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Green credit is an important manifestation of commercial banks' environmental responsibility, but few studies have examined the impact of green credit policies on the financial performance of commercial banks. Based on the panel data of 62 commercial banks in China from 2013 to 2020, this paper investigates the changes in financial performance due to the implementation of green credit policies in 2016 using the difference-in-differences (DID) method and explores the mediating mechanism of green credit affecting commercial banks' profit. The sample was divided into a treatment and a control group. The treatment group disclosed total green credit data during the sample period, while the control group did not. The findings of this paper are as follows: (1) the implementation of the green credit policy increases the profits of commercial banks. (2) The green credit policy improves the profits of commercial banks by increasing their noninterest income and reducing their nonperforming loan ratios. (3) The green credit policy does not improve commercial banks' profit by reducing their cost-to-income ratios. (4) The implementation of the green credit policy significantly improves the profits of banks with low (vs. high) nonperforming loan ratios. (5) Compared to large national banks, regional urban and agricultural commercial banks' profits improve more significantly after executing the green credit policy. The research contribution of this paper provides a quantitative basis for Chinese commercial banks to improve their financial performance through the implementation of green credit in recent years and for the government to further improve green credit policies to motivate banks to implement green credit and achieve sustainable development. Then, we further discuss the implications for the prominent theoretical and managerial policies, study's limitations, and future research directions. [ABSTRACT FROM AUTHOR]

The main path of development credit funds in rural poverty alleviation in Y province is crucial. This paper studies the rural poverty alleviation work in extreme poverty areas in Yunnan and puts forward targeted and instructive policy suggestions for specific difficult areas. Research the relationship between credit resource allocation and rural poverty alleviation. The existing research is mainly based on the relationship between financial development and economic growth, income growth, income distribution, and, on the surface, the relationship between the scale of financial development and the efficiency of financial development and other indicators. The purpose is to put forward targeted measures and suggestions on the basis of theoretical research and model analysis to help the Yunnan banking industry support poverty alleviation. The results of the study show that there is a causal relationship between agriculture-related loans. [ABSTRACT FROM AUTHOR]

Credit problems are the main bottleneck in the development of e-commerce. Both the time and degree of e-commerce credit control directly affect its economic benefits. From the perspective of the criticality of complex systems, this paper explores the control node of e-commerce credit behaviour. Implementing control in this node can not only ensure the stable development of the credit network but also optimise the control cost. This paper constructs a credit behaviour model for the four regulatory behaviours of the transaction subject, analyses the evolution law of the credit network, and determines the critical state of the network. Finally, the paper's empirical analysis and simulation experiments prove that when the false information in the credit network in the empirical data is 32%, the implementation of credit control has an efficient control effect. Nevertheless, 32% is not a universal result; the specific critical point value needs to be recalculated according to the theoretical derivation of the critical point combined with the actual network. These research results can help regulators obtain the highest regulatory return with the lowest regulatory investment. [ABSTRACT FROM AUTHOR]

In recent years, the new agricultural business entities have grown rapidly in all parts of the country and have become an effective carrier to achieve the basic stability of China's rural family operation system and moderate-scale agricultural operation. However, the systemic defects of rural financial market and the credit rationing of formal financial institutions make the capital needs of rural areas unsatisfied for a long time. Financial demand determines the direction of supply reform. Therefore, in order to improve rural financial supply and promote the transformation and development of agricultural economy under the current situation, it is necessary to effectively understand the formal credit demand and the impact factors of accessibility of the new agricultural business entities, which represents the direction of China's agricultural development in the future. Based on back propagation (BP) neural network, this paper constructs the farmers' formal credit availability prediction model and studies the formal credit demand and the impact factors of the availability of new agricultural business entities. The experimental results show that the farmers' formal credit availability prediction model has good performance in prediction accuracy, prediction time, and mean squared error. [ABSTRACT FROM AUTHOR]

In modern market economy, corporate financial frauds emerge one after another, which have a huge impact on the stock market and triggered an unprecedented credit crisis. Therefore, it is particularly important to identify financial frauds. Improving the efficiency, accuracy, and coverage of fraud identification in financial reports through digital and intelligent means is one of the important links to improve credit risk control of securities companies and also for securities companies to accurately price related financial products of target companies. Traditional recognition methods based on artificial rules can cover relatively limited indicators; rule parameters are set randomly. Besides, it is difficult to make rules based on high-dimension indicators and to dig the hidden deep relationships between indicators. This paper summarizes the relevant indicators of financial fraud identification from the perspective of financial and nonfinancial characteristics. Then, the identification and early warning of financial fraud risk based on bidirectional long-short term memory model are proposed. This method uses the idea of ensemble learning, weights the probability of financial key indicators, and uses the optimal transfer probability to solve the financial fraud risk results. The results show that the industry-specific modeling can significantly improve the accuracy of the financial fraud identification model and it also can effectively help the government regulatory departments, investors, and audit departments to correctly identify the financial fraud of listed companies. [ABSTRACT FROM AUTHOR]

Green innovation is an important tool in environmental management, and green finance can provide financial support for green innovation. The greening of the financial system has attracted attention. In order to promote the development of green finance, the Chinese government has implemented policy intervention in the financial market. Green finance reform differs from green credit policy, as it is a comprehensive green finance policy aimed at the financial system. In order to study the policy effects of green finance reform on corporate green innovation, this paper applies the green finance reform that the Chinese government introduced in 2017 as a quasi-natural experiment and implements the difference-in-difference (DID) method to investigate the impact of green finance reform on corporate green innovation. We found that green finance reform promotes corporate green innovation. The result remained valid after a series of robustness tests and is more prominent for state-owned enterprises (SOEs) and large enterprises. Furthermore, we examined the impact of green finance reform on different types of innovation, finding that it had a positive effect on green invention innovation and green utility model innovation. Mechanism tests showed that green finance reform promotes corporate green innovation by alleviating financial constraints. [ABSTRACT FROM AUTHOR]

