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International Journal of Academic Research in Economics and Management Sciences

Open Access Journal

ISSN: 2226-3624

AI-Centric Fintech Platform for MSMEs: Optimizing Supply Chain Operation and Credit Access in Bangladeshi Emerging Economy

Nargish Fatema, Haslindar Ibrahim, Syed Akhter Hossain, Raquiba Sultana, Thurasamy Ramayah, Khan Md. Mahfuzus Salam

http://dx.doi.org/10.6007/IJAREMS/v15-i1/27898

Open access

Purpose: MSMEs play an important role in emerging economies by contributing a significant part of the GDP and offering jobs to the mass population. Despite their economic significance, they struggle with structural challenges, including inefficient logistics, limited storage, and limited access to finance. The purpose of this study is to introduce a feasible approach to address these challenges by adopting a data-driven, AI-based digital platform. Design/methodology/approach: We propose to bring the MSMEs, manufacturers/suppliers, and financial institutions into a platform where all the purchase transactions are verified by the supplier. Based on reliable transaction information, the platform can evaluate credit scores using AI, and financial institutions can finance the retailers. Through this ecosystem, the financing issue can be resolved, and the supplier can provide frequent delivery support to resolve the product collection and limited storage capacity problem for retailers. It also helps the financier in collecting the debt payments. As a result, the ecosystem allows retailers to increase their regular sales. It’s a three-way win-win model. Findings: The AI model is able to generate credit scores for retailers. With the help of this score, trusted business profiles can be created for retailers. This will eventually assist in clustering all the retailers by various categories. It can finally assist trustworthy MSME businesses to get access to digital finance. The performance of these businesses can be monitored continuously by calculating credit scores per month. Regular financial monitoring can assist in practicing an immediate recovery scheme for any unexpected situation. Research limitations/implications: The model was built using limited parameters. However, more raw data parameters, like repayment frequency, on-time payment, etc., should be collected to obtain optimal results. The number of retail stores should also be increased. The process of collaboration with the financier also needs to be finalized. Practical implications: The pilot implementation of this project is being conducted in Dhaka, Bangladesh. Originality/value: The novelty of this research is to propose a data-driven, AI-based solution for addressing the challenges that MSMEs face in their businesses in a developing country, like Bangladesh.

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Fatema, N., Ibrahim, H., Hossain, S. A., Sultana, R., Ramayah, T., & Salam, K. M. M. (2026). AI-Centric Fintech Platform for MSMEs: Optimizing Supply Chain Operation and Credit Access in Bangladeshi Emerging Economy. International Journal of Academic Research in Economics and Management Sciences, 15(1), 600–615.