Should the Advanced Measurement Approach for Operational Risk be Discarded? Evidence from the Chinese Banking Industry

Zhu, Xiaoqian; Li, Jianping; Wu, Dengsheng

doi:10.1142/s0219091519500073

Cited by 7 publications

(5 citation statements)

References 28 publications

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“…As the core technology of self-organizing data mining, GMDH (Group Method of Data Handling) mainly includes the following four models: parametric GMDH input and output model, parametric GMDH autoregressive model, nonparametric similar synthesis model, and nonparametric fuzzy rule induction model. Among them, the parameter GMDH input and output model can automatically select the independent variables that enter the model and perform hierarchical screening through optimal criteria, so it is often used for the extraction and output of key variables in complex economic systems [7]. e algorithm can analyze and process the relationship between the input variables of the system, use self-organizing data mining technology to objectively and directly generate the optimal fuzzy rules from all possible fuzzy rules of the system and directly and effectively describe the fuzzy system qualitatively and quantitatively, So as to establish a predictive model.…”

Section: E-banking Risk Measurement and Early Warning Index Selectionmentioning

confidence: 99%

Research on Risk Measurement and Early Warning of Electronic Banking Business Based on GMDH Algorithm

Zeng

2021

Security and Communication Networks

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In order to deal with the problems of traditional e-banking risk measurement and early warning methods, such as low accuracy of e-banking risk measurement and longer early warning time, an e-banking risk measurement and early warning method based on the GMDH algorithm is proposed. This scheme mines the e-banking risk measurement and early warning indicators by the GMDH algorithm, and it will input the influencing factors and risk factors as independent variables into the GMDH modeling network and then input the e-banking business growth rate as the dependent variable into the GMDH modeling network which is standardized by the normative method of processing the e-banking business risk measurement and early warning index data. According to the processing results, it calculates the weight of the measurement and early warning index by the entropy method, and it constructs the e-banking risk measurement model with the genetic algorithm which can help to calculate the optimal solution of the parameters, formulate the risk measurement interval, and determine the risk in order to realize the risk warning of electronic banking business. The simulation results show that the proposed method has a higher accuracy of e-banking risk measurement and a shorter warning time.

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Section: E-banking Risk Measurement and Early Warning Index Selectionmentioning

confidence: 99%

Research on Risk Measurement and Early Warning of Electronic Banking Business Based on GMDH Algorithm

Zeng

2021

Security and Communication Networks

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“…This adds to the security of operational risk estimates. The results obtained in the AMA method tend to be smaller than the BIA method (Zhu et al 2019). Smaller yields can be leveraged for the minimum optimal backup value.…”

Section: Discussionmentioning

confidence: 91%

Estimation of Maximum Potential Losses for Digital Banking Transaction Risks Using the Extreme Value-at-Risks Method

Saputra

Chaerani

2022

Risks

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The application of industry 4.0 in banking presents many challenges, with several operational risks related to downtime and timeout services due to system failures. One of the operational risk management steps is to estimate the value of the maximum potential losses. The purpose of this study is to estimate the maximum potential losses for digital banking transaction risks. The method used for estimating risks is the EVaR method. There are several steps in this study. The first step is to resample the data using MEBoot. This process is a simulation of the operational risk loss data of digital banking. Next, the threshold value is determined to obtain the extreme data value. Then, a Kolmogorov–Smirnov test is conducted to fit the data with the GPD. Afterward, the GPD parameter is estimated. Then, EVaR is calculated using a portfolio approach to obtain a combination of risk values as maximum potential losses. The analysis results show that the maximum potential loss is IDR144,357,528,750.94. The research results imply that the banks need to pay attention to the maximum potential losses of digital financial transactions as a reference for risk management. Therefore, banks can anticipate the adequacy of reserve funds for these potential risks.

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“…The tourism industry is increasingly valued for its contributions to economic growth, employment, poverty reduction, export earnings, consumer demand, capital accumulation, tax revenues, fostering economic diversification, and a more service-oriented economy that 411 helps stimulate urban development, oblast and cultural activities are in decline [7,24] (Endo, 2006;UNCTAD, 2007).…”

Section: Literature Reviewmentioning

confidence: 99%

Financial and Credit Support of Innovative Developing Activities of Enterprises in the Sphere of Tourism Services

Karimova

2023

EIT

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Currently, tourism is one of the rapidly developing areas of activity, however, according to the results of the study, most enterprises feel a lack of financial resources. In this connection, this article discusses issues related to the lack of financial resources at enterprises in the field of tourism services, as well as factors that are an obstacle to lending to subjects of this industry. Conclusions are drawn and proposals are given that contribute to the further development of subjects with the help of financial and credit support.

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Should the Advanced Measurement Approach for Operational Risk be Discarded? Evidence from the Chinese Banking Industry

Cited by 7 publications

References 28 publications

Research on Risk Measurement and Early Warning of Electronic Banking Business Based on GMDH Algorithm

Research on Risk Measurement and Early Warning of Electronic Banking Business Based on GMDH Algorithm

Estimation of Maximum Potential Losses for Digital Banking Transaction Risks Using the Extreme Value-at-Risks Method

Financial and Credit Support of Innovative Developing Activities of Enterprises in the Sphere of Tourism Services

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