https://mail.insyma.org/proceedings/files/original/articles/9. Vietnam_Hue Nguyen Thi.pdf Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Proceedings of the International Symposium on Management (INSYMA) (Vol 22, 2025) Proceedings meta_title AI-Driven Transformation in Finance: A Review of Emerging Trends Author #1 Hue Nguyen Thi Author #2 Mi Nguyen Thi Thao Abstract/Description Artificial Intelligence (AI) significantly transforms the financial sector, facilitating advancements in predictive analytics, process automation, and decision-making. Financial institutions are leveraging AI to analyze vast datasets rapidly, enabling more informed and accurate decision-making. AI models have found applications in a variety of financial domains, including banking, investment management, risk assessment, and regulatory compliance. By utilizing machine learning (ML), deep learning (DL), and natural language processing (NLP), AI enables more accurate predictions of market trends, enhances creditworthiness assessments, detects fraudulent activities, and optimizes investment strategies. This paper reviews the applications of AI in finance, focusing on emerging trends such as generative AI and AI-driven regulatory technology (RegTech). We examine the opportunities AI presents, such as cost reduction, enhanced operational efficiency, and personalized customer services, while acknowledging the challenges including algorithmic bias, data privacy, and regulatory compliance concerns. Ethical considerations play a crucial role in AI deployment, as risks related to discrimination and data security remain significant. Through a synthesis ... keywords a;b;c;d Artificial Intelligence (AI), Finance, Predictive Analytics, Process Automation, Decision-Making, Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Generative AI, Regulatory Technology (RegTech), Algorithmic Bias, Data Privacy, Regulatory Compliance, Ethical Considerations publication_date 2025/06/20 2025/06/20 pdf_url https://insyma.org/proceedings/files/articles/9. Vietnam_Hue Nguyen Thi.pdf abstract_html_url https://insyma.org/proceedings/items/show/ https://insyma.org/proceedings/items/show/474 firstpage 1010 lastpage 1015 issn 3047-857X 3047-857X conference Proceedings of the International Symposium on Management (INSYMA) Proceedings of the International Symposium on Management (Volume 21, 2024) publisher_name Fakultas Bisnis dan Ekonomika, Universitas Surabaya Fakultas Bisnis dan Ekonomika, Universitas Surabaya no article 162 Volume 22 authors Hue Nguyen Thi, Mi Nguyen Thi Thao Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource AI-Driven Transformation in Finance: A Review of Emerging Trends Creator An entity primarily responsible for making the resource Hue Nguyen Thi