Leveraging Maching Learning in Financial Fraud Forensics in the Age of Cybersecurity

Authors

Md. Ariful Haque, Old Dominion University
Sachin Shetty, Old Dominion UniversityFollow

Document Type

Book Chapter

Publication Date

2022

DOI

10.4018/978-1-7998-8386-9.ch010

Publication Title

Technologies to Advance Automation in Forensic Science and Criminal Investigation

Pages

220-249

Abstract

Financial sectors are lucrative cyber-attack targets because of their immediate financial gain. As a result, financial institutions face challenges in developing systems that can automatically identify security breaches and separate fraudulent transactions from legitimate transactions. Today, organizations widely use machine learning techniques to identify any fraudulent behavior in customers' transactions. However, machine learning techniques are often challenging because of financial institutions' confidentiality policy, leading to not sharing the customer transaction data. This chapter discusses some crucial challenges of handling cybersecurity and fraud in the financial industry and building machine learning-based models to address those challenges. The authors utilize an open-source e-commerce transaction dataset to illustrate the forensic processes by creating a machine learning model to classify fraudulent transactions. Overall, the chapter focuses on how the machine learning models can help detect and prevent fraudulent activities in the financial sector in the age of cybersecurity.

Rights

© 2022 IGI Global. All rights reserved.

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Post the final typeset PDF (which includes the title page, table of contents and other front materials, and the copyright statement) of their chapter or article (NOT THE ENTIRE BOOK OR JOURNAL ISSUE), on the author or editor's secure personal website and/or their university repository site.

Original Publication Citation

Haque, M. A., & Shetty, S. (2022). Leveraging machine learning in financial fraud forensics in the age of cybersecurity. In C.-H. Chen, W.-C. Yang, & L. Chen (Eds.), Technologies in advance automation in forensic science and criminal investigation (pp. 220-249). IGI Global. https://doi.org/10.4018/978-1-7998-8386-9.ch010

ORCID

0000-0003-1306-1913 (Haque), 0000-0002-8789-0610 (Shetty)

Repository Citation

Haque, Md. Ariful and Shetty, Sachin, "Leveraging Maching Learning in Financial Fraud Forensics in the Age of Cybersecurity" (2022). VMASC Publications. 108.
https://digitalcommons.odu.edu/vmasc_pubs/108