Shaping Cutting-Edge Technologies and Applications for Digital Banking and Financial Services

Cutting-edge technologies have recently shown great promise in a variety of activities for enhancing the existing services of a bank such as the improvement of transactions, ensuring that transactions are done correctly, and managing records of services of savings accounts, loan and mortgage services, wealth management, providing credit and debit cards, overdraft services and physical evidence as key drivers of bank ecosystem. In the financial world, emerging analytics and prediction tools can be used to analyze and visualize structured data, such as financial market data, and to forecast future trends that can be supported by leaders to make informed decisions about investment strategies.

This book explores the importance of artificial intelligence (AI)-based predictive analytics tools in the financial services industry and their role in combating financial fraud. As fintech continues to revolutionize the financial landscape, it also brings forth new challenges, including sophisticated fraudulent activities. Therefore, this book shares the problem of enhancing fraud detection and prevention through the application of predictive analytics.

This book contributes to a deeper understanding of the importance of predictive analytics in the finance field and its pivotal role in cybersecurity and combating fraud. It provides valuable insights for the financial services industry, researchers, and policymakers, aiming to fortify the security and resilience of financial systems in the face of evolving financial fraud challenges.

Cuurently, AI has replaced recurrent intellectual decisions due to the availability of information and its access. These changes have created a revolution in financial operations resulting in environmental variations in the banking and finance sectors. Likewise, analytics transformed the not only finance field but also banking as it is increasing the transparency of lending-related activities.

In addition, this book provides a set of tools for complex analyses of people-related data and through a variety of statistical analysis techniques ranging from simple descriptive statistics to machine learning, HR analytics enables performance evaluation and increases the transparency of finance transactions as well as the problems, advantages, and disadvantages of new digital transformation. The book is not merely a compilation of technical knowledge; it is a beacon of innovation that beckons readers to envision a future where cutting-edge technologies and finance services intertwine seamlessly.

With its engaging and thought-provoking content, the book leaves an indelible impression, urging readers to embrace the transformative power of technology and embark on a collective mission to unlock the full potential of fintech for the betterment of humanity.

Dr. Alex Khang is a professor in information technology at the Universities of Science and Technology in Vietnam, and the United States; IT Workforce Development Consultant for High-tech Corporations in the USA and Vietnam; AI and data scientist, software industry expert, and the chief of technology officer (AI and Data Science Research Center) at the Global Research Institute of Technology and Engineering, North Carolina, United States. He has more than 28 years of teaching and research experience in information technology (Software Development, Database Technology, AI Engineering, Data Engineering, Data Science, Data Analytics, IoT-based Technologies, and Cloud Computing) at the Universities of Science and Technology in Vietnam, India, and the USA.

He has been the chair session for 20 conferences, keynote speaker for more than 25 international conclaves; an expert tech speaker for 100 seminars and webinars; an international technical board member for 10 international organizations; an editorial board member for more than 5 ISSNs; an international reviewer and evaluator for more than 100 journal papers; an international examiner and evaluator for more than 15 PhD. theses in the computer science field