Data Analytics and AI for Quantitative Risk Assessment and Financial Computation

In today's fast-paced financial landscape, professionals face an uphill battle in effectively integrating data analytics and artificial intelligence (AI) into quantitative risk assessment and financial computation. The constantly increasing volume, velocity, and variety of data generated by digital transactions, market exchanges, and social media platforms offer unparalleled financial analysis and decision-making opportunities. However, professionals need sophisticated AI technologies and data analytics methodologies to harness this data for predictive modeling, risk assessment, and algorithmic trading. Navigating this complex terrain can be daunting, and a comprehensive guide that bridges theory and practice is necessary. Data Analytics and AI for Quantitative Risk Assessment and Financial Computation is an all-encompassing reference for finance professionals, risk managers, data scientists, and students seeking to leverage the transformative power of AI and data analytics in finance. The book encapsulates this integration's theoretical underpinnings, practical applications, challenges, and future directions, empowering readers to enhance their analytical capabilities, make informed decisions, and stay ahead in the competitive financial landscape. The book provides a structured approach that covers foundational topics in quantitative risk assessment, data analytics, and AI, providing a roadmap for professionals to navigate the complexities of integrating AI and data analytics into financial practices. The book explores specific applications and methodologies, including machine learning algorithms for economic modeling and AI-driven strategies for risk management, providing readers with practical insights and strategies for success in the AI-driven financial future. With this book as a guide, professionals can confidently embrace the power of AI and data analytics to stay ahead in the ever-evolving economic landscape.

Mohammad Gouse Galety , a seasoned professional in computer science, is currently a Professor at the computer science department of Samarkand International University of Technology, Samarkand, Uzbekistan. His research interests encompass a wide range of computer and information science, focusing on Web Mining, Computer Vision, IoT, Machine Learning, and Artificial Intelligence. His impactful research has led to the (co) authorship of several journal papers and international conference proceedings indexed by Springer, Web of Science, and Scopus, holding four patents and writing six books. His standing in the academic community is further solidified by his role as a Fellow of the IEEE and ACM.With a career spanning over two decades, Mohammad Gouse Galety has served in many national and international organizations, solidifying his expertise in the field. His teaching experience includes roles at Sree Vidyanikethan Degree College, India; Emeralds Degree College, Tirupati, India; Brindavan College of Engineering, India; Kuwait Educational Center, Kuwait; Ambo University, Ethiopia; Debre Berhan University, Ethiopia; Lebanese French University, Iraq; and Catholic University in Erbil, Iraq. He imparts his knowledge to undergraduate and postgraduate students, teaching various courses in computer science and information technology/science engineering.

Jimbo H. Claver (Professor, PhD Supervisor, HoD, and JSPS Fellow) received in 2001 the Ph.D. degree in Applied Mathematics and Statistics from the Moscow State University named Lomonosov, and he did post-doctorate studies with the Institute of Statistical Mathematics in Tokyo, Japan. Currently, he is a Full Professor and Head of the Department of Applied Mathematics with the Samarkand International University of Technology (SIUT). His previous positions include Head of the Department of Mathematics at the American International University (Kuwait), - Professor of Applied Mathematics at the American University of Afghanistan, Associate Professor of Applied Mathematics with the Nara Institute of Science and Technology, Nara (Japan), Visiting Professor of Applied Mathematics with Waseda. University (Japan), Assistant Professor of Mathematics and Statistics with Lakeland College, Tokyo (Japan), Senior Lecturer with the University of York (United Kingdom), Lecturer with Sino British College-Shanghai Institute of Science and Technology (China), visiting research fellow with the Swiss Banking Institute (Zurich) and visiting fellow Morehouse College, Atlanta, Georgia (USA). His research focuses on system modeling, predictive analysis, system control, stochastic processes, applied probability, applied statistics, data analysis, quantitative finance, and actuary. In addition, he serves as editor and reviewer of several international journals; he is a member of the International Mathematical Union (IMU), Japan Mathematical Society (JMS), Japan Statistical Society (JSS), and Moscow Mathematical Society (MMS). He has published four books and numerous scientific papers in pure, applied mathematics, applied statistics, quantitative finance, quantitative risk management, and data analysis in peer-reviewed journals and conference proceedings. He also supervised countless MSc, PhD, and MBA students.

Narasimha Rao Vajjhala is working as the Dean of the Faculty of Engineering and Architecture at the University of New York Tirana, Albania. He had previously worked as the Chair of Computer Science and Software Engineering programs at the American University of Nigeria. He is a senior member of ACM and IEEE. He is the Editor-in-Chief (EiC) of the International Journal of Risk and Contingency Management (IJRCM). He is also a member of the Risk Management Society (RIMS), and the Project Management Institute (PMI). He has over 23 years of experience teaching programming and database-related courses at both graduate and undergraduate levels in Europe and Africa. He has also worked as a consultant in technology firms in Europe and has experience participating in EU-funded projects. He has completed a Doctorate in Information Systems and Technology (United States); holds a Master of Science in Computer Science and Applications (India), and a Master of Business Administration with a specialization in Information Systems (Switzerland).

Arul Kumar Natarajan currently serves as an Assistant Professor in the Department of Computer Science at the Samarkand International University of Technology in Uzbekistan. He earned his Doctor of Philosophy degree in Computer Science from Bharathidasan University, India, in 2017. Concurrently, he is engaged in postdoctoral research in Generative AI for Cybersecurity at the Singapore Institute of Technology, Singapore. Throughout his 14-year teaching career, Dr. Arul has held esteemed positions at various institutions, including Christ University, Bishop Heber College in India, and Debre Berhan University in Ethiopia. Dr. Arul has made significant contributions to academia, specializing in cybersecurity and artificial intelligence, as evidenced by his portfolio of scholarly works. He has authored 52 peer-reviewed and internationally indexed publications and delivered 35 conference presentations. Additionally, he has edited and published 04 books with IGI Global, USA, which are indexed in Scopus and focus on Artificial Intelligence and Cybersecurity. He also has 04 more books in the processing stage with IGI Global, Wiley, and Springer. In addition to his academic pursuits, Dr. Arul is a prolific innovator. He has 17 patents granted in India and 1 granted in the United Kingdom, spanning diverse fields such as communication and computer science. His latest work involves 1 copyrighted research (Govt. of India) in Artificial Intelligence and Machine Learning, specifically focused on segmenting, classifying, and tracking issue nuclei in images. Dr. Arul also exhibits notable proficiency in networking and cybersecurity, having completed the CCNA Routing and Switching Exam from CISCO and the Networking Fundamentals exam from Microsoft. He continues to demonstrate a strong interest in Generative AI for Cybersecurity.