Authors :
Jennifer Amebleh; Otugene Victor Bamigwojo; Joy Onma Enyejo
Volume/Issue :
Volume 10 - 2025, Issue 9 - September
Google Scholar :
https://tinyurl.com/3eshzbz2
Scribd :
https://tinyurl.com/mr3evyms
DOI :
https://doi.org/10.38124/ijisrt/25sep331
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Note : Google Scholar may take 30 to 40 days to display the article.
Abstract :
Automated User Acceptance Testing (UAT) is becoming a cornerstone in regulated payment systems, where
technical reliability and financial compliance must operate in unison. Traditional manual UAT approaches often fail to
provide the scalability, accuracy, and coverage required to validate complex payment workflows under stringent accounting
standards. This review explores how property-based testing and synthetic data generation can enhance automated UAT
frameworks, offering systematic validation of transaction invariants, expanded scenario coverage, and improved data
privacy protections. A central focus is the integration of International Financial Reporting Standards (IFRS 15) and
Generally Accepted Accounting Principles (ASC 606) through revenue-recognition validation gates, which embed
accounting compliance into testing pipelines. Case studies from banking, FinTech, and payment service providers illustrate
how these methods strengthen auditability, reduce compliance risks, and support transparent financial reporting. Emerging
trends—including the adoption of artificial intelligence, continuous testing in DevOps environments, and cloud-enabled
platforms—are identified as shaping the future of automated UAT. The review concludes that bridging technical testing
with financial governance not only ensures regulatory compliance but also enhances operational resilience, scalability, and
trust in modern payment infrastructures.
Keywords :
Automated user Acceptance Testing (UAT); Regulated Payment Systems; Property-Based Testing; Synthetic Data; Revenue Recognition.
References :
- ALAHMADI, H. A. (2020). A QUALITATIVE INVESTIGATION INTO SHARIAH GOVERNANCE ATTRIBUTES, SUPERVISION PROCEDURES AND AUDITING IN SAUDI ISLAMIC BANKS.
- Amebleh, J. & Okoh, O. F. (2023). Accounting for rewards aggregators under ASC 606/IFRS 15: Performance obligations, consideration payable to customers, and automated liability accruals at payments scale. Finance & Accounting Research Journal, Fair East Publishers Volume 5, Issue 12, 528-548 DOI: 10.51594/farj.v5i12.2003
- Amebleh, J. & Omachi, A. (2022). Data Observability for High-Throughput Payments Pipelines: SLA Design, Anomaly Budgets, and Sequential Probability Ratio Tests for Early Incident Detection International Journal of Scientific Research in Science, Engineering and Technology Volume 9, Issue 4 576-591 doi : https://doi.org/10.32628/IJSRSET
- Amelia, (2019). What Do You Need to Know About UAT Testing? https://wpamelia.com/uat-testing/
- Arora, A., & Kumar, R. (2020). Cloud-based testing frameworks for scalable financial systems. International Journal of Cloud Applications and Computing, 10(3), 22–34.
- Arts, T., Hughes, J., Norell, U., & Svensson, H. (2016). Testing telecom software with Quviq QuickCheck. ACM SIGPLAN Notices, 51(12), 1–6.
- Atalor, S. I. (2019). Federated Learning Architectures for Predicting Adverse Drug Events in Oncology Without Compromising Patient Privacy ICONIC RESEARCH AND ENGINEERING JOURNALS JUN 2019 | IRE Journals | Volume 2 Issue 12 | ISSN: 2456-8880
- Atalor, S. I. (2022). Blockchain-Enabled Pharmacovigilance Infrastructure for National Cancer Registries. International Journal of Scientific Research and Modern Technology, 1(1), 50–64. https://doi.org/10.38124/ijsrmt.v1i1.493
- Atalor, S. I. (2022). Data-Driven Cheminformatics Models for Predicting Bioactivity of Natural Compounds in Oncology. International Journal of Scientific Research and Modern Technology, 1(1), 65–76. https://doi.org/10.38124/ijsrmt.v1i1.496
- Atoum, I., Baklizi, M. K., Alsmadi, I., Otoom, A. A., Alhersh, T., Ababneh, J., ... & Alshahrani, S. M. (2021). Challenges of software requirements quality assurance and validation: A systematic literature review. IEEE Access, 9, 137613-137634.
