Open Access
ARTICLE
Big Data Audit of Banks Based on Fuzzy Set Theory to Evaluate Risk Level
Yilin Bi1, Yuxin Ouyang1, Guang Sun1, Peng Guo1, 2, Jianjun Zhang3, Yijun Ai1, *
1 Hunan University of Finance and Economics, Changsha, 410205, China.
2 University Malaysia Sabah, Sabah, 88400, Malaysia.
3 Hunan Normal University, Changsha, 410081, China.
* Corresponding Author: Yijun Ai. Email: .
Journal on Big Data 2020, 2(1), 9-18. https://doi.org/10.32604/jbd.2020.01002
Received 05 January 2020; Accepted 13 May 2020; Issue published 07 September 2020
Abstract
The arrival of big data era has brought new opportunities and challenges to the
development of various industries in China. The explosive growth of commercial bank data
has brought great pressure on internal audit. The key audit of key products limited to key
business areas can no longer meet the needs. It is difficult to find abnormal and exceptional
risks only by sampling analysis and static analysis. Exploring the organic integration and
business processing methods between big data and bank internal audit, Internal audit work
can protect the stable and sustainable development of banks under the new situation.
Therefore, based on fuzzy set theory, this paper determines the membership degree of audit
data through membership function, and judges the risk level of audit data, and builds a risk
level evaluation system. The main features of this paper are as follows. First, it analyzes the
necessity of transformation of the bank auditing in the big data environment. The second is
to combine the determination of the membership function in the fuzzy set theory with the
bank audit analysis, and use the model to calculate the corresponding parameters, thus
establishing a risk level assessment system. The third is to propose audit risk assessment
recommendations, hoping to help bank audit risk management in the big data environment.
There are some shortcomings in this paper. First, the amount of data acquired is not large
enough. Second, due to the lack of author’ knowledge, there are still some deficiencies in
the analysis of audit risk of commercial banks.
Keywords
Cite This Article
Y. Bi, Y. Ouyang, G. Sun, P. Guo, J. Zhang
et al., "Big data audit of banks based on fuzzy set theory to evaluate risk level,"
Journal on Big Data, vol. 2, no.1, pp. 9–18, 2020.