AI’s Bipolar Effect on Mitigating and Motivating Frauds

Abstract

In the time of digital innovation, Artificial Intelligence (AI) stands at the forefront, signaling new capabilities in fraud management but also new vulnerabilities. This paper aims to dissect AI's paradoxical influence on fraud, portraying its roles in both promoting and mitigating fraudulent activities. The research seeks to bridge the gap in understanding the dual nature of AI, highlighting the need for ethical and regulatory frameworks to traverse the complications AI introduces into fraud detection and prevention. Utilising secondary data from Google News and academic databases with the keyword 'AI fraud,' this study adopts a keyword-based analysis to sift through the most relevant literature. The approach is designed to capture a comprehensive snapshot of the current discourse, underlining the bipolar impact of AI on fraud. The analysis reveals AI's significant potential in enhancing fraud detection systems through rapid data analysis and pattern recognition. However, AI technologies can be exploited to facilitate sophisticated fraud schemes. The study underscores an urgent need for evolving practices and policies that counteract AI's potential for misuse, weighing in the emerging concept of self-regulatory AI systems as a promising direction for future research. This paper contributes insights into the dualistic role of AI in fraud, adding depth to the discourse on its implications for security, ethical considerations, and regulatory challenges. It advocates for a balanced perspective on AI's capabilities.