- Chowdhury, H. A., Bhattacharyya, D. K., & Kalita, J. K. (2018). Differential expression analysis of RNA-seq reads: overview, taxonomy, and tools. IEEE/ACM transactions on computational biology and bioinformatics, 17(2), 566-586.
- Claessen, K., & Hughes, J. (2011). QuickCheck: a lightweight tool for random testing of Haskell programs. Acm sigplan notices, 46(4), 53-64.
- Clarke, C. (nd). THE SOCIAL FOUNDATIONS OF FINTECH. THE SOCIAL FOUNDATIONS OF GLOBAL FINANCE, 111.
- COSO. (2017). Internal control—Integrated framework: Executive summary. Committee of Sponsoring Organizations of the Treadway Commission.
- Ekundayo, F., & Ikumapayi, O. J. (2022). Leadership practices in overseeing data engineers developing compliant, highperformance REST APIs in regulated financial technology environments. Int J Comput Appl Technol Res, 11(12), 566-577.
- El Emam, K., Mosquera, L., & Bass, J. (2020). Evaluating identity disclosure risk in fully synthetic health data: model development and validation. Journal of medical Internet research, 22(11), e23139.
- Erös, E. (2024). On Intelligent Automation Systems: Methods for Preparation, Control, and Testing. Chalmers Tekniska Hogskola (Sweden).
- Fahrezi, M. (2024). A Systematic Literature Review: The Use of Artificial Intelligence and Machine Learning in Financial Risk Management and Predictive Analytics. International Journal of Research and Applied Technology (INJURATECH), 4(2), 60-72.
- Feng, J. (2024). Internal governance, external governance, and corporate strategic decisions (Doctoral dissertation, University of Southampton).
- Gai, K., Qiu, M., & Sun, X. (2018). A survey on FinTech. Journal of Network and Computer Applications, 103, 262–273.
- Garg, R. (2025). User Acceptance Testing (UAT) Checklist and Key Benefits https://www.frugaltesting.com/blog/user-acceptance-testing-uat-checklist-and-key-benefits
- Goncalves, A., Ray, P., Soper, B., Stevens, J., Coyle, L., & Sales, A. P. (2020). Generation and evaluation of synthetic patient data. NPJ Digital Medicine, 3(1), 1–9.
- Harris, W. N. (2011). China Energy: A Crossroads Historiography. T. Marshall L. Rev., 37, 255.
- Idika, C. N. (2023). Quantum Resistant Cryptographic Protocols for Securing Autonomous Vehicle to Vehicle (V2V) Communication Networks International Journal of Scientific Research in Computer Science, Engineering and Information Technology Volume 10, Issue 1 doi : https://doi.org/10.32628/CSEIT2391547
- Idika, C. N., James, U.U, Ijiga, O. M., Enyejo, L. A. (2023). Digital Twin-Enabled Vulnerability Assessment with Zero Trust Policy Enforcement in Smart Manufacturing Cyber-Physical System International Journal of Scientific Research in Computer Science, Engineering and Information Technology Volume 9, Issue 6 doi : https://doi.org/10.32628/IJSRCSEIT
- Idika, C. N., Enyejo, J. O., Ijiga, O. M. & Okika, N. (2025). Entrepreneurial Innovations in AI-Driven Anomaly Detection for Software-Defined Networking in Critical Infrastructure Security International Journal of Social Science and Humanities Research Vol. 13, Issue 3, pp: (150-166), DOI: https://doi.org/10.5281/zenodo.16408773
- Igba, E., Olarinoye, H. S., Ezeh, N. V., Sehemba, D. B., Oluhaiyero, Y. S., & Okika, N. (2025). Synthetic Data Generation Using Generative AI to Combat Identity Fraud and Enhance Global Financial Cybersecurity Frameworks. International Journal of Scientific Research and Modern Technology (IJSRMT) Volume 4, Issue 2, 2025. DOI: https://doi.org/10.5281/zenodo.14928919
- Ijiga, O. M., Balogun, S. A., Okika, N., Agbo, O. J. & Enyejo, L. A. (2025). An In-Depth Review of Blockchain-Integrated Logging Mechanisms for Ensuring Integrity and Auditability in Relational Database Transactions International Journal of Social Science and Humanities Research Vol. 13, Issue 3, DOI: https://doi.org/10.5281/zenodo.15834931
- Ijiga, O. M., Ifenatuora, G. P., & Olateju, M. (2021). Bridging STEM and Cross-Cultural Education: Designing Inclusive Pedagogies for Multilingual Classrooms in Sub Saharan Africa. JUL 2021 | IRE Journals | Volume 5 Issue 1 | ISSN: 2456-8880.
