AI-orchestrated Blockchain Settlement Networks: A Next-generation Framework for Real-time, Fraud-proof, Cross-border Payments
Main Article Content
Abstract
The global payment systems are still grappling with lag time, fractured infrastructure, compliance burden, and a consistent risk of fraud. Despite the fact that blockchain networks have created the potential of near-instant settlement with transparent and tamper-resistant ledger books, their current application is still limited by constraints of scalability, irregular liquidity, and lack of smart coordination among chains and jurisdictions. The paper introduces a post-generational model integrating advanced artificial intelligence and blockchain-based settlement networks to realize a cross-border payment without fraud and being real-time and cross-interoperable. The presented architecture employs AI-based routing, liquidity optimization that is dynamic, automated compliance checks, and predictive fraud detection to make distributed ledgers faster, more dependable, and better aligned with regulations. With the coordination of transactions over various blockchain rails - including high-throughput open networks and permissioned financial-grade registries - AI can change the settlement process of a single workflow into a self-adjusting ecosystem. This article defines the technical principles, business advantages, and prospects of AI-managed settlement networks, providing a futuristic pattern, which can redefine the value transfer between financial institutions, payment services providers, and international trade.
Downloads
Download data is not yet available.
Article Details
How to Cite
Mandadhi, V. R. (2023). AI-orchestrated Blockchain Settlement Networks: A Next-generation Framework for Real-time, Fraud-proof, Cross-border Payments. SAMRIDDHI : A Journal of Physical Sciences, Engineering and Technology, 15(04), 441-448. Retrieved from https://smsjournals.com/index.php/SAMRIDDHI/article/view/3433
Section
Articles
References
[1] Chatterjee, P. (2022). AI-Powered Real-Time Analytics for Cross-
Border Payment Systems. Available at SSRN 5251235.
[2] Strohmer, M. F., Easton, S., Eisenhut, M., Epstein, E., Kromoser, R.,
Peterson, E. R., & Rizzon, E. (2020). Disruptive Procurement: Winning
in a Digital World. Springer Nature.
[3] Vermesan, O., Friess, P., Guillemin, P., Serrano, M., Bouraoui, M.,
Freire, L. P., ... & van der Wees, A. (2022). IoT digital value chain
connecting research, innovation and deployment. In Digitising the
Industry Internet of Things Connecting the Physical, Digital and
VirtualWorlds (pp. 15-128). River Publishers.
[4] Sharma, S. K., Dwivedi, Y. K., Metri, B., & Rana, N. P. (Eds.). (2020).
Re-imagining Diffusion and Adoption of Information Technology and
Systems: A Continuing Conversation: IFIP WG 8.6 International
Conferenceon Transfer and Diffusion of IT, TDIT 2020, Tiruchirappalli, India,
December 18–19, 2020, Proceedings, Part II (Vol. 618). Springer Nature.
[5] Özelli, T. (2021). The financial and conceptual foundations of
intangible asset manager capitalism. Journal of Ekonomi, 3(1), 29-
100.
[6] IMT, H. D., Stefanou, H., Raptopoulos, A., WEL, D. K., CUH, J. C., & NSE,
C. N. HEIR innovations for healthcare systems.
[7] SANUSI, B. O. (2022). Sustainable Stormwater Management:
Evaluating the Effectiveness of Green Infrastructure in
Midwestern Cities. Well Testing Journal, 31(2), 74-96.
[8] Bodunwa, O. K., & Makinde, J. O. (2020). Application of Critical Path
Method (CPM) and Project Evaluation Review Techniques (PERT) in
Project Planning and Scheduling. J. Math. Stat. Sci, 6, 1-8.
[9] Isqeel Adesegun, O., Akinpeloye, O. J., & Dada, L. A. (2020).
Probability Distribution Fitting to Maternal Mortality Rates in Nigeria.
Asian Journal of Mathematical Sciences.
[10] Sanusi, B. O. Risk Management in Civil Engineering Projects Using
Data Analytics. Oyebode, O. A. (2022). Using Deep Learning to Identify Oil
Spill Slicks by Analyzing Remote Sensing Images (Master’s thesis,
Texas A&M University-Kingsville).
[11] Olalekan, M. J. (2021). Determinants of Civilian Participation Rate in G7
Countries from (1980-2018). Multidisciplinary Innovations & Research
Analysis, 2(4), 25-42.
[12] Asamoah, A. N. (2022). Global Real-Time Surveillance of Emerging
Antimicrobial Resistance Using Multi-Source Data Analytics.
INTERNATIONAL JOURNAL OF APPLIED PHARMACEUTICAL
SCIENCES AND RESEARCH, 7(02), 30-37.
[13] Pullamma, S. K. R. (2022). Event-Driven Microservices for Real-Time
Revenue Recognition in Cloud-Based Enterprise Applications.
