Externally indexed torrent

If you are the original uploader, contact staff to have it moved to your account

Textbook in PDF format

The convergence of Artificial Intelligence (AI) and Financial Technology (Fintech) has ushered in a new era of innovation in the finance ecosystem, particularly within the context of the digital gig economy. This emerging trend has created a unique set of challenges and opportunities, which AI and Fintech are poised to address. This book explores how the convergence of these cutting-edge technologies is reshaping the financial landscape, especially related to the way people work and earn in the gig economy, and examines the rise of the digital gig economy and its impact on the traditional workforce.
Synergy of AI and Fintech in the Digital Gig Economy presents the key advancements in AI and Fintech, how they are disrupting traditional financial systems, and how AI-powered tools and platforms are streamlining financial processes, enhancing decision-making, and providing personalized services to individuals and businesses. The book explores how the synergy of AI and Fintech is advancing financial inclusion and looks at how these technologies are providing previously underserved populations with access to financial services and empowering them to participate in the global economy. Highlights include how AI and Fintech are revolutionizing risk assessment and management in the financial sector and discuss the use of advanced algorithms to detect fraud, assess creditworthiness, and mitigate financial risk more effectively. The book also addresses the regulatory challenges and ethical considerations arising from the integration of AI and Fintech and discusses the need for responsible AI and data privacy to ensure sustainable development. Insights, case studies, and practical examples provided in the book show how AI and Fintech are driving transformative changes and represent an area of significant interest and importance in the realm of finance and technology.
Artificial Intelligence (AI) refers to the simulation of human intelligence in machines, enabling them to perform tasks typically requiring human intelligence, such as learning, reasoning, problem?solving, and decision?making. AI systems use algorithms and large datasets to recognize patterns, make predictions, and improve their performance over time. ML is a subset of AI focused on the development of algorithms that enable machines to learn from and make predictions or decisions based on data. ML algorithms use statistical techniques to allow computers to improve their performance on a specific task through learning from data, without being explicitly programmed. ML is the core technology that drives many AI applications, as it provides systems the ability to adapt and improve with experience. In recent years, the integration of Artificial Intelligence (AI) and Machine Learning (ML) has emerged as a game?changer in fintech. AI?powered chatbots, robo?advisors, and fraud detection systems have revolutionized customer service, investment management, and risk mitigation in the financial industry.
Generative AI, particularly in the form of large language models, represents a new frontier in computing. What sets it apart as a potential killer app is its ability to act as an intermediary between users and generic applications, thereby facilitating personalized computing. Imagine the power of an AI model that understands your unique needs, habits, and preferences. By simply conversing with this AI in plain English, you can tailor a generic application to meet your specific needs without any programming knowledge. This form of personalization is groundbreaking it not only makes technology an extension of oneself but also democratizes the personalization process. The user can ‘program’ applications by merely describing what they want, turning a generic app into a personalized tool. This is akin to having a ‘robotic extension’ of yourself that understands you and automates tasks according to your unique needs, all without requiring a deep understanding of programming. In summary, the integration of Large Language Models with robotic technology could indeed serve as the “killer app” that makes robotics a universally accessible and functional technology. The natural, intuitive interface provided by generative AI could be the missing link that brings robots out of factories and specialized settings and into everyday life.
Written for students, scholars, lecturers, researchers, scientists, experts, specialists, and engineers, this book represents an area of significant interest and importance in the realm of finance and technology. Real-world examples and contributions from industry experts give readers a comprehensive understanding of this hot trending topic