Volume 2 Issue 2 | 2025 | View PDF
Paper Id:IJMSM-V2I2P117
doi: 10.71141/30485037/V2I2P117

AI-Agentic PayTech Orchestration for Cross-Border Remittances

Vijay Kumar Soni, Manish Tomar, Yeswanth Surampudi

Citation:
Vijay Kumar Soni, Manish Tomar, Yeswanth Surampudi, "AI-Agentic PayTech Orchestration for Cross-Border Remittances" International Journal of Multidisciplinary on Science and Management, Vol. 2, No. 2, pp. 176-186, 2025.

Abstract:
Cross-border remittances particularly for small and medium enterprises (SMEs) continue to face challenges such as latency, high fees, regulatory burdens, and fragmented financial infrastructure. This article presents an AI-agentic orchestration framework that employs autonomous agents and large language model (LLM)-enhanced smart contracts to dynamically manage end-to-end PayTech processes. The proposed system intelligently selects optimal payment networks, enforces compliance through generative regulatory interpretation, and executes real-time foreign exchange (FX) hedging. It also incorporates self-healing workflows capable of auto-generating code patches and audit narratives, thereby minimizing operational risks. Empirical evaluations conducted via ISO 20022 messaging endpoints reveal significant gains in cost efficiency, transaction speed, and audit transparency. This research establishes AI-agentic orchestration as a foundational architecture for building scalable, secure, and intelligent global remittance solutions.

Keywords: SMEs, multi-agent systems (MAS), FX hedging and risk mitigation, retrieval-augmented generation (RAG), anti-money laundering (AML), compliance-as-a-service (CaaS), banking-as-a-service (BaaS).

