AI-Enhanced Customer Fraud Prevention Strategies

Abstract

Fraud and associated illicit activities that lead to them are gradually becoming an everyday experience. Insurance fraud accounted for the greatest share of fraud referrals received between April and September, at 31 percent. This was followed by banking, at 28 percent, and mortgage fraud at 26 percent. The police reported that there has been an increase in both the volume and complexity of fraud. This sub-sector is the most heavily regulated part of the market, but it was not subject to any Retail Policy Report; hence it seems like an area where an action plan should be developed.

The aim of this essay is to explore the role and effectiveness of fraud prevention strategies and solutions in enhancing customer security, in particular, whether the applications of artificial intelligence have the potential to add value in this increasingly complex system. This will be achieved as applications of technology in tracking present a novel form of obfuscation techniques to evade rigorous prevention while negating customer data care across a distributed environment. A more unassuming goal of this research was to evaluate the impact of incorporating new technological trends such as AI into the efficiency of existing solutions for fraud and AML eradication. The paper intends to provide general views on the field and is presented in six main sections. It starts with the technology trends defining the customer security landscape. The third section covers customer security, including attacks, the impact of attacks, and prevention techniques. The next section, ongoing research in the security of customers, covers the solution landscape. Following that is the expertise of the technology encompassing the capabilities and availability of technology. Then the supporting paper and manual material are presented, which provide a round of information. Finally, the paper concludes with the summary, limitations, and future works and prospects.