1 Student, Business Analytics, Trine University, Phoenix, Arizona, USA.
2 Professor, Business Administration Management, Trine University, Phoenix, Arizona, USA.
3 Student, Information Technology, Washington University of Science and Technology, Virginia, USA.
Research Article
World Journal of Advanced Research and Reviews, 2024, 24(03), 1032-1041
Received on 31 October 2024; revised on 09 December 2024; accepted on 11 December 2024
This research paper explores in depth on enhanced fraud detection methodologies in order to enhance security of business on financial transactions using AI, machine learning and blockchain technologies. Based on a set of financial transactions the paper identifies the pattern of frauds and measures the efficiency of various anti-fraud measures. The results thus show that AI and machine learning enhance the level of accuracy of the detection of fraud while at the same time reducing the number of false positives. These are suggested to be implemented with existing systems in the following effective manner: The findings of this work can help organizations interested in further upgrading their security and counteracting new fraud strategies. The study thus highlights the need for, and value of obedience to, frequent checks and training of employees and most importantly staying in compliance with financial laws. The last section of the work is focused on the set of recommendations for future research pertinent to the development of more sophisticated methods for fraud identification within various fields combined with an introduction to quantum computing
Fraud Detection; Blockchain Technology; Artificial Technology and Fraud Prevention JEL Specification: G32; G34; G38; M42 and K22
Preview Article PDF
MD SULTANUL AREFIN SOURAV, LISBETH MERRETT, JAFRIN REZA, TANVIR RAHMAN AKASH and K M YAQUB ALI. Fortifying Financial Integrity: Advanced Fraud Detection Techniques for Business Security. World Journal of Advanced Research and Reviews, 2024, 24(3), 1032-1041. Article DOI: https://doi.org/10.30574/wjarr.2024.24.3.3777