- Ijiga, O. M., Ifenatuora, G. P., & Olateju, M. (2021). Digital Storytelling as a Tool for Enhancing STEM Engagement: A Multimedia Approach to Science Communication in K-12 Education. International Journal of Multidisciplinary Research and Growth Evaluation. Volume 2; Issue 5; September-October 2021; Page No. 495-505. https://doi.org/10.54660/.IJMRGE.2021.2.5.495-505
- Ijiga, O. M., Okika, N., Balogun, S. A., Agbo, O. J. & Enyejo, L. A. (2025). Recent Advances in Privacy-Preserving Query Processing Techniques for Encrypted Relational Databases in Cloud Infrastructure, International Journal of Computer Science and Information Technology Research Vol. 13, Issue 3, DOI: https://doi.org/10.5281/zenodo.15834617
- Imoh, P. O. & Enyejo, J. O. (2025). Analyzing Social Communication Deficits in Autism Using Wearable Sensors and Real-Time Affective Computing Systems, International Journal of Innovative Science and Research Technology Volume 10, Issue 5 https://doi.org/10.38124/ijisrt/25may866
- Imoh, P. O. (2023). Impact of Gut Microbiota Modulation on Autism Related Behavioral Outcomes via Metabolomic and Microbiome-Targeted Therapies International Journal of Scientific Research and Modern Technology (IJSRMT) Volume 2, Issue 8, 2023 DOI: https://doi.org/10.38124/ijsrmt.v2i8.494
- Imoh, P. O., & Idoko, I. P. (2022). Gene-Environment Interactions and Epigenetic Regulation in Autism Etiology through Multi-Omics Integration and Computational Biology Approaches. International Journal of Scientific Research and Modern Technology, 1(8), 1–16. https://doi.org/10.38124/ijsrmt.v1i8.463
- Imoh, P. O., & Idoko, I. P. (2023). Evaluating the Efficacy of Digital Therapeutics and Virtual Reality Interventions in Autism Spectrum Disorder Treatment. International Journal of Scientific Research and Modern Technology, 2(8), 1–16. https://doi.org/10.38124/ijsrmt.v2i8.462
- Israeli, A., Jurgens, D., & Romero, D. (2024). A Test of Time: Predicting the Sustainable Success of Online Collaboration in Wikipedia. arXiv preprint arXiv:2410.19150.
- James, U. U., Idika, C. N., & Enyejo, L. A. (2023). Zero Trust Architecture Leveraging AI-Driven Behavior Analytics for Industrial Control Systems in Energy Distribution Networks, International Journal of Scientific Research in Computer Science, Engineering and Information Technology Volume 9, Issue 4 doi : https://doi.org/10.32628/CSEIT23564522
- James, U. U., Idika, C. N., Enyejo, L. A., Abiodun, K., & Enyejo, J. O. (2024). Adversarial Attack Detection Using Explainable AI and Generative Models in Real-Time Financial Fraud Monitoring Systems. International Journal of Scientific Research and Modern Technology, 3(12), 142–157. https://doi.org/10.38124/ijsrmt.v3i12.644
- Jimmy, F. N. U. (2024). Cyber security vulnerabilities and remediation through cloud security tools. Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023, 2(1), 129-171.