References:
1. The World Bank, “Small and Medium Enterprises (SMEs) Finance,” World Bank, Oct. 16, 2019. [Online]. Available: https://www.worldbank.org/en/topic/smefinance
2. J. Byrum, "The past, present, and future of the payment system as trusted broker and the implications for banking," in *Innovative Technology at the Interface of Finance and Operations: Volume I*, 2022, pp. 101–151.
3. International Monetary Fund, “A Financial System Tested by Higher Inflation and Interest Rates,” Chapter 1 at a Glance, *Global Financial Stability Report: Safeguarding Financial Stability amid High Inflation and Geopolitical Risks*, Apr. 2023. [Online]. Available: https://www.imf.org/-/media/Files/Publications/GFSR/2023/April/English/ch1.ashx. [Accessed: Jun. 10, 2025].
4. Financial Action Task Force, “The FATF Recommendations,” as amended Feb. 2025. [Online]. Available: https://www.fatf-gafi.org/en/publications/Fatfrecommendations/Fatf-recommendations.html
5. McKinsey & Company, “2023: The year in charts,” *Featured Insights – 2023 Year in Review*, Dec. 8, 2023. [Online]. Available: https://www.mckinsey.com/featured-insights/2023-year-in-review/2023-the-year-in-charts. [Accessed: Jun. 10, 2025].
6. K. Kalluri, "Optimizing Financial Services Implementing Pega's Decisioning Capabilities for Fraud Detection," *Int. J. Innov. Res. Eng. Multidiscip. Phys. Sci.*, vol. 10, no. 1, pp. 1–9, 2022.
7. A. Verhage, "Between the hammer and the anvil? The anti-money laundering-complex and its interactions with the compliance industry," *Crime Law Soc. Change*, vol. 52, pp. 9–32, 2009.
8. V. Thokal and P. R. Patil, "Review and analysis of the literature: Artificial intelligence-based digital transformation of automated customer onboarding," *Eng. Proc.*, vol. 59, no. 1, p. 234, 2024.
9. M. L. Bech, Y. Shimizu, and P. Wong, "The quest for speed in payments," *BIS Q. Rev.*, Mar. 2017.
10. A. Adesiyun et al., "Stakeholder Engagement Report: Deliverable D1," 2023.
11. G. Wehinger, "SMEs and the credit crunch: Current financing difficulties, policy measures and a review of literature," *OECD J. Financ. Mark. Trends*, vol. 2013, no. 2, pp. 115–148, 2014.
12. M. Verstraete, "The stakes of smart contracts," *Loy. U. Chi. L. J.*, vol. 50, pp. 743–769, 2018.
13. M. Tarhini, "Application of asset tokenization, smart contracts and decentralized finance in agriculture," *Rev. Stud. Financ.*, vol. 6, no. 10, pp. 152–163, 2021.
14. R. L. Axtell and J. D. Farmer, "Agent-based modeling in economics and finance: Past, present, and future," *J. Econ. Lit.*, vol. 63, no. 1, pp. 197–287, 2025.
15. M. Gauci, "Navigating ISO 20022 maintenance in a connected world: A vision for harmonisation," *J. Digit. Bank.*, vol. 9, no. 2, pp. 118–128, 2024.
16. X. Wang et al., "Executable code actions elicit better llm agents," in *Proc. 41st Int. Conf. Mach. Learn.*, 2024.
17. G. Kaur, "Trust the Machine and Embrace Artificial Intelligence (AI) to Combat Money Laundering Activities," in *Computational Intelligence for Modern Business Systems: Emerging Applications and Strategies*, Singapore: Springer Nature, 2023, pp. 63–81.
18. S. I. Abir et al., "Use of AI-Powered Precision in Machine Learning Models for Real-Time Currency Exchange Rate Forecasting in BRICS Economies," *J. Econ. Finance Account. Stud.*, vol. 6, no. 6, pp. 66–83, 2024.
19. B. Padiu et al., "To what extent have llms reshaped the legal domain so far? a scoping literature review," *Information*, vol. 15, no. 11, p. 662, 2024.
20. A. Mahida, "Comprehensive Review on Automated Suspicious Activity Report Generation (SAR)."
21. J. Enajero, "The Impact of AI-Driven Predictive Models on Traditional Financial Market Volatility: A Comparative Study with Crypto Markets."
22. X. Ma et al., "A comprehensive survey on graph anomaly detection with deep learning," *IEEE Trans. Knowl. Data Eng.*, vol. 35, no. 12, pp. 12012–12038, 2021.
23. W. Sun et al., "Source code summarization in the era of large language models," *arXiv preprint arXiv:2407.07959*, 2024.
24. Y. N. Gwon et al., "The use of generative AI for scientific literature searches for systematic reviews: ChatGPT and Microsoft Bing AI performance evaluation," *JMIR Med. Inform.*, vol. 12, p. e51187, 2024.
25. A. Mongoli, *The Use of LLMs in the Legal Field: Optimizing Contract Management with Generative Artificial Intelligence*. M.S. thesis, Politecnico di Torino, 2024.
26. P. Liu et al., "Scanflow-k8s: Agent-based framework for autonomic management and supervision of ml workflows in kubernetes clusters," in *Proc. 22nd IEEE Int. Symp. Cluster, Cloud Internet Comput. (CCGrid)*, 2022.
27. C. Catalini and J. S. Gans, "Some simple economics of the blockchain," *Commun. ACM*, vol. 63, no. 7, pp. 80–90, 2020.
28. J. R. Martínez Resano, "Regulating for Competition with Bigtechs: Banking-As-A-Service and 'Beyond Banking'," *SSRN Electron. J.*, 2021. [Online]. Available: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3982500
29. S. Banerjee, A. Agarwal, and S. Singla, "Llms will always hallucinate, and we need to live with this," *arXiv preprint arXiv:2409.05746*, 2024.
30. Dixit, S., & Jangid, J. (2025). Exploring smart contracts and artificial intelligence in FinTech. Journal of Information Systems Engineering and Management, 10(14s), 282–295. https://doi.org/10.52783/jisem.v10i14s.2208