Accounts Receivable (AR) management is fundamental to the financial activities of an enterprise, as it impacts liquidity, working capital optimization, and exposure to credit risk. Also, while SAP ERP incorporates a basic shell for AR processes, it heavily depends on batch-driven systems, manual validation loops, and fragmented exception handling for invoices, payments, and dunning activities. This is the imbalanced system we aim to rectify in this paper, wherein we discuss the design, implement the working framework of RPA systems using UiPath, and analyse the impact of deploying such systems on SAP FI-AR module’s seamless AR management. The system is designed in a way so as to automated transaction matching, running sequence initiation, flagging customer credit holds, and resolving discrepancies through defined bots triggered by SAP status document and aging report s with timed rules. In this experiment, we drew upon the business scenario simulated with over 50,000 AR documents from a diverse set of customers, payment and invoice classes, and regional compliance jurisdictions, enabling us to assess the operational limits of our automation efficiency testbed.
Empirical results are shown in a 61% reduction in reconciliation exceptions and a 49% increase in matching accuracy, alongside a greater than 2.3-times acceleration of completion of the dunning cycle for high value overdue accounts. The UiPath framework further decreased the average AR closing time by 3.8 days per cycle and provided real-time audit dashboards which enhanced visibility and cross departmental traceability. Plus, finance practitioners reported enhanced automated intervention, improved trust, and better collaboration between manual credit and automated collections on account of the survey driven feedback. Most notably, the bots maintained high operational system dependability, low negative flagging rates, and sustained high false positive rates proving low-volume trust automation integration autonomy mature, validating the integrations even in stressed financial seasons. This study provides SAP ERP users responsive modular designs focused on transforming AR processes, which can easily be replicated, and builds a basis for imagining AI powered credit acuity in prospective AR strategy frameworks.
Panigrahi T, Chapter. 17 Working Capital Management: Strategies for Efficiency. Financial Management Excellence: Strategies for Sustainable Growth. 2022;226.
2.
Chinnasamy. A Blockchain and Machine Learning Integrated Hybrid System for Drug Supply Chain Management for the Smart Pharmaceutical Industry. Clin J Med Health Pharm. 2024;(2):29–40.
3.
Wright M. Credit Management in SAP S/4HANA. 2019;
4.
Qiao X, Ren P, Dustdar S, Liu L, Ma H, Chen J. Web AR: A Promising Future for Mobile Augmented Reality—State of the Art, Challenges, and Insights. Proceedings of the IEEE. 2019;107(4):651–66.
5.
Menon R, Joshi A. Enzyme Recovery and Reuse via Ultrafiltration in Dairy Processing. Engineering Perspectives in Filtration and Separation. 2024;1–4.
6.
Nasution F, Puspitasari W, Saputra M. Automation Financial Processing in Account Receivable for Integrated Hospital System using ERP and Quickstart Approach. Proceedings of the 2020 The 6th International Conference on Frontiers of Educational Technologies. ACM; 2020. p. 204–11.
7.
Adrian M, Grinberg F, Griffoli M, Townsend R, Zhang N. A multi-currency exchange and contracting platform. 2022;
8.
Mehta P, Malhotra K. Natural language processing for automated extraction of medical terms in electronic health records. Global Journal of Medical Terminology Research and Informatics. 2024;(2):1–4.
9.
Holma J. SAP automation using Robot Process Automation. Bachelor’s Thesis, Degree Programme in Information Technology. 2020;
10.
Korrapati R. Revolutionizing HR Document Generation: An AI-Powered UiPath Bot for SAP SuccessFactors Author: Rakesh Korrapati. Sr Software engineer.
11.
Rydning D, Reinsel J, Gantz J. The digitization of the world from edge to core. 2018;1–28.
12.
Nagendra Harish Jamithireddy. Blockchain Based Supply Chain and Finance Reconciliation Frameworks in SAP Environments. Research Briefs on Information and Communication Technology Evolution. 2024;10:190–210.
13.
Szelągowski M, Berniak-Woźny J, Lupeikiene A, Senkus P. Paving the Way for Tomorrow: The Evolution of ERP and BPMS Systems. 2023;
14.
Nguyen TD, Le HS, Ho TT, Nguyen QH, Truong HP. Design an RPA model for the fulfillment process in an SAP ERP system. Journal of the Chinese Institute of Engineers. 2023;46(6):683–91.
15.
Arasuraja G. Organizational Change Management in Digital Transformation: A Framework for Success. Global Perspectives in Management. 2024;(2):12–21.
16.
Keller G, Teufel T. SAP R/3 process-oriented implementation: iterative process prototyping. 1998;
17.
Julius S. The role of artificial intelligence in enhancing financial decision-making: a case for AI-integrated ERP systems. International Journal for Novel Research in Economics. 2025;(1):24–33.
18.
Antysheva E, Prishutova T, Frolova V. Accounts receivable management in Digital transformation. 2020;1–6.
19.
Leelavathy V, Chithra N, Nachiammai V. Examining the Influence and Advantages of Digital Transformation within Accounting Firms: A Comprehensive Analysis. Advances in Economics, Business and Management Research. Atlantis Press International BV; 2024. p. 45–56.
20.
Menon R, Nair D. Cross-Border Climate Agreements: Legal Frameworks and Implementation Barriers. International Journal of SDG’s Prospects and Breakthroughs. 2024;13–6.
21.
Witjaksono R, Kusumasari T. Implementation Of Automated Testing: Order to Cash Business Processes on SAP Using Uipath Software. International Seminar on Intelligent Technology and Its Applications (ISITIA). 2024;148–53.
22.
Nabilla M DA, Witjaksono RW, Kusumasari TF. Implementation Of Automated Testing: Order To Cash Business Processes On SAP Using Uipath Software. 2024 International Seminar on Intelligent Technology and Its Applications (ISITIA). IEEE; 2024. p. 148–53.
23.
Kapoor S, Sharma V. A comprehensive framework for measuring brand success and key metrics. Brand Management Metrics Periodic Series in Multidisciplinary Studies. 2024;16–30.
The statements, opinions and data contained in the journal are solely those of the individual authors and contributors and not of the publisher and the editor(s). We stay neutral with regard to jurisdictional claims in published maps and institutional affiliations.