- Jinadu, S. O., Akinleye, E. A., Onwusi, C. N., Raphael, F. O., Ijiga, O. M. & Enyejo, L. A. (2023). Engineering atmospheric CO2 utilization strategies for revitalizing mature american oil fields and creating economic resilience Engineering Science & Technology Journal Fair East Publishers Volume 4, Issue 6, P.No. 741-760 DOI: 10.51594/estj.v4i6.1989
- Kaushik, M., Sharma, R., Peious, S. A., Shahin, M., Yahia, S. B., & Draheim, D. (2021). A systematic assessment of numerical association rule mining methods. SN Computer Science, 2(5), 348.
- Khan, R. A., Khan, S. U., Khan, H. U., & Ilyas, M. (2022). Systematic literature review on security risks and its practices in secure software development. ieee Access, 10, 5456-5481.
- Krishna, K. S. S. S. V. (2025). IT Services.
- Lal, C., & Marijan, D. (2021). Blockchain testing: Challenges, techniques, and research directions. arXiv preprint arXiv:2103.10074.
- Loikkanen, I. (2024). Improving End to End Testing of a Complex Full Stack Software.
- Mangal, A., Goel, D. P., & Kumar, L. (2022). Achieving Revenue Recognition Compliance: A Study of ASC606 vs. IFRS15. IFRS15 (July 20, 2022).
- Mangal, A., Goel, D. P., & Kumar, L. (2022). Achieving Revenue Recognition Compliance: A Study of ASC606 vs. IFRS15. IFRS15 (July 20, 2022).
- Mangal, A., Goel, D. P., & Kumar, L. (2022). Achieving Revenue Recognition Compliance: A Study of ASC606 vs. IFRS15. IFRS15 (July 20, 2022).
- McCallum, B., & McCallum, C. (2022). Revenue Recognition Accounting: Understanding the Impact of ASC 606. McCallum, Brent, and Chloe McCallum.“Revenue Recognition Accounting: Understanding the Impact of ASC, 606, 31-45.
- Mishra, K., & Celestin, P. (2025). IFRS vs. GAAP: How Differences in Accounting Standards Impact Financial Reporting, Cross-Border Investments, and Multinational Decision-Making. Mbonigaba, IFRS vs. GAAP: How Differences in Accounting Standards Impact Financial Reporting, Cross-Border Investments, and Multinational Decision-Making (May 01, 2025).
- Ngai, E. W., Hu, Y., Wong, Y. H., Chen, Y., & Sun, X. (2011). The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature. Decision Support Systems, 50(3), 559–569.
- Ononiwu, M., Azonuche, T. I., & Enyejo, J. O. (2023). Exploring Influencer Marketing Among Women Entrepreneurs using Encrypted CRM Analytics and Adaptive Progressive Web App Development. International Journal of Scientific Research and Modern Technology, 2(6), 1–13. https://doi.org/10.38124/ijsrmt.v2i6.562
- Ononiwu, M., Azonuche, T. I., & Enyejo, J. O. (2025). Analyzing Email Marketing Impacts on Revenue in Home Food Enterprises using Secure SMTP and Cloud Automation International Journal of Innovative Science and Research Technology Volume 10, Issue 6, https://doi.org/10.38124/ijisrt/25jun286
- Ononiwu, M., Azonuche, T. I., Imoh, P. O. & Enyejo, J. O. (2024). Evaluating Blockchain Content Monetization Platforms for Autism-Focused Streaming with Cybersecurity and Scalable Microservice Architectures ICONIC RESEARCH AND ENGINEERING JOURNALS Volume 8 Issue 1
- Ononiwu, M., Azonuche, T. I., Okoh, O. F., & Enyejo, J. O. (2023). AI-Driven Predictive Analytics for Customer Retention in E-Commerce Platforms using Real-Time Behavioral Tracking. International Journal of Scientific Research and Modern Technology, 2(8), 17–31. https://doi.org/10.38124/ijsrmt.v2i8.561
- Parvathinathan, K., Karkala, S., Hossain, S., Krishnapatnam, M., Aggarwal, A., Zahir, Z., ... & Shah, V. (2025). Automated Unit Testing Frameworks for Deep Learning Components in ML Software Stacks.
