Research on the Construction of Accounting Informatics System and Risk Assessment Method in Big Data’s Era
The traditional financial informatics administration system risk assessment method in the evaluation of system risk can deal with less data throughput, and the system risk assessment effect is not good, so the study of the financial informatics administration system of the risk assessment method und...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2022/7673807 |
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| _version_ | 1850178428769140736 |
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| author | Yining Wang Tian Wang Rui Zhao Xi Lun |
| author_facet | Yining Wang Tian Wang Rui Zhao Xi Lun |
| author_sort | Yining Wang |
| collection | DOAJ |
| description | The traditional financial informatics administration system risk assessment method in the evaluation of system risk can deal with less data throughput, and the system risk assessment effect is not good, so the study of the financial informatics administration system of the risk assessment method under the background of big data is a necessity. The method sets logical nodes according to system modules and builds risk estimation models by finding logical relationships between data. Based on the big data background, according to the utility theory and the risk preference function estimation, choose the big data batch calculation and streaming calculation methods to calculate the system programme risk index and financial data faithless risk index. According to the risk residual value, the probability of a system function failure in the main module and submodule of the system is adjusted, and the risk level is defined by the exponential function to realize the system risk estimation under the background of big data. Experimental results show that compared with the two traditional system risk estimation methods, the proposed method has a larger data throughput and a wider range of risk indicators. It can be seen that the proposed method meets the risk estimation requirements of the enterprise financial informatics administration system. |
| format | Article |
| id | doaj-art-bbee5512e24a4124976b33301896d48c |
| institution | OA Journals |
| issn | 1607-887X |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-bbee5512e24a4124976b33301896d48c2025-08-20T02:18:43ZengWileyDiscrete Dynamics in Nature and Society1607-887X2022-01-01202210.1155/2022/7673807Research on the Construction of Accounting Informatics System and Risk Assessment Method in Big Data’s EraYining Wang0Tian Wang1Rui Zhao2Xi Lun3Qinhuangdao Vocational and Technical CollegeQinhuangdao Vocational and Technical CollegeQinhuangdao Vocational and Technical CollegeQinhuangdao Vocational and Technical CollegeThe traditional financial informatics administration system risk assessment method in the evaluation of system risk can deal with less data throughput, and the system risk assessment effect is not good, so the study of the financial informatics administration system of the risk assessment method under the background of big data is a necessity. The method sets logical nodes according to system modules and builds risk estimation models by finding logical relationships between data. Based on the big data background, according to the utility theory and the risk preference function estimation, choose the big data batch calculation and streaming calculation methods to calculate the system programme risk index and financial data faithless risk index. According to the risk residual value, the probability of a system function failure in the main module and submodule of the system is adjusted, and the risk level is defined by the exponential function to realize the system risk estimation under the background of big data. Experimental results show that compared with the two traditional system risk estimation methods, the proposed method has a larger data throughput and a wider range of risk indicators. It can be seen that the proposed method meets the risk estimation requirements of the enterprise financial informatics administration system.http://dx.doi.org/10.1155/2022/7673807 |
| spellingShingle | Yining Wang Tian Wang Rui Zhao Xi Lun Research on the Construction of Accounting Informatics System and Risk Assessment Method in Big Data’s Era Discrete Dynamics in Nature and Society |
| title | Research on the Construction of Accounting Informatics System and Risk Assessment Method in Big Data’s Era |
| title_full | Research on the Construction of Accounting Informatics System and Risk Assessment Method in Big Data’s Era |
| title_fullStr | Research on the Construction of Accounting Informatics System and Risk Assessment Method in Big Data’s Era |
| title_full_unstemmed | Research on the Construction of Accounting Informatics System and Risk Assessment Method in Big Data’s Era |
| title_short | Research on the Construction of Accounting Informatics System and Risk Assessment Method in Big Data’s Era |
| title_sort | research on the construction of accounting informatics system and risk assessment method in big data s era |
| url | http://dx.doi.org/10.1155/2022/7673807 |
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