Abstract Financial fraud cases in the United States have seen a marked increase not only in their magnitude but also in their complexity due to several reasons including accelerated digitalization, growth of online financial institutions, and highly complex approaches employed by cybercriminals. However, the use of traditional methods for detecting fraud, which involve rule-based and reaction-based systems, appears inadequate for dealing with multi-modal modern fraud patterns. In this respect, this paper discusses how artificial intelligence (AI) can change the existing paradigms in finance by providing opportunities for efficient fraud detection based on data-driven approaches and conducted in real time. Multimodal fraud prevention strategies emerge as another area of considerable importance since they combine different kinds of information sources in order to make a comprehensive assessment of risks. The research shows that the use of AI contributes not only to enhanced capabilities to detect fraud but can also result in major cost savings and higher levels of consumer confidence. Additionally, it is expected that with the broad adoption of AI technology, trillions of dollars worth of fraud will be saved in the future, allowing the USA to become a leading country in the sphere of financial technology innovations. Nevertheless, several obstacles should be taken into account when using AI for fraud protection purposes.
Isaias Davis Robleto Sanchez (Thu,) studied this question.