| Issue |
EPJ Web Conf.
Volume 369, 2026
4th International Conference on Artificial Intelligence and Applied Mathematics (JIAMA’26)
|
|
|---|---|---|
| Article Number | 02015 | |
| Number of page(s) | 13 | |
| Section | XAI and Data-Driven Optimization in Energy, Environment, and Economic Systems | |
| DOI | https://doi.org/10.1051/epjconf/202636902015 | |
| Published online | 13 May 2026 | |
https://doi.org/10.1051/epjconf/202636902015
Leveraging Remittance-based financial inclusion and explainable segmentation for product design: Testing explainable clustering/credit models
1 Karakalpak State University named after Berdakh
2 Tashkent State Transport University
3 Khorezm Regional Center for Pedagogical Skills
4 Tashkent University of Architecture and Civil Engineering
5 Termez University of Economics and Service
6 Kimyo International University in Tashkent
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Published online: 13 May 2026
Abstract
The inter-relationship between the migrant worker and his/her household beneficiaries is vital in ensuring the sustainability in financial product adoption. Hence, this research aims at explaining the segmentation logic and credit modelling adopted by the financial institutions in remittance corridors to enhance product design and exploring the challenges that faced by the providers in implementing these clustering and credit models in real market settings. The present study aims to determine the influence of remittance behaviour patterns on financial inclusion outcomes from the perspective of a group of selected remittance-receiving households. To analyse the data, lexicon-based sentiment analysis and regression analysis were carried out to identify significant predictors which explain several dimensions of customer creditworthiness. For this purpose, the present study employed a quantitative research methodology based on clustering and sentiment analysis along with analytic hierarchy process. As the findings confirmed that the explainable clustering model (ECM) matters in determining customers’ credit access (CA), it is a managerial implication (MI) for financial service providers to align themselves with the behavioural segments the market requires to improve customers’ financial stability and inclusion, which in turn increase the performance of financial products. The findings encourage the financial institutions to establish inclusive product strategies that will impacted positively on customers’ financial resilience for the benefits of the community so that their long-term financial inclusion would be achievable. Generally, remittance flows and explainable segmentation models are the primary contributors to the sustainability of the financial ecosystem.
Key words: Remittance-based financial inclusion / Explainable clustering model / Credit access modeling / Financial literacy / Sentiment analysis
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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