An Analysis of Financial Fraud Detection Methods Using Artificial Intelligence

Abstract

Financial fraud is a significant concern in the financial industry, and it has been observed to be dynamic with no discernible trends. There are many fraudulent activities that occur on a daily basis, such as Identity Theft, fraudulent identity impersonation schemes (phishing assaults), and debit and credit card fraud and Debit card frauds, foreclosure and loan scams, fraudulent activities involving fraudulent checks, online fraud, ransomware, and malware frauds. These fraudulent practices can result in considerable financial losses, reputational damage, and a loss of client confidence. Fraudsters take advantage of current technological breakthroughs. One method of tracing fraudulent transactions is to analyse and spot anomalous activity using data mining tools. As technology progresses, Artificial-Intelligence (AI) has emerged as a viable solution for detecting and preventing financial fraud. The author investigates the various steps that may be performed to avoid financial fraud using Artificial-Intelligence in this research study. The author highlights many such uses of machine learning, Deep-learning, as well as Natural-Language-Processing are examples of Artificial-Intelligence techniques that may be used to avoid financial fraud. The author then concludes that NLP is the best AI for fraud detection.