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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]

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 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]

It has great significance for the healthy development of credit industry to control the credit default risk by using the information technology. For some traditional research about the credit default prediction model, more attention is paid to the model accuracy, while the business characteristics of the credit risk prevention are easy to be ignored. Meanwhile, to reduce the complicity of the model, the data features need be extracted manually, which will decrease the high-dimensional correlation among the analyzing data and then result in the low prediction performance of the model. So, in the paper, the CNN (convolutional neural network) is used to establish a personal credit default prediction model, and both ACC (accuracy) and AUC (the area under the ROC curve) are taken as the performance evaluation index of the model. Experimental results show the model ACC (accuracy) is above 95% and AUC (the area under the ROC curve) is above 99%, and the model performance is much better than the classical algorithm including the SVM (support vector machine), Bayes, and RF (random forest). [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]

This paper studies the behavior of commercial guarantee company in the game theory framework. Different payoff structures with guarantee company behavior for banks, borrowers, and the guarantors are formed in the presence of credit rationing. We derived and explained the surviving rule of different types of guarantee companies, and we further conclude the condition in which guarantee companies are likely to be involved in a moral hazard problem. We conclude that, in the presence of regulatory arbitrage opportunity, the guarantee company has incentive to switch its role from bank agent to the borrower, being a second-hand lender. When the macroeconomic risk is high, the switching of this role will transfer the risk back to the banks. [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]