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With the digital transformation of commercial banks and the online transfer of credit transactions, the relationship between credit subjects tends to be complex, and personal credit risk management is facing challenges. The contagiousness of personal credit risk and the relationship among credit subjects are poorly understood in the field of credit risk management. This study used an SEIR infectious disease model to reveal the mode and structure of associated credit risk based on the theory and method of complex networks, and it explored the status and influencing factors of associated credit risk in a scale-free network using simulation experiments. The research findings indicate that the coefficient of latency, the coefficient of risk contagion, the coefficient of direct recovery, the coefficient of latent transformation, the coefficient of immune recovery, and the structure of the association network have a significant influence on the scale and threshold of associated credit risk. This study reveals comprehensive reasons for the outbreak of credit risk clusters and provides a new perspective for financial institutions, such as commercial banks, to help them manage credit risk. [ABSTRACT FROM AUTHOR]

The low-cost, highly efficient online finance credit provides underfunded individuals and small and medium enterprises (SMEs) with an indispensable credit channel. Most of the previous studies focus on the client crediting and screening of online finance. Few have studied the risk rating under a complete credit risk management system. This paper introduces the improved neural network technology to the credit risk rating of online finance. Firstly, the study period was divided into the early phase and late phase after the launch of an online finance credit product. In the early phase, there are few manually labeled samples and many unlabeled samples. Therefore, a cold start method was designed for the credit risk rating of online finance, and the similarity and abnormality of credit default were calculated. In the late phase, there are few unlabeled samples. Hence, the backpropagation neural network (BPNN) was improved for online finance credit risk rating. Our strategy was proved valid through experiments. [ABSTRACT FROM AUTHOR]

Most project operations management belongs to the type of public-private partnership (PPP), which is usually dynamic. This paper aims to propose a method for optimizing the price of credit default swaps (CDS) for the dynamic PPP system. This study investigates the credit risk measurement of PPP project financing and the pricing of risk mitigation instruments which are widely used in the case of immature markets in the early stage of China’s PPP development. Based on the credit risk measurement theory of the corporate and debt ratings, this paper considers the differences in various credit enhancement methods in the equity-like debt agreement and determines the credit rating of the equity-like debt in PPP projects. Some optimization methods are also proposed to derive the probability of default, so as to determine the price of the credit risk mitigation instrument of CDS which is based on the equity-like debt. [ABSTRACT FROM AUTHOR]

Experiences manifest the importance of comovement and communicable characters among the risks of financial assets. Therefore, the portfolio view considering dependence relationship among credit entities is at the heart of risk measurement. This paper introduces a mixed Poisson model assuming default probabilities of obligors depending on a set of common economic factors to construct the dependence structure of obligors. Further, we apply mixed Poisson model into an empirical study with data of four industry portfolios in the financial market of China. In the process of model construction, the classical structural approach and option pricing formula contribute to estimate dynamic default probabilities of single obligor, which helps to obtain the dynamic Poisson intensities under the model assumption. Finally, given the values of coefficients in this model calculated by a nonlinear estimation, Monte Carlo technique simulates the progress of loss occurrence. Relationship between default probability and loss level reflected through the MC simulation has practical features. This study illustrates the practical value and effectiveness of mixed Poisson model in risk measurement for credit portfolio. [ABSTRACT FROM AUTHOR]