Financing guarantee is an important means and key link to solve the financing difficulties of small- and medium-size enterprises (SMEs). However, while financial guarantees alleviate the financing difficulties of SMEs, the complex guarantee relationships also constitute a new channel for credit risk contagion in the financial guarantee network. In this paper, we construct a model of credit risk contagion process of guarantee network based on SEIR and analyse the equilibrium point and stability of the model. Then, we find the threshold value of risk contagion and further simulate the SEIR model dynamically to analyse the influence of each parameter of the model. The results show that the risk of the financing guarantee network begins to be widely contagious only when risk contagion threshold is greater than 1, and the conversion rate of exposed enterprises, removal rate of infected enterprises, nodal enterprises degree, and risk contagion rate have significant effects on the changes of individual density of susceptible, exposed, infected, and recovered enterprises. Combining the above findings, it is of great theoretical and practical significance to propose relevant countermeasures for credit risk control of financial guarantee network. [ABSTRACT FROM AUTHOR]

In this highly volatile, uncertain, complex, and ambiguous (VUCA) environment, a fuzzy inventory optimization problem is a hot topic that received the most attention from both academicians and practitioners. In this paper, the authors have studied the integrated inventory problems under trade credit in fuzzy environments, where the demand rate and deterioration rate are taken here as triangular fuzzy numbers. Accordingly, three types of fuzzy programming models as fuzzy expected cost minimization model, fuzzy α-cost minimization model, and credibility maximization model are built according to different management goals. Since the problem is shown to be NP-hard, this research focuses on proposing a hybrid intelligent algorithm by integrating fuzzy simulation, neural network, and genetic algorithm for solving these models. Then, some numerical examples are presented to illustrate the benefits of the models and evaluate the efficiency of the algorithms. The computational experiments show that the trade credit strategy has a positive impact on improving the supply chain's performance and reducing its total cost. In addition, the maximum relative error of the objective values is less than 1%, which implies that the hybrid intelligent algorithm is robust to the parameter settings and effective in solving our models. Finally, the practical implications are discussed and useful managerial insights are given. [ABSTRACT FROM AUTHOR]

It is essential to solve the problem of information asymmetry in bank housing credit management, thus reducing bank operating costs and credit risk. Therefore, the present work constructs a bank housing credit blockchain alliance system based on the technical characteristics of blockchain to strengthen bank housing credit risk control. First, according to blockchain's elements and system architecture, the application of blockchain to bank housing credit business is analyzed. On this basis, the bank housing credit risk control strategy is proposed. Finally, the mathematical model is used to investigate residents' household consumption to explore the impact of housing credit on the household consumption plan of residents. The results show that when the educational level of the head of household is illiterate or semi-illiterate, the coefficients of participation credit (PC), nonparticipation credit (NPC), and total samples (TSs) of total household consumption are −0.064, 0.067, and 0.174, respectively; when the educational level of the head of household is primary school or junior middle school, the coefficients of PC, NPC, and TS of total household consumption are -0.026, 0.017, and 0.105, respectively; when the educational level of the head of household is high school or above, the coefficients of PC, NPC, and TS of total household consumption are 0.084, 0.073, and 0.064, respectively. The results indicate that the education level of the head of household plays a crucial role in the family consumption plan. Those with a high educational level will compromise on the best consumption decision after constantly weighing the consumption motivation and consumption thinking after obtaining the credit funds. The content reported here is vitally significant in guiding households to clarify the proportion of credit fund distribution and understand their consumption tendency. [ABSTRACT FROM AUTHOR]

Network lending, an innovative financial lending product, is separated from traditional financial media and implemented on the Internet platform. We study the credit risk prediction of online loan based on risk efficiency analysis. Moreover, we put forward the concept of borrower risk efficiency and apply it to risk prediction. The main task of this study is to establish risk efficiency characteristics on the basis of referring to various risk characteristics and carry out risk prediction after passing the screening of a series of features. The framework is realized by combining logistic regression and slack-based measure (SBM), and feature selection and verification are carried out through machine learning and statistics. Firstly, the efficiency risk characteristics are extracted and the risk efficiency is calculated by MaxDEA. Secondly, the features are screened and verified by Python. Then, the efficiency value obtained by SBM method is used as a new index for the training and testing of logistic model together with the initial related indexes. Moreover, in order to prove the effectiveness of the proposed credit risk prediction control scheme based on risk efficiency, the research compares the prediction before and after adding the risk efficiency feature. The simulation results demonstrated that the logistic-SBM model is more suitable for credit risk prediction than the commonly used logistic method, which realized the efficient prediction of credit risk based on the logistic-SBM model. Finally, some suggestions are put forward to China's regulatory authorities and the platform itself to control the credit risk of Internet lending industry. [ABSTRACT FROM AUTHOR]

For the secondary supply chain composed of a supplier with sufficient funds and a retailer with limited funds and risk aversion, to enhance the supply chain stability and comprehensively improve benefits, the supply chain members may choose to implement a supply chain's coordination strategy. Thus, we study the following supply chain coordination problems, i.e., the supplier provides a trade credit policy and signs a buyback contract for the surplus products with the retailer. For this, based on maximizing the benefits of supply chain members, the supply chain coordination model has been established. By analyzing two participants' benefit, the supply chain's optimum coordination mechanism is obtained. The theoretical results are verified by numerical experiments. [ABSTRACT FROM AUTHOR]