Utilizing AI and Machine Learning in Financial Analysis

Machine learning models can imitate the cognitive process by assimilating knowledge from data and employing it to interpret and analyze information. Machine learning methods facilitate the comprehension of vast amounts of data and reveal significant patterns incorporated within it. This data is utilized to optimize financial business operations, facilitate well-informed judgements, and aid in predictive endeavors. Financial institutions utilize it to enhance pricing, minimize risks stemming from human error, mechanize repetitive duties, and comprehend client behavior. Utilizing AI and Machine Learning in Financial Analysis explores new trends in machine learning and artificial intelligence implementations in the financial sector. It examines techniques in financial analysis using intelligent technologies for improved business services. This book covers topics such as customer relations, predictive analytics, and fraud detection, and is a useful resource for computer engineers, security professionals, business owners, accountants, academicians, data scientists, and researchers.

Dina Darwish - EditorProf. Dina Darwish, Vice dean, faculty of computer science and information technology, Ahram Canadian university, Egypt. I obtained my Ph.D from Cairo university at 2009, engineering faculty. I am professor since 2020, also my special domain is artificial intelligence and I have many publications in the following topics, including: Artificial intelligence, wireless ad hoc networks, Internet of things, Big data analytics, Blockchain applications, Cloud computing applications, Web 3 technologies, Chatbots development and others. My email is: dina.g.darwish@gmail.com

Sanjeev Kumar is a professor at School of Hotel Management and Tourism, Lovely Professional University.