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Zhou, H., Sun, G., Fu, S., Liu, J., Zhou, X., & Zhou, J. (2019). A Big Data Mining Approach of PSO-Based BP Neural Network for Financial Risk Management with IoT. Institute of Electrical and Electronics Engineers, 7, 54035-154043.
https://doi.org/10.1109/ACCESS.2019.2948949

has been cited by the following article:

• TITLE: Research on Network Lending Risk Analysis Based on Platform Efficiency

  AUTHORS: Dongmei Li, Jin Xu, Liping Li

  KEYWORDS: Inclusive Finance, DEA, Efficiency, Risk Analysis

  JOURNAL NAME: Journal of Financial Risk Management, Vol.10 No.4, December 2, 2021

  ABSTRACT: Optimizing the financial risk control mechanism is very important for small and medium-sized enterprises. It is an important foundation for lending companies to continue to operate steadily and ensure the safety of credit assets. Only by optimizing the financial risk control mechanism can small and medium-sized enterprises develop better and healthily. This study designs the data envelopment analysis (DEA) model (CCR and BCC) to evaluate the relative credit risk of the enterprise. According to the selected core indicators, comprehensive technical efficiency, pure technical efficiency and scale efficiency of each lending platform are calculated. In order to further explore the efficiency status of each lending platform and the reasons for its inefficiency, the efficiency pedigree was drawn according to the pure technical efficiency value and scale efficiency value of the platform. The main reason for the low efficiency of online loan platform was the low management level. Therefore, we need to improve the comprehensive management level of the platform, and strengthen the risk management control to improve the operation efficiency of the online loan platform. Finally the related policy proposal was put forward.