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.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

AI Ethics and Bias in Financial Models
Algorithmic Trading and High-Frequency Trading (HFT)
Artificial Intelligence and Beyond
Big Data Technologies in Finance
Blockchain and Cryptocurrencies Risk Assessment
Credit Risk Modeling and Assessment
Derivative Pricing
Fundamentals of Data Analytics and AI
Liquidity Risk Measurement and Management
Machine Learning Algorithms for Financial Modeling
Market Risk Analysis and Value at Risk (VaR) Models
Natural Language Processing (NLP) in Financial Analysis
Operational Risk Management
Portfolio Optimization and Asset Allocation
Probability Theory and Statistical Analysis for Risk Assessment

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Editor/Author Biographies

Mohammad Gouse Galety has been working in CS since 1999. He is now a Professor in the CS department of Samarkand International University of Technology, Samarkand, Uzbekistan. He holds two Ph. D.s in web mining and image processing of CS and two master's degrees in computers. The first master's degree is in computer applications, and the second is in computer science. His research interests span computer and information science, mainly web mining, IoT, and AI. He (co) authorizes over 50 journal papers and international conference proceedings indexed by Springer and Scopus, four patents, and five books. He is a Fellow of the IEEE and ACM. Since 1999, he has served in different national and international organizations like 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, Erbil, Iraq, CUE, Erbil, Iraq. He teaches undergraduate and postgraduate students several courses on computer science and information technology/science engineering.

Dr. 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).

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