Citation :

Braja Gopal Mahapatra , 2025. "Enhancing B2B Payment Efficiency with AI and RPA: Moving Towards Fully Automated Transactions" ESP International Journal of Advancements in Computational Technology (ESP-IJACT)  Volume 2, Issue 2: 5-16.

Abstract :

Business-to-Business (B2B) payments are an area factor that affects traditional payments. The main issues affecting traditional payments include the fact that they are prone to making mistakes such as inefficiencies, errors, and delays, which affect operations. The evolvements of Artificial Intelligence (AI) and Robotic Process Automation (RPA) state the significance of revolutionary changes in this area. This paper examines how AI and RPA can work together to improve B2B payment systems to offer smooth, efficient, and robotics payments. It is also necessary to mention that the major directions are deeply associated with the functioning of the payment processes, with the methods of fraud detection, the boosting of the decision-making processes, and the integration of AI analytical systems. By reviewing the current literatures and conducting empirical analysis, this paper discusses the advantages, disadvantages, and prospects of these technologies in transforming B2B payments.

References :

[1] Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. WW Norton & company.

[2] Ferrara, A., & Ferraresi, M. (2022). Assessing the economic impact of faster payments in B2B commercial transactions. Publications Office of the European Union.

[3] Moro-Visconti, R. (2022). Digital Scalability and Growth Options. In The Valuation of Digital Intangibles: Technology, Marketing, and the Metaverse (pp. 85-139). Cham: Springer International Publishing.

[4] Paunov, Y., Wänke, M., & Vogel, T. (2019). Transparency effects on policy compliance: disclosing how defaults work can enhance their effectiveness. Behavioural Public Policy, 3(2), 187-208.

[5] Yarlagadda, R. T. (2018). The RPA and AI automation. International Journal of Creative Research Thoughts (IJCRT), ISSN, 2320-2882.

[6] Listfield, R., & Montes-Negret, F. (1994). Modernizing payment systems in emerging economies (Vol. 1336). World Bank Publications.

[7] Kim, H., Hong, H., Ryu, G., & Kim, D. (2021). A study on the automated payment system for artificial intelligence-based product recognition in the age of contactless services. International Journal of Advanced Culture Technology, 9(2), 100-105.

[8] Miglionico, A. (2022). Digital payments system and market disruption. Law and Financial Markets Review, 16(3), 181-196.

[9] Xu, Q., Xu, L., Jiang, G., & He, Y. (2024, June). Artificial Intelligence in Risk Protection for Financial Payment Systems. In The 24th International scientific and practical conference “Technologies of scientists and implementation of modern methods”(June 18–21, 2024) Copenhagen, Denmark. International Science Group. 2024. 431 p. (p. 344).

[10] Agrawal, S. (2022). Enhancing payment security through AI-Driven anomaly detection and predictive analytics. International Journal of Sustainable Infrastructure for Cities and Societies, 7(2), 1-14.

[11] Mujtaba, N., & Yuille, A. AI-Powered Financial Services: Enhancing Fraud Detection and Risk Assessment with Predictive Analytics.

[12] Jackson, D. (2018). Innovation in Business to Business Payment Services: a contextual approach to future innovation.

[13] Xu, J., & Quaddus, M. (2010). Overview-Part Ii: B2c, B2b And Other Types Of E-Business. E-Business in the 21st century: realities challenges and outlook, 25-62.

[14] Roy, S. (2015). Overview of Electronic Payment System: A Special Reference to India. In Handbook of Research on Cultural and Economic Impacts of the Information Society (pp. 391-418). IGI Global.

[15] Rani, N. J., & Suresh, A. (2024). Role of Artificial Intelligence in Bank Payment Applications. Center for Development Economic, 11(19), 173-182.

[16] Wang, S., Wen, W., Niu, Y., & Li, X. (2024). Digital transformation and corporate labor investment efficiency. Emerging Markets Review, 59, 101109.

[17] Challoumis, C. (2024, October). THE FUTURE OF MONEY-EXPLORING AI’S ROLE IN FINANCE AND PAYMENTS. In XVI International Scientific Conference (pp. 158-189).

[18] Mullangi, K. (2023). Innovations in payment processing: Integrating accelerated testing for enhanced security. American Digits: Journal of Computing and Digital Technologies, 1(1), 18-32.

[19] Inampudi, R. K., Pichaimani, T., & Surampudi, Y. (2022). AI-Enhanced Fraud Detection in Real-Time Payment Systems: Leveraging Machine Learning and Anomaly Detection to Secure Digital Transactions. Australian Journal of Machine Learning Research & Applications, 2(1), 483-523.

[20] Gayam, S. R. (2021). Artificial Intelligence for Financial Fraud Detection: Advanced Techniques for Anomaly Detection, Pattern Recognition, and Risk Mitigation. African Journal of Artificial Intelligence and Sustainable Development, 1(2), 377-412.

[21] Tillu, R., Muthusubramanian, M., & Periyasamy, V. (2023). From Data to Compliance: The Role of AI/ML in Optimizing Regulatory Reporting Processes. Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online), 2(3), 381-391.

Keywords :

B2B Payments, Artificial Intelligence, Robotic Process Automation, Automation, Efficiency, Fraud Detection.