Evaluation of Financial Intelligent Systems Digitalization Maturity of Small and Medium-sized Enterprises Based on Fuzzy Logic Algorithm

Authors

  • Tong Tian KPMG Huazhen LLP Shenyang Branch, Shenyang 110000,China

Abstract

In response to the problem of having inadequate and inaccurate methods of evaluating the digital maturity evaluation of small and medium-sized enterprises (SMEs), this study designed a financial digital maturity evaluation method based on the size of enterprises in a provincial region of China. By analyzing the current status of financial digitization in SMEs, evaluation indicators were determined, and a digital maturity evaluation model was constructed using fuzzy logic algorithms and analytic hierarchy process. Verification showed that the Cronbach’s Alpha coefficient of the established evaluation model was 0.87, and the consistency ratio of the judgment matrix was 0.030. The average scores for digital management, input, output, and
external digital environment of the 25 selected SMEs were 2.8008, 2.0588, 1.4964, and 1.7568, respectively. The average score for overall financial digital maturity was 1.6768, which is a relatively weak level. The results indicate that the financial digitalization maturity level of SMEs in the study area is relatively low. When undertaking digital transformation, it is necessary to strengthen the application of enterprise digital technology, optimize the digital business capabilities of enterprise finance, and promote the digital transformation of enterprise finance. The use of fuzzy logic algorithms to evaluate the digital maturity of enterprise finance can improve the efficiency and accuracy of evaluation and has positive practical significance in the field of evaluation.

Keywords: Fuzzy logic algorithm; AHP; SMEs; Digital transformation; Digital maturity; Evaluation model

Cite As

T. Tian, "Evaluation of Financial Intelligent Systems Digitalization Maturity of Small and Medium-sized Enterprises Based
on Fuzzy Logic Algorithm", Engineering Intelligent Systems, vol. 33 no. 3, pp. 275-284, 2025.


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Published

2025-05-01

Issue

Vol. 33 No. 3 (2025): International Journal of Engineering Intelligent Systems

Section

Article

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