SAMRIDDHI: A Journal of Physical Sciences, Engineering and
Technology, 14(04), 176-184.
[14] Oyebode, O. (2022). Neuro-Symbolic Deep Learning Fused with
Blockchain Consensus for Interpretable, Verifiable, and
Decentralized Decision-Making in High-Stakes Socio-Technical
Systems. International Journal of Computer Applications Technology
and Research, 11(12), 668-686.
[15] SANUSI, B. O. (2023). Performance monitoring and adaptive
management of as-built green infrastructure systems. Well Testing
Journal, 32(2), 224-237.
[16] Olalekan, M. J. (2023). Economic and Demographic Drivers of US
Medicare Spending (2010–2023): An Econometric Study Using CMS
and FRED Data. SAMRIDDHI: A Journal of Physical Sciences, Engineering
and Technology, 15(04), 433-440.
[17] Asamoah, A. N. (2023). The Cost of Ignoring Pharmacogenomics: A US
Health Economic Analysis of Preventable Statin and
Antihypertensive Induced Adverse Drug Reactions. SRMS JOURNAL
OF MEDICAL SCIENCE, 8(01), 55-61.
[18] Asamoah, A. N. (2023). Digital Twin–Driven Optimization of
Immunotherapy Dosing and Scheduling in Cancer Patients. Well Testing
Journal, 32(2), 195-206.
[19] Rony, M. M. A., Soumik, M. S., & SRISTY, M. S. (2023). Mathematical and AIBlockchain
Integrated Framework for Strengthening Cybersecurity in
National Critical Infrastructure. Journal of Mathematics and Statistics
Studies, 4(2), 92-103.
[20] Asamoah, A. N. (2023). Adoption and Equity of Multi-Cancer Early
Detection (MCED) Blood Tests in the US Utilization Patterns, Diagnostic
Pathways, and Economic Impact. INTERNATIONAL
JOURNALOFAPPLIEDPHARMACEUTICALSCIENCES ANDRESEARCH, 8(02),
35-41.
[21] Odunaike, A. (2023). Time-Varying Copula Networks for Capturing
Dynamic Default Correlations in Credit Portfolios. Multidisciplinary
Innovations & Research Analysis, 4(4), 16-37.
[22] Rony, M. M. A., Soumik, M. S., & Akter, F. (2023). Applying Artificial
Intelligence to Improve Early Detection and Containment of
Infectious Disease Outbreaks, Supporting National Public Health
Preparedness. Journal of Medical and Health Studies, 4(3), 82-93.
[23] Siddique, M. T., Hussain, M. K., Soumik, M. S., & SRISTY, M. S. (2023).
Developing Quantum-Enhanced Privacy-Preserving Artificial
Intelligence Frameworks Based on Physical Principles to Protect
Sensitive Government and Healthcare Data from Foreign Cyber
Threats. British Journal of Physics Studies, 1(1), 46-58.
[24] Parra Domínguez, J., Rodríguez González, S., Prieto Tejedor, J.,
Corchado Rodríguez, J. M., Marreiros, G., & Ramos, C. (2022). Actas del III
Taller de tecnologías de la información y la comunicación disruptivas
para la innovación y la transformación digital: 18 de diciembre de
2020, Online.
[25] Garcia, I. F. (2020). Why and How the 2018 Caravanas from Central America
Happened and How an Iris Recognition Program Could Help These Massive
Typeof Movementsto Be More Efficient and Secure for All Parties Involved
(Master’s thesis, San Diego State University).
[26] Venkata Krishna Bharadwaj Parasaram. (2021). Assessing the Impact
of Automation Tools on Modern Project Governance. International
Journal of Engineering Science and Humanities, 11(4), 38–47.
Retrieved from https://www.ijesh.com/j/article/ view/423
[27] Feffer, J. (2021). Right Across the World: The Global Networking of the Far-
Right and the Left Response. Pluto Press.
[28] Boutaud, B. (2022). Energy Autonomy: From the Notion to the
Concepts. John Wiley & Sons.
[29] Satish Kumar Nalluri, Venkata Krishna Bharadwaj Parasaram,
Varun Teja Bathini. (2020). Secure Automation Frameworks for
Smart Manufacturing Using Blockchain-Assisted Traceability.
International Journal of Research & Technology, 8(2), 47–53.
Retrieved from https://ijrt.org/j/article/view/879
[30] Komninos, N., Kakderi, C., Panori, A., Psaltoglou, A., &
Chatziparadeisis, A. (2020). Ecosystems and functioning EDP for S3
2021–2027 in Greece. Report to the European Commission, DG Regional
and Urban Policy.
[31] Chebbo, M. (2022). Digitalization and Smart Energy Devices.
Technologies for Integrated Energy Systems and Networks.
