From Sentinel to Saboteur: Asymmetric Impact of Artificial Intelligence on Digital Financial Crimes

Abstract

This study explores the asymmetric impact of artificial intelligence on digital financial crimes across 10 selected economies (the USA, Germany, Japan, India, Brazil, South Korea, the UK, South Africa, Mexico, and Australia). The Quantile-on-Quantile method is applied to reveal nation-specific dynamics and characteristics of each country. The results demonstrate that artificial intelligence significantly amplifies digital financial crimes in the USA, India, Brazil, South Africa, and Mexico. In contrast, Germany, South Korea, and the UK exhibit a decrease in such crimes. However, Japan and Australia exhibit mixed findings, where artificial intelligence both mitigates and facilitates these crimes. The findings call for data-driven policies and aligning artificial intelligence with national goals through refined regulations to maximize benefits and minimize misuse.

Keywords

artificial intelligence digital financial crimes quantile estimation

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