- Patki, N., Wedge, R., & Veeramachaneni, K. (2016). The synthetic data vault. In 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA) (pp. 399–410). IEEE.
- Rahmah, A. S., Pratama, N. R., Kuswadi, S. A., & Ichsan, M. (2024). The effectiveness of implementing agile project management: A systematic literature review. Global Business & Finance Review (GBFR), 29(6), 170-186.
- Saha, A., & Kumar, M. (2021). Artificial intelligence in software testing: Applications in financial systems. Journal of Software Engineering and Applications, 14(12), 559–572.
- Singh, J. (2024). Applied Data Science and Smart Systems. S. B. Goyal, R. K. Kaushal, N. Kumar, & S. S. Sehra (Eds.). Taylor & Francis Group.
- Singh, S., Sarva, M., & Gupta, N. (2025). Capital market manipulation and regulatory compliance–a bibliometric analysis of scholarly research in the post-2000 era. Qualitative Research in Financial Markets, 17(1), 111-152.
- Sulaiman, N. A., & Kassim, M. (2011, June). Developing a customized software engineering testing for Shared Banking Services (SBS) System. In 2011 IEEE International Conference on System Engineering and Technology (pp. 132-137). IEEE.
- Thakur, A., Bhageerathy, R., Mithra, P., Sekaran, V. C., & Kumar, S. (2025). Diagnosing the Health of Digital Health: Development and Validation of a Fast and Frugal Tree (FFT) Decision Tool for Public Health Supervisors in Low-Resource Settings.
- Ussher-Eke, D., Raphael, F. O., Ijiga, O. M. & Enyejo, J. O. (2025). Enhancing Workforce Morale and Organizational Communication through Sentiment Analysis in HR Feedback and Review Systems International Journal of Social Science and Humanities Research Vol. 13, Issue 3, Page No: 167-180 DOI: https://doi.org/10.5281/zenodo.16568976
- Vassent, C. A. (2025). This Is Why We Can’t Have Nice Things: Performing Justice, Dodging Responsibility—Selective Justice Approaches to Loss and Damage and Cultural Restitution in the European Union.
- Wagenhofer, A. (2014). The role of revenue recognition in performance reporting. Accounting and Business Research, 44(4), 349-379.
- Woungang, I., Dhurandher, S. K., Pattanaik, K. K., Verma, A., & Verma, P. (Eds.). (2023). Advanced Network Technologies and Intelligent Computing: Second International Conference, ANTIC 2022, Varanasi, India, December 22–24, 2022, Proceedings, Part I. Springer Nature.
- Zhang, Y., Xiong, F., Xie, Y., Fan, X., & Gu, H. (2020). The impact of artificial intelligence and blockchain on the accounting profession. Ieee Access, 8, 110461-110477.
Automated User Acceptance Testing (UAT) is becoming a cornerstone in regulated payment systems, where
technical reliability and financial compliance must operate in unison. Traditional manual UAT approaches often fail to
provide the scalability, accuracy, and coverage required to validate complex payment workflows under stringent accounting
standards. This review explores how property-based testing and synthetic data generation can enhance automated UAT
frameworks, offering systematic validation of transaction invariants, expanded scenario coverage, and improved data
privacy protections. A central focus is the integration of International Financial Reporting Standards (IFRS 15) and
Generally Accepted Accounting Principles (ASC 606) through revenue-recognition validation gates, which embed
accounting compliance into testing pipelines. Case studies from banking, FinTech, and payment service providers illustrate
how these methods strengthen auditability, reduce compliance risks, and support transparent financial reporting. Emerging
trends—including the adoption of artificial intelligence, continuous testing in DevOps environments, and cloud-enabled
platforms—are identified as shaping the future of automated UAT. The review concludes that bridging technical testing
with financial governance not only ensures regulatory compliance but also enhances operational resilience, scalability, and
trust in modern payment infrastructures.
Keywords :
Automated user Acceptance Testing (UAT); Regulated Payment Systems; Property-Based Testing; Synthetic Data; Revenue Recognition.