FRAUD DETECTION AND PREVENTION IN A DIGITAL ECONOMY

ABSTRACTS

This study evaluate the impact of fraud detection and prevention in a digital economy, focusing on the use of artificial intelligence, machine learning, robo advisors and blockchain to detect and prevent fraud . By addressing key research questions, this research aims to determine how the application of artificial intelligence, machine learning, blockchain and robo advisors impact the effectiveness of fraud detection and prevention in a digital economy. The study population consists of all auditors working in an audit firm in Benin city Edo state, with a sample size of 100 auditors within benin city picked at random.Utilizing a stratified sampling technique, the method of data collected was a primary source of data by distributing questionnaires to auditors. The data analysis is conducted through the ordinary least square method to ensure robust and empirical results. The research findings indicate that artificial intelligence and blockchain has a negative and insignificant relationship with fraud detection and prevention in a digital economy, recommended that management conduct a thorough review of how artificial intelligence and blockchains are currently being implemented and addressing any inefficiencies or implementation issues.from our findings, machine learning has a significant relationship with fraud detection and prevention in a digital economy it therefore recommends that the acquisition of machine learning solution that can analyze large volume data and identify complex fraud patterns should be considered.interestingly, robo advisors has a positive insignificant relationship with fraud detection and prevention in a digital economy therefore recommending that managers should evaluate and determine the specific conditions under which robo advisors can be most effective.