moment exponential stability for all sufficiently small timesteps under appropriate conditions.
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