This research delves into integrating Natural Language Processing (NLP) and Generative AI within Enterprise Resource Planning (ERP) systems to bolster fraud prevention measures. The study commences by thoroughly mapping the fraud tree taxonomy with existing ERP applications to identify areas susceptible to fraudulent activities, encompassing corruption, asset misappropriation, and financial statement fraud. The research proposes the utilisation of specific NLP and Generative AI APIs tailored to address these areas, effectively building upon these identified vulnerabilities. By establishing standardised criteria for API development, the research provides a comprehensive roadmap for the accounting and finance profession to adopt and implement these advanced technologies to combat fraud more efficiently. The suggested roadmap encompasses crucial stages, including evaluating organisational requirements, assessing API providers, seamlessly integrating APIs into ERP systems, conducting thorough testing, and establishing robust monitoring and governance mechanisms. The findings underscore the tremendous potential of NLP and Generative AI in fortifying fraud prevention endeavours within ERP systems while highlighting the interdisciplinary nature of this research, which amalgamates insights from ERP systems, fraud detection, NLP, and Generative AI. The study also encourages future empirical investigations to validate and refine the proposed solutions within real-world contexts.