The Role of Cloud and AI Technology in Providing Secure and Fast Payments
DOI:
https://doi.org/10.5281/zenodo.17732019Keywords:
Cloud, Computing, Artificial, Intelligence, Blockchain, Technology, Cryptocurrency, AdoptionAbstract
The financial landscape has undergone unprecedented change through incorporation of cloud computing and artificial intelligence technologies, radically transforming transactional processes and payment ecosystems globally. Payment systems in emerging economies exhibit outstanding growth patterns, with the uptake of mobile payment going exponential as the constraints of conventional banking infrastructure fuel innovation in finance technology solutions. Cloud infrastructure makes it possible for payment platforms to attain higher scalability features by means of elastic resource provisioning, distributed computing models, and event-driven processing systems that can support huge transaction volumes with sub-second response times. Artificial intelligence optimizes payment security by means of advanced fraud detection algorithms that employ supervised machine learning methods, ensemble learning methods, and behavioral analysis systems with the ability to scan millions of transaction records to detect fraudulent patterns accurately. Biometric authentication solutions utilize hybrid deep learning techniques integrating convolutional and recurrent neural networks to ensure secure user authentication through fingerprint recognition, face detection, and multi-modal biometric processing. Centralized payment interfaces utilize event-driven, scalable architectures and AI-driven cache management systems to enhance API performance and support multiple payment schemes through unified interfaces. Blockchain technology is a paradigm change towards decentralized payment processing using distributed ledger systems, smart contracts, and consensus algorithms augmented by machine learning models. Patterns of cryptocurrency adoption show very strong correlations with the level of economic development, providing new notions of financial sovereignty while tackling challenges of financial inclusion in countries with low banking infrastructure levels. The intersection of cloud computing and artificial intelligence forms holistic payment ecosystems that provide better security, faster transactions, lower operational costs, and greater financial access to previously excluded populations around the world.
References
Romny Ly and Bora Ly, "Digital payment systems in an emerging economy," ScienceDirect, 2024. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2451958824001507
Alexandru Iosup et al., "Performance Analysis of Cloud Computing Services for Many-Tasks Scientific Computing," ResearchGate, 2011. [Online]. Available: https://www.researchgate.net/publication/224221 699_Performance_Analysis_of_Cloud_Computing_Services_for_Many-Tasks_Scientific_Computing
Goutham Sabbani, "Cloud-Based High Frequency Trading," Journal of Artificial Intelligence & Cloud Computing, 2023. [Online]. Available: https://onlinescientificresearch.com/articles/cloudbased-high-freq uency-trading.pdf
Faith Victoria, "SECURITY CONSIDERATIONS IN MICROSERVICES FOR FINANCIAL AND INSURANCE APPLICATIONS," ResearchGate, 2025. [Online]. Available: https://www.researchgate.net/ publication/393679900_SECURITY_CONSIDERATIONS_IN_MICROSERVICES_
FOR_FINANCIAL_AND_INSURANCE_APPLICATIONS
Jonathan Kwaku Afriyie et al., "A supervised machine learning algorithm for detecting and predicting fraud in credit card transactions," ScienceDirect, 2023. [Online]. Available: https://www.sciencedirect.com/ science/article/pii/S2772662223000036
Abdulrahman Hussian et al., "A Hybrid Deep Learning Approach for Secure Biometric Authentication Using Fingerprint Data," MDPI, 2025. [Online]. Available: https://www.mdpi.com/2073-431X/14/5/178
Israel Chandra Aarush and Alaa Al Aswany, "Scalable Event-Driven Architectures for High-Throughput Payment Processing Systems," ResearchGate, 2025. [Online]. Available: https://www.researchgate.net/ publication/392021130_Scalable_Event-Driven_Architectures_for_High-Throughput_Payment_Processing_Systems
Kalyan Chakravarthy Thatikonda, "METHODS AND PROCESSES FOR OPTIMIZATION OF CLOUD API PERFORMANCE THROUGH AI BASED MACHINE LEARNING ENSEMBLE CACHE MANAGEMENT," International Journal of Advanced Research in Engineering and Technology (IJARET), 2025. [Online]. Available: https://www.researchgate.net/publication/389521911_METHODS_AND_ PR OCESSES_FOR_OPTIMIZATION_OF_CLOUD_API_PERFORMANCE_THROUGH_
AI_BASED_MACHINE_LEARNING_ENSEMBLE_CACHE_MANAGEMENT
Mohd Javaid et al., "A review of Blockchain Technology applications for financial services," ScienceDirect, 2022. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2772485922000606
Syamsul Rizal and Dong-Seong Kim, "Enhancing Blockchain Consensus Mechanisms: A Comprehensive Survey on Machine Learning Applications and Optimizations," ScienceDirect, 2025. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2096720925000296
Cosimo Magazzino et al., "Economic and financial development as determinants of crypto adoption," ScienceDirect, 2025. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S105752192500 3047
Yongsheng Guo et al., "Examining the Drivers and Economic and Social Impacts of Cryptocurrency Adoption," MDPI, 2025. [Online]. Available: https://www.mdpi.com/2674-1032/4/1/5
Surana, S. “Implementing ERP Systems in Financial Services: A Case Study on Driving Adoption and Ensuring Data Integrity." Sarcouncil Journal of Economics and Business Management 4.06 (2025): pp 1-10
Belhassen, A. " Machine Learning for Predictive Maintenance: Fusing Vibration Sensor Data and Thermal Imaging to Forecast Bearing Failure." Sarcouncil Journal of Engineering and Computer Sciences 1.3 (2022): pp 9-18
Belhassen, A. "An Automated Test Bench for Characterizing the Efficiency of DC-DC Converters under Dynamic Load Conditions." Jr. Inn. Sci. 1.2 (2025): pp 39-47
Surana, S. "The Future of Financial Reporting: Integrating ESG Metrics into Traditional Financial Statements and Management Review." Sarcouncil Journal of Entrepreneurship and Business Management 3.3 (2024): pp 1-9.
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