TakaGuard: Mitigating Fraud Risks in Bangladesh’s Mobile Financial Services through BERT-based Sentence Classification

Natasha Tanzila Monalisa; Pranta Biswas; Anika Afrin; Shirin Sultana; Shinthi Tasnim Himi

doi:10.2991/978-94-6239-664-7_61

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TakaGuard: Mitigating Fraud Risks in Bangladesh’s Mobile Financial Services through BERT-based Sentence Classification

Authors

Natasha Tanzila Monalisa³, Pranta Biswas¹^{, 2}, Anika Afrin⁴^{, *}, Shirin Sultana¹, Shinthi Tasnim Himi³

¹Department of CSE, Military Institute of Science and Technology, Dhaka, Bangladesh

²Department of ICT, Bangladesh University of Professionals, Dhaka, Bangladesh

³Department of CSE, Jahangirnagar University, Dhaka, Bangladesh

⁴Department of CSE, BRAC University, Dhaka, Bangladesh

^*Corresponding author. Email: anika.afrin@g.bracu.ac.bd

Corresponding Author

Anika Afrin

Available Online 8 June 2026.

DOI: 10.2991/978-94-6239-664-7_61 How to use a DOI?
Keywords: BERT-based Classification; Fraud Detection; Multilingual Text Analysis; Bangla NLP; MFS Fraud Detection
Abstract: The rapid growth of Mobile Financial Services (MFS) has increased concerns about fraud, highlighting the need for language-specific detection systems. While machine learning has advanced digital security, most solutions focus on English, leaving major languages like Bangla underserved. This study introduces TakaGuard, a BERT-based fraud detection framework for SMS written in Bangla, English, and Romanized Bangla. Trained on a curated dataset of 50,000 real-world messages, the system evaluates multiple BERT models, with Bangla-BERT-base achieving the best performance. TakaGuard also includes user-friendly popup alerts to support individuals with limited technical skills. Overall, the framework addresses linguistic and usability gaps, offering a practical solution for reducing fraud in mobile financial services.
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the International Conference on Intelligent Data Analysis and Applications (IDAA 2025)
Series: Advances in Intelligent Systems Research
Publication Date: 8 June 2026
ISBN: 978-94-6239-664-7
ISSN: 1951-6851
DOI: 10.2991/978-94-6239-664-7_61 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Natasha Tanzila Monalisa
AU  - Pranta Biswas
AU  - Anika Afrin
AU  - Shirin Sultana
AU  - Shinthi Tasnim Himi
PY  - 2026
DA  - 2026/06/08
TI  - TakaGuard: Mitigating Fraud Risks in Bangladesh’s Mobile Financial Services through BERT-based Sentence Classification
BT  - Proceedings of the International Conference on Intelligent Data Analysis and Applications (IDAA 2025)
PB  - Atlantis Press
SP  - 891
EP  - 905
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-664-7_61
DO  - 10.2991/978-94-6239-664-7_61
ID  - Monalisa2026
ER  -

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