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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM63576

AI For Fraud Detection In Financial Transaction

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM63576

Volume:

10 |

5 |

May 2026

Pages:

1-6

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

APM

ANUSHA P M

Master of Computer Applications

Bapuji Institute of Engineering and Technology

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RN

RASHMI N

Master of Computer Applications

Bapuji Institute of Engineering and Technology

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Abstract

In today’s digital world most people use online banking mobile wallets and credit cards to make financial transactions. they have also increased scams. Detecting such fraudulent transactions quickly is very important to protect customers and financial institutions from loss. This project “AI for Fraud Detection in Financial Transactions” aims to develop to automatically activities and generate the reports and recommendation to overcome from the frauds analyses large sets of transaction data and identifies unusual For example if a customer suddenly makes a large purchase in a new location odd time the system can recognize it as suspicious and alert the bank immediately. The project is designed with three main components: an API and Server Layer for processing real-time fraud detection. The AI is using past transaction data so it can learn the difference between normal and fraudulent transactions.

KEYWORDS

KEYWORDS: Artificial Intelligence Fraud Detection Financial Transactions Data Analysis Security Risk Detection

Cite This Article

ANUSHA P M, RASHMI N, "AI For Fraud Detection In Financial Transaction," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 5, pp. 1-6, May 2026.

Full Article/Conclusion

It is an effective remedy offered by an AI- based fraud prevention system in relation to financial transaction fraud detection in the real -time environment. As a measure of identifying the irregular trends that could attract the attention of fraud in the transaction additionally the system considers a massive quantity of highly valuable data in the transaction. Experimental results shows that the model achieves an accuracy of approximately 90%–95%.  

References

1. Adhikari, P., Hamal, P., & Baidoo Jnr, F. (2024). Fraud using Artificial intelligence in detection: Revolutionizing financial security. Journal of International Science and Research Archive, 13(1), 1457–1472. https://doi.org/10.30574/ijsra.2024.13.1.18 60   2.   Sarna, N. J., Rithen, F. A., Jui, U. S., Belal, S., Al Amin, Kabir Oishee, T., & Islam, A. K. M. M. (2025). AI driven fraud detection models in financial networks: A comprehensive systematic review. IEEE Access,         13,       141204–1412xx. https://doi.org/10.1109/ACCESS.2025.35960 60  3.    Sai, Das, and Chaithanya Vamshi Explainable AI-Driven Financial Transaction Fraud Detection Using Machine Learning and Deep Neural Networks, Debashish and Elmitwally, Nouh and Elezaj, Ogerta and Islam, Md Baharul. Available at SSRN: https://ssrn.com/abstract=4439980 or http://dx.doi.org/10.2139/ssrn.4439980   4.   Ali, A. H., & Hagag, A. A. (2024). An enhanced AI-based model for financial fraud detection. Journal of International Advanced and Applied Sciences, 11(10), 114–121. https://doi.org/10.21833/ijaas.2024.10.013    5.   Md Mainul Islam, Ismoth Zerine, Md Arifur Rahman, Md Saiful Islam, & Md Yousuf Ahmed. (2024). AI- Powered Financial Fraud DetectionTransactions –Using a Machine Acquiring knowlwdge and deep Learning to Detect Anomalies and Fraudulent Behaviour in Banking and E-Commerce Transactions. https://ijcnis.org/index.php/ijcni s/article/view/8167 8. Bello O.A., Folorunso A., Ejiofor O.E., Budale F.Z., Adebayo K., and Babatunde O.A. (2023) Methods of Machine Learning for Improving Financial Fraud Prevention Transactions, International Journal of Technology for management, Vol.10, No 1, pp.85-109 https://www.researchgate.net/profile/Oluwab usayo- Bello/publication/381548533_Machine_Lear ning_Approaches_for_Enhancing_Fraud_Pre vention_in_Financial_Transactions/links/667 364938408575b837957a6/Machine- Learning-Approaches-for-Enhancing-Fraud- Prevention-in-Financial-Transactions.pdf .  6.   Tambi, V. K. (2022). AI-proweredReal- Time financial transaction fraud detection. Journal of International Research in Electronics and Computer Engineering (IJRECE), 10(4), 148–156. https://philarchive.org/archive/VARAFD-2   7.   . Raibagi, P. S., & Shwetha, S. (2025). Artificial intelligence and financial fraud detection: A review paper. International Journal of Advanced Research in Science, Communication and Technology (IJARSCT), 5(7). https://www.ijarsct.co.in/Paper26801.pdf

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Publication Date

5/22/2026

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Double-Blind Peer Review

Review Rounds: 2

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