Driving Efficiency and Risk Management in Finance through AI and RPA

Xiaoan Zhan; Zhipeng Ling; Zeqiu Xu; Lingfeng Guo; Shikai Zhuang

doi:10.20944/preprints202407.0083.v1

Preprint Article Version 1 This version is not peer-reviewed

Version 1 : Received: 29 June 2024 / Approved: 1 July 2024 / Online: 1 July 2024 (11:47:16 CEST)

This article examines the integration of artificial intelligence (AI) and robotic process automation (RPA) in financial accounting and management, underscoring their role in driving the digital transformation of corporate finance. It discusses the shortcomings of traditional financial processes and highlights the potential of AI and RPA technologies to enhance efficiency, accuracy, and cost-effectiveness. The paper also explores the limitations of RPA, such as its challenges in processing unstructured data and handling complex decision-making scenarios. Looking forward, it considers the future trends in AI and RPA, emphasizing the benefits of cloud technology in scaling automated systems and addressing associated challenges.

Artificial intelligence (AI); Robotic Process Automation (RPA); Intelligent Process Automation (IPA); Financial Risk Management

Computer Science and Mathematics, Artificial Intelligence and Machine Learning

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Driving Efficiency and Risk Management in Finance through AI and RPA

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