[32] Parra Domínguez, J., Rodríguez González, S., Prieto Tejedor, J.,
& Corchado, J. M. (2021). Proceedings of the III Workshop on
Disruptive information and communication technologies for
innovation and digital transformation= Actas del III Taller de
Tecnologías de la información y la comunicación disruptivas
para la innovación y la transformación digital.
[33] Soumik, M. S., Sarkar, M., & Rahman, M. M. (2021). Fraud Detection
and Personalized Recommendations on Synthetic E-Commerce
Data with ML. Research Journal in Business and Economics,
1(1a), 15-29.
[34] Islam, M. Z. (2022). Digital Transformation Management. Dhaka:
BRAC University.
[35] Olateju, M., & Frempong, D. (2022). Sustainability-Driven Stem
Education: A Project-Based Model for Teaching Climate Science
In Urban High Schools.
Border Payment Systems. Available at SSRN 5251235.
[2] Strohmer, M. F., Easton, S., Eisenhut, M., Epstein, E., Kromoser, R.,
Peterson, E. R., & Rizzon, E. (2020). Disruptive Procurement: Winning
in a Digital World. Springer Nature.
[3] Vermesan, O., Friess, P., Guillemin, P., Serrano, M., Bouraoui, M.,
Freire, L. P., ... & van der Wees, A. (2022). IoT digital value chain
connecting research, innovation and deployment. In Digitising the
Industry Internet of Things Connecting the Physical, Digital and
VirtualWorlds (pp. 15-128). River Publishers.
[4] Sharma, S. K., Dwivedi, Y. K., Metri, B., & Rana, N. P. (Eds.). (2020).
Re-imagining Diffusion and Adoption of Information Technology and
Systems: A Continuing Conversation: IFIP WG 8.6 International
Conferenceon Transfer and Diffusion of IT, TDIT 2020, Tiruchirappalli, India,
December 18–19, 2020, Proceedings, Part II (Vol. 618). Springer Nature.
[5] Özelli, T. (2021). The financial and conceptual foundations of
intangible asset manager capitalism. Journal of Ekonomi, 3(1), 29-
100.
[6] IMT, H. D., Stefanou, H., Raptopoulos, A., WEL, D. K., CUH, J. C., & NSE,
C. N. HEIR innovations for healthcare systems.
[7] SANUSI, B. O. (2022). Sustainable Stormwater Management:
Evaluating the Effectiveness of Green Infrastructure in
Midwestern Cities. Well Testing Journal, 31(2), 74-96.
[8] Bodunwa, O. K., & Makinde, J. O. (2020). Application of Critical Path
Method (CPM) and Project Evaluation Review Techniques (PERT) in
Project Planning and Scheduling. J. Math. Stat. Sci, 6, 1-8.
[9] Isqeel Adesegun, O., Akinpeloye, O. J., & Dada, L. A. (2020).
Probability Distribution Fitting to Maternal Mortality Rates in Nigeria.
Asian Journal of Mathematical Sciences.
[10] Sanusi, B. O. Risk Management in Civil Engineering Projects Using
Data Analytics. Oyebode, O. A. (2022). Using Deep Learning to Identify Oil
Spill Slicks by Analyzing Remote Sensing Images (Master’s thesis,
Texas A&M University-Kingsville).
[11] Olalekan, M. J. (2021). Determinants of Civilian Participation Rate in G7
Countries from (1980-2018). Multidisciplinary Innovations & Research
Analysis, 2(4), 25-42.
[12] Asamoah, A. N. (2022). Global Real-Time Surveillance of Emerging
Antimicrobial Resistance Using Multi-Source Data Analytics.
INTERNATIONAL JOURNAL OF APPLIED PHARMACEUTICAL
SCIENCES AND RESEARCH, 7(02), 30-37.
[13] Pullamma, S. K. R. (2022). Event-Driven Microservices for Real-Time
Revenue Recognition in Cloud-Based Enterprise Applications.
SAMRIDDHI: A Journal of Physical Sciences, Engineering and
Technology, 14(04), 176-184.
[14] Oyebode, O. (2022). Neuro-Symbolic Deep Learning Fused with
Blockchain Consensus for Interpretable, Verifiable, and
Decentralized Decision-Making in High-Stakes Socio-Technical
Systems. International Journal of Computer Applications Technology
and Research, 11(12), 668-686.
[15] SANUSI, B. O. (2023). Performance monitoring and adaptive
management of as-built green infrastructure systems. Well Testing
Journal, 32(2), 224-237.
[16] Olalekan, M. J. (2023). Economic and Demographic Drivers of US
Medicare Spending (2010–2023): An Econometric Study Using CMS
and FRED Data. SAMRIDDHI: A Journal of Physical Sciences, Engineering
and Technology, 15(04), 433-440.
