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<p>Using PayAll as a conceptual case study, this article investigates the possible effects of integrating Artificial Intelligence of Things (AIoT) with Decentralised Internet of Things (IoT) network architecture in the context of finance organisations. The author looks at how these technologies might support the expansion of banking systems in underdeveloped countries, tackling issues including inadequate infrastructure, financial inclusion, and operational inefficiencies. The study uses a simulation-based evaluation system that has been validated using established benchmarks from digital financial inclusion datasets (Global Findex, GSMA, IMF), IoT infrastructure performance literature, and mobile money impact studies. In order to determine the primary barriers to financial inclusion and economic progress, the study first examines the state of banking institutions in emerging countries. After that, we examine the technological aspects of decentralised IoT and AIoT, describing their core ideas and possible uses in the financial sector. The study provides a conceptual framework for integrating these technologies into fintech platforms using PayAll as a theoretical case study. Performance estimates are based on simulations calibrated by the literature rather than actual field data. According to the results of our simulation, the availability and effectiveness of financial services in developing nations might be significantly increased by combining decentralised IoT with AIoT. Fintech companies could use decentralised networks to circumvent infrastructure limitations and provide banking services to remote and underserved locations. Better fraud detection, customised financial products, and more precise risk assessment were anticipated thanks to advanced data analysis made possible by AIoT integration. Potential difficulties are also covered in the report, such as legal restrictions, worries about data protection, and the requirement for digital literacy initiatives. We offer answers to these issues, stressing the value of cooperation between international organisations, local governments, and fintech businesses. We specifically note that our results are simulation-based estimates that need to be empirically validated through pilot implementation in the future.</p>

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Leveraging decentralized IoT and AIoT to revolutionize banking in developing countries: a case study of PayAll

  • 期刊论文

  • 发表日期：

    2026年7月24日

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  • Paulin Tchumtcha Wembe

摘要

Using PayAll as a conceptual case study, this article investigates the possible effects of integrating Artificial Intelligence of Things (AIoT) with Decentralised Internet of Things (IoT) network architecture in the context of finance organisations. The author looks at how these technologies might support the expansion of banking systems in underdeveloped countries, tackling issues including inadequate infrastructure, financial inclusion, and operational inefficiencies. The study uses a simulation-based evaluation system that has been validated using established benchmarks from digital financial inclusion datasets (Global Findex, GSMA, IMF), IoT infrastructure performance literature, and mobile money impact studies. In order to determine the primary barriers to financial inclusion and economic progress, the study first examines the state of banking institutions in emerging countries. After that, we examine the technological aspects of decentralised IoT and AIoT, describing their core ideas and possible uses in the financial sector. The study provides a conceptual framework for integrating these technologies into fintech platforms using PayAll as a theoretical case study. Performance estimates are based on simulations calibrated by the literature rather than actual field data. According to the results of our simulation, the availability and effectiveness of financial services in developing nations might be significantly increased by combining decentralised IoT with AIoT. Fintech companies could use decentralised networks to circumvent infrastructure limitations and provide banking services to remote and underserved locations. Better fraud detection, customised financial products, and more precise risk assessment were anticipated thanks to advanced data analysis made possible by AIoT integration. Potential difficulties are also covered in the report, such as legal restrictions, worries about data protection, and the requirement for digital literacy initiatives. We offer answers to these issues, stressing the value of cooperation between international organisations, local governments, and fintech businesses. We specifically note that our results are simulation-based estimates that need to be empirically validated through pilot implementation in the future.