Fraud Detection in Financial Transaction Using Advanced Analytical Techniques

S. Md Riyaz Naik, Syed Mohammad Arif, Donthala Rakesh, Shaik Khaja Peer, Battu Sai Deepak, Kasetty Sandeep

2025

Abstract

Fraud detection for financial transactions is a challenging issue that is crucial to customers, merchants and financial service providers alike. Rule based detection that is typical cannot keep up with the increasing complexity of fraud. A need to develop robust and scalable systems that exploit state-of-the-art technology such as Artificial Intelligence (AI), Data Analytics (DA) and Machine Learning (ML) for this purpose are the subject of this issue statement. A primary objective is to develop models and algorithms that are able to accurately identify fraudulent transactions while minimizing false positives. This requires analysing large volumes of transaction data in real-time or near-real-time to identify any suspicious trends or anomalies. Iteach8 How do you keep the model updated with latest fraud patterns? Learning and updating must continue since system should also evolve/respond to new types of fraud when they occur. Managing imbalanced datasets, where fraudulent transactions are uncommon in comparison to legal ones, protecting sensitive financial data, and keeping latency low to avoid processing delays are some of the primary issues.

Paper Citation

in Harvard Style

Naik S., Arif S., Rakesh D., Peer S., Deepak B. and Sandeep K. (2025). Fraud Detection in Financial Transaction Using Advanced Analytical Techniques. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 765-769. DOI: 10.5220/0013905200004919

in Bibtex Style

@conference{icrdicct`2525,
author={S. Naik and Syed Arif and Donthala Rakesh and Shaik Peer and Battu Deepak and Kasetty Sandeep},
title={Fraud Detection in Financial Transaction Using Advanced Analytical Techniques},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={765-769},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013905200004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Fraud Detection in Financial Transaction Using Advanced Analytical Techniques
SN - 978-989-758-777-1
AU - Naik S.
AU - Arif S.
AU - Rakesh D.
AU - Peer S.
AU - Deepak B.
AU - Sandeep K.
PY - 2025
SP - 765
EP - 769
DO - 10.5220/0013905200004919
PB - SciTePress