Article: Research on process optimisation and intelligent decision-making modelling of RPA in university fund management Journal: International Journal of Information and Communication Technology (IJICT) 2026 Vol.27 No.77 pp.77 - 93 Abstract: As fund management in colleges and universities faces the challenges of low efficiency and intensified operational risks, this study aims to build a new intelligent decision-making model to realise process automation and decision optimisation by integrating robotic process automation (RPA) and artificial intelligence technology. This paper adopts a hierarchical architecture to integrate data layer, process layer, decision layer and application layer, and uses OCR, LSTM and random forest technologies to automatically process invoice identification, fund forecast and risk monitoring. Although the model has achieved remarkable results in improving the efficiency of capital use and reducing risks, it still has limitations such as strong data dependence, and it is necessary to optimise the lightweight and cross-scenario adaptability of the algorithm in the future. Generally speaking, this study provides empirical support for financial intelligence in colleges and universities, and promotes the innovative practice of integrating automation and decision-making. Inderscience Publishers - linking academia, business and industry through research

Title: Research on process optimisation and intelligent decision-making modelling of RPA in university fund management

Authors: Longxia Yuan

Addresses: Beijing Information Science and Technology University, Beijing, 100192, China

Abstract: As fund management in colleges and universities faces the challenges of low efficiency and intensified operational risks, this study aims to build a new intelligent decision-making model to realise process automation and decision optimisation by integrating robotic process automation (RPA) and artificial intelligence technology. This paper adopts a hierarchical architecture to integrate data layer, process layer, decision layer and application layer, and uses OCR, LSTM and random forest technologies to automatically process invoice identification, fund forecast and risk monitoring. Although the model has achieved remarkable results in improving the efficiency of capital use and reducing risks, it still has limitations such as strong data dependence, and it is necessary to optimise the lightweight and cross-scenario adaptability of the algorithm in the future. Generally speaking, this study provides empirical support for financial intelligence in colleges and universities, and promotes the innovative practice of integrating automation and decision-making.

Keywords: colleges and universities; money management; RPA robots; process optimisation; intelligent decision-making.

DOI: 10.1504/IJICT.2026.154955

International Journal of Information and Communication Technology, 2026 Vol.27 No.77, pp.77 - 93

Received: 27 Feb 2026
Accepted: 30 Apr 2026
Published online: 20 Jul 2026 *

Title: Research on process optimisation and intelligent decision-making modelling of RPA in university fund management

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