Artificial Intelligence and Fraud Detection: An Overview

Abstract

The digital revolution, unquestionably, has changed nations by promoting greater connectivity and quickening development.  The digital revolution is giving nations the means to close infrastructure gaps, take advantage of international opportunities, and promote sustainable growth in a variety of industries, from e-commerce and digital banking. At this critical point, a paradigm shift is needed to develop a new artificial intelligence (AI)-powered line of defense. One of the most important uses of artificial intelligence in the finance industry is fraud detection. The way financial institutions, companies, and organizations detect and stop fraudulent activity has completely changed because of the combination of cutting-edge AI technologies with complex detection methods. The present status, approaches, difficulties, and potential future paths of AI-driven fraud detection systems are all examined in this thorough analysis. A theoretical literature review is conducted to achieve the research's goals and objectives, and a conceptual framework for future study is offered. In the current research, authors consider fraud detection as dependent variable affected by AI. AI-driven systems have proven remarkably successful in detecting fraudulent activity while reducing false positives, from deep learning architectures that capture intricate temporal and spatial patterns to machine learning algorithms that get better over time. AI's involvement in protecting financial systems and lowering losses is growing as financial fraud grows more complex.