Artificial intelligence systems and fraud investigations

As the economy has shifted to operate primarily on digital transactions, financial fraud has become a multibillion-dollar criminal enterprise. New technologies such as generative AI allow fraudsters to develop new techniques that will make financial fraud even more profitable. In one recent case, a manager initiated a wire transfer at the instructions of his CEO, who gave the instructions on a live video conference call with several other key employees.  As it turns out, every person on the call other than the manager himself was an AI generated stream, and the transaction was fraudulent. To combat the increase in fraud risk, individuals and businesses will need to adopt updated fraud detection strategies. Current top of the line fraud prevention strategies implement Machine Learning and other forms of AI to increase accuracy and automation of their systems.

As a warning, AI should be used as a reference, all functions should be supervised and any data that AI returns should be analysed, especially if they will be used in a litigation setting. 

AI Fraud detection systems use a combination of Machine Learning, Natural Language Processing and Deep learning to combat fraud. Machine learning uses data and algorithms that mimic the way humans learn, this allows AI systems to analyse vast amounts of data and recognise patterns and irregularities. Natural Language processing allows computers to comprehend and communicate in human language giving systems the ability to “text mine”. With text mining capabilities, non-numerical data that may go unnoticed is surveyed as well. Deep learning uses multilayered neural networks to simulate the decision making of the human brain. This ability allows models to improve its ability to analyse data on its own to keep up with the development of new fraud strategies. 

The implementation of AI into Fraud detection and prevention systems can be tricky. A high level of data quality is required, keeping up with data regulation and data privacy laws can be demanding.  Fraudsters develop new methods frequently and AI systems need to continuously be developed by professionals to keep up. The benefits of having AI systems make implementing it worthwhile. Successful systems will have real-time detection and prevention measures, increase the accuracy of fraud detection, cost reduction and scalability, and ultimately an increase in customer trust and satisfaction.

Jim Martin is Managing Director of Cendrowski Corporate Advisors (CCA). Jim specializes in providing comprehensive risk assessments, focusing on the evaluation of operating effectiveness of business processes, internal control structures, and the development of recommendations for improvement.