Article: Process control of financial informatisation in industrial enterprises based on data mining and RPA technology Journal: International Journal of Information and Communication Technology (IJICT) 2026 Vol.27 No.27 pp.1 - 22 Abstract: To better control internal financial risk in industrial enterprises, this study developed an intelligent financial internal control system based on robot process automation. The system utilises a multi-objective evolutionary clustering algorithm with reference vectors to enhance credit management and billing optimisation. Results demonstrate an average value of 0.95 for the proposed method. The maximum mean of the normalised mutual information entropy index is 0.92 under the normalised mutual information index. This algorithm exhibits high clustering accuracy and robustness. The system achieves an accuracy rate of over 0.8 for enterprise credit rating, with an average of 86.9%. It surpasses other systems in evaluation accuracy and exhibits consistent results in manual evaluation. It can be seen that the performance of the system is more excellent, which can help industrial enterprises to carry out internal control of financial risks and simplify the financial workflow. Inderscience Publishers - linking academia, business and industry through research

Title: Process control of financial informatisation in industrial enterprises based on data mining and RPA technology

Authors: Ji Sun

Addresses: School of Economics and Management, Shaoxing Institute of Technology, Shaoxing 312000, China

Abstract: To better control internal financial risk in industrial enterprises, this study developed an intelligent financial internal control system based on robot process automation. The system utilises a multi-objective evolutionary clustering algorithm with reference vectors to enhance credit management and billing optimisation. Results demonstrate an average value of 0.95 for the proposed method. The maximum mean of the normalised mutual information entropy index is 0.92 under the normalised mutual information index. This algorithm exhibits high clustering accuracy and robustness. The system achieves an accuracy rate of over 0.8 for enterprise credit rating, with an average of 86.9%. It surpasses other systems in evaluation accuracy and exhibits consistent results in manual evaluation. It can be seen that the performance of the system is more excellent, which can help industrial enterprises to carry out internal control of financial risks and simplify the financial workflow.

Keywords: sustainable; financial management; robotic process automation; industrial enterprises; financial internal control.

DOI: 10.1504/IJICT.2026.152536

International Journal of Information and Communication Technology, 2026 Vol.27 No.27, pp.1 - 22

Received: 06 Aug 2025
Accepted: 11 Nov 2025
Published online: 25 Mar 2026 *

Title: Process control of financial informatisation in industrial enterprises based on data mining and RPA technology

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