<![CDATA[Generative Artificial Intelligence (GenAI) has the potential to transform the financial services sector by advancing financial modelling, risk assessment, fraud detection, and customer service. This study employs Structured Topic Modelling (STM), a machine learning-based method for analysing unstructured text, to uncover key themes from academic and grey literature. Academic discourse focuses on technical applications, including portfolio optimisation and financial forecasting, while grey literature emphasises ethical risks, regulatory challenges, and operational concerns. The findings reveal that GenAI enhances operational efficiency, optimises risk management, and personalises services. However, challenges related to data security, algorithmic bias, and robust ethical governance persist. Policymakers must develop regulatory frameworks that balance innovation and consumer protection, ensuring privacy, transparency, and accountability. The study identifies five key areas for future research: ethical governance, blockchain integration, employment impacts, AI-driven risk management, and personalised financial services. These insights offer a roadmap for financial institutions, policymakers, and technology providers, highlighting GenAI’s transformative potential while addressing ethical considerations for its responsible deployment.]]>
Copyrights © 2026
