Comprehensive review of financial fraud detection techniques
Author(s):
Bhavikkumar Jain, Chirag Nadam, Rishabh Kukhrania, Mohammed Moinuddin sheikh, Rakshith Raagavindra Balaji, Saritha S R , Sunitha B K
Keywords:
Financial fraud detection, machine learning, deep learning, ensemble methods, challenges, advancements, strategies, regulatory compliance, interdisciplinary collaboration, risk management.
Abstract
Financial fraud poses a serious threat to the stability and integrity of global financial systems and requires effective detection and prevention measures. This review examines financial fraud detection developments, challenges and strategies to analyse the literature on machine learning techniques, deep learning innovations, and clustering methods through mixed methods, research explores how fraud the detection methods are effective , identify challenges , and find solutions that can solve emerging fraud threats and new advanced technologies in improving the detection of promising methods, while challenges reside that data imbalances and adversarial attacks require the adoption of effective risk management Assessment of consumer interest in preventing and protecting against financial fraud intersectoral cooperation, regulatory and compliance measures , emphasize the importance of need ongoing innovation and fraud detection for analysts, practitioners, policy makers and regulators to improve, fraud It also recommends promoting accountability, and enabling economic reform programs
Article Details
Unique Paper ID: 162898

Publication Volume & Issue: Volume 10, Issue 11

Page(s): 328 - 332
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