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1712082 Vol 9 · Issue 5 Download Paper

Fraud Detection Analysis Using Machine Learning

Harish Ramakrishnan Rakesh Darji Suyog Kevane Sunil Ghadigaonkar Siddhikesh Warandekar Rajesh Kamble Akshay Kamble Shankar S

Subject area: Science,Engineering and Technology  ·  Area of research: Artificial Inteliigence and Machine Learning

DOI: 10.64388/IREV9I5-1712082

Abstract

Fraud detection which is one of the most important applications of machine learning in finance and e-commerce, insurance, and other industries. It helps organizations identify suspicious activities, such as credit card fraud, identity theft, or fake claims, by analyzing data patterns and detecting anomalies that differ from normal behavior.

Keywords

Fraud Dectection pattern, Algorithmic pattern, Machine learning, Artificial intelligence.

References

[1] F. Carillo, Y. A. Le Borgne, and G. Bontempi: Their work on combining unsupervised and supervised learning for credit card fraud detection is highly regarded.

[2] M. S. Sahin, H. Huang, and J. Kim: These authors have published influential articles on financial fraud detection using machine learning models, with a high number of citations.

[3] Paolo Vanini et al.: Their work explores the transition from anomaly detection to comprehensive risk management in online payment fraud.

[4] Varun Kumar et al.: Authors of a key article in Expert Systems With Applications titled "Credit-Card Fraud Detection Using Machine Learning Algorithms" (2020). 

[5] Manava Daria, Manthan S., et al. are primary authors of the book chapter "Machine Learning for Fraud Detection and Financial Crimes" within the 2025.

[6] Papadakis, Stylianos, Alexandros Garefalakis, and Christos Lemonakis are editors of the book Machine Learning Applications for Accounting Disclosure and Fraud Detection, published by IGI Global

How to cite this paper

Harish Ramakrishnan, Rakesh Darji, Suyog Kevane; Sunil Ghadigaonkar, Siddhikesh Warandekar; Rajesh Kamble, Akshay Kamble; Shankar S "Fraud Detection Analysis Using Machine Learning" Iconic Research And Engineering Journals Volume 9 Issue 5 2025 Page 1191-1195 https://doi.org/10.64388/IREV9I5-1712082
Harish Ramakrishnan, Rakesh Darji, Suyog Kevane; Sunil Ghadigaonkar, Siddhikesh Warandekar; Rajesh Kamble, Akshay Kamble; Shankar S "Fraud Detection Analysis Using Machine Learning" Iconic Research And Engineering Journals, vol. 9, no. 5, Nov. 2025, doi: https://doi.org/10.64388/IREV9I5-1712082
Harish Ramakrishnan, Rakesh Darji, Suyog Kevane; Sunil Ghadigaonkar, Siddhikesh Warandekar; Rajesh Kamble, Akshay Kamble; Shankar S (2025). Fraud Detection Analysis Using Machine Learning. Iconic Research And Engineering Journals, 9(5). doi: https://doi.org/10.64388/IREV9I5-1712082
Harish Ramakrishnan, Rakesh Darji, Suyog Kevane; Sunil Ghadigaonkar, Siddhikesh Warandekar; Rajesh Kamble, Akshay Kamble; Shankar S "Fraud Detection Analysis Using Machine Learning" Iconic Research And Engineering Journals, vol. 9, no. 5, Nov. 2025. Crossref, https://doi.org/10.64388/IREV9I5-1712082
@article{1712082,
      author = {Harish Ramakrishnan, Rakesh Darji, Suyog Kevane; Sunil Ghadigaonkar, Siddhikesh Warandekar; Rajesh Kamble, Akshay Kamble; Shankar S},
      title = {Fraud Detection Analysis Using Machine Learning},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {5},
      pages = {1191-1195},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1712082.pdf},
      abstract = {Fraud detection which is one of the most important applications of machine learning  in finance and e-commerce, insurance, and other industries. It helps organizations identify suspicious activities, such as credit card fraud, identity theft, or fake claims, by analyzing data patterns and detecting anomalies that differ from normal behavior.},
      keywords = {Fraud Dectection pattern, Algorithmic pattern, Machine learning, Artificial intelligence.},
      month = {November},
      doi = {https://doi.org/10.64388/IREV9I5-1712082}
  }