[17] Asamoah, A. N. (2023). The Cost of Ignoring Pharmacogenomics: A US
Health Economic Analysis of Preventable Statin and
Antihypertensive Induced Adverse Drug Reactions. SRMS JOURNAL
OF MEDICAL SCIENCE, 8(01), 55-61.
[18] Asamoah, A. N. (2023). Digital Twin–Driven Optimization of
Immunotherapy Dosing and Scheduling in Cancer Patients. Well Testing
Journal, 32(2), 195-206.
[19] Rony, M. M. A., Soumik, M. S., & SRISTY, M. S. (2023). Mathematical and AIBlockchain
Integrated Framework for Strengthening Cybersecurity in
National Critical Infrastructure. Journal of Mathematics and Statistics
Studies, 4(2), 92-103.
[20] Asamoah, A. N. (2023). Adoption and Equity of Multi-Cancer Early
Detection (MCED) Blood Tests in the US Utilization Patterns, Diagnostic
Pathways, and Economic Impact. INTERNATIONAL
JOURNALOFAPPLIEDPHARMACEUTICALSCIENCES ANDRESEARCH, 8(02),
35-41.
[21] Odunaike, A. (2023). Time-Varying Copula Networks for Capturing
Dynamic Default Correlations in Credit Portfolios. Multidisciplinary
Innovations & Research Analysis, 4(4), 16-37.
[22] Rony, M. M. A., Soumik, M. S., & Akter, F. (2023). Applying Artificial
Intelligence to Improve Early Detection and Containment of
Infectious Disease Outbreaks, Supporting National Public Health
Preparedness. Journal of Medical and Health Studies, 4(3), 82-93.
[23] Siddique, M. T., Hussain, M. K., Soumik, M. S., & SRISTY, M. S. (2023).
Developing Quantum-Enhanced Privacy-Preserving Artificial
Intelligence Frameworks Based on Physical Principles to Protect
Sensitive Government and Healthcare Data from Foreign Cyber
Threats. British Journal of Physics Studies, 1(1), 46-58.
[24] Parra Domínguez, J., Rodríguez González, S., Prieto Tejedor, J.,
Corchado Rodríguez, J. M., Marreiros, G., & Ramos, C. (2022). Actas del III
Taller de tecnologías de la información y la comunicación disruptivas
para la innovación y la transformación digital: 18 de diciembre de
2020, Online.
[25] Garcia, I. F. (2020). Why and How the 2018 Caravanas from Central America
Happened and How an Iris Recognition Program Could Help These Massive
Typeof Movementsto Be More Efficient and Secure for All Parties Involved
(Master’s thesis, San Diego State University).
[26] Venkata Krishna Bharadwaj Parasaram. (2021). Assessing the Impact
of Automation Tools on Modern Project Governance. International
Journal of Engineering Science and Humanities, 11(4), 38–47.
Retrieved from https://www.ijesh.com/j/article/ view/423
[27] Feffer, J. (2021). Right Across the World: The Global Networking of the Far-
Right and the Left Response. Pluto Press.
[28] Boutaud, B. (2022). Energy Autonomy: From the Notion to the
Concepts. John Wiley & Sons.
[29] Satish Kumar Nalluri, Venkata Krishna Bharadwaj Parasaram,
Varun Teja Bathini. (2020). Secure Automation Frameworks for
Smart Manufacturing Using Blockchain-Assisted Traceability.
International Journal of Research & Technology, 8(2), 47–53.
Retrieved from https://ijrt.org/j/article/view/879
[30] Komninos, N., Kakderi, C., Panori, A., Psaltoglou, A., &
Chatziparadeisis, A. (2020). Ecosystems and functioning EDP for S3
2021–2027 in Greece. Report to the European Commission, DG Regional
and Urban Policy.
[31] Chebbo, M. (2022). Digitalization and Smart Energy Devices.
Technologies for Integrated Energy Systems and Networks.
[32] Parra Domínguez, J., Rodríguez González, S., Prieto Tejedor, J.,
& Corchado, J. M. (2021). Proceedings of the III Workshop on
Disruptive information and communication technologies for
innovation and digital transformation= Actas del III Taller de
Tecnologías de la información y la comunicación disruptivas
para la innovación y la transformación digital.
[33] Soumik, M. S., Sarkar, M., & Rahman, M. M. (2021). Fraud Detection
and Personalized Recommendations on Synthetic E-Commerce
Data with ML. Research Journal in Business and Economics,
1(1a), 15-29.
[34] Islam, M. Z. (2022). Digital Transformation Management. Dhaka:
BRAC University.
[35] Olateju, M., & Frempong, D. (2022). Sustainability-Driven Stem
Education: A Project-Based Model for Teaching Climate Science
In Urban High Schools.