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Integrating Artificial Intelligence (AI) presents immense opportunities and daunting challenges in the rapidly evolving finance landscape as AI-driven algorithms and models revolutionize decision-making and enhance efficiency, concerns about bias, ethics, and security loom. Financial institutions must navigate these complexities responsibly while leveraging AI's potential to innovate and thrive. Risks and Challenges of AI-Driven Finance: Bias, Ethics, and Security guides this dynamic environment. Written for professionals, researchers, policymakers, and students, this book comprehensively explores AI's impact on finance. It delves into the intricacies of bias in algorithms, ethical frameworks, cybersecurity, and regulatory compliance, offering actionable insights to address these critical issues.
This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
Neuromarketing plays a significant role in sustainable finance by tapping into the emotional and cognitive factors that influence investor decisions regarding socially and environmentally responsible investments. It helps financial institutions understand how individuals respond to sustainability messages, enabling them to craft more persuasive campaigns that resonate with investors’ values. By leveraging insights into behavior and decision-making processes, neuromarketing enhances the appeal of sustainable finance, encourages greener investment choices, and helps align financial practices with the growing demand for ethical, long-term impact solutions. Neuromarketing's Role in Sustainable Finance explores the intersection of neuromarketing and sustainable finance, revealing how insights from cognitive neuroscience can drive environmentally responsible investment behaviors. It examines subconscious factors influencing consumer decisions toward green investments, offering theoretical frameworks and practical applications to understand and promote ethical financial choices. Covering topics such as behavioral finance, environmental awareness, and investor patterns, this book is an excellent resource for scholars, researchers, financial professionals, marketers, business professionals, academicians, graduate and postgraduate students, and more.
Integrating Artificial Intelligence (AI) presents immense opportunities and daunting challenges in the rapidly evolving finance landscape as AI-driven algorithms and models revolutionize decision-making and enhance efficiency, concerns about bias, ethics, and security loom. Financial institutions must navigate these complexities responsibly while leveraging AI's potential to innovate and thrive. Risks and Challenges of AI-Driven Finance: Bias, Ethics, and Security guides this dynamic environment. Written for professionals, researchers, policymakers, and students, this book comprehensively explores AI's impact on finance. It delves into the intricacies of bias in algorithms, ethical frameworks, cybersecurity, and regulatory compliance, offering actionable insights to address these critical issues.
The global economy is undergoing profound shifts, powered by technological advancements and financial innovations, reshaping the role of finance in ways we've never seen before. As these forces reshape the world of finance, it becomes increasingly essential for academic scholars, practitioners, and future finance professionals to stay ahead of the curve, understanding the latest developments and trends. The problem is that finance education and practice often struggle to keep pace with these transformative changes. Standard textbooks and curricula tend to lag behind advancements in the field, leaving aspiring accountants and finance practitioners ill-prepared to tackle the challenges and opportunities of the modern financial world. Additionally, there is a gap between academic research and practical applications, making it difficult for scholars to bridge the divide and offer real-world solutions. Contemporary Research and Practices for Promoting Financial Literacy and Sustainability presents a comprehensive solution to these challenges. It serves as a beacon of knowledge, bringing together classical finance topics and the latest developments, ensuring that future accountants and finance professionals are equipped with the knowledge necessary to navigate the reshaped financial landscape. By integrating contemporary research into finance teaching, this book bridges the gap between theory and practice, offering innate insights into theoretical concepts and their practical applications.
Machine learning algorithms and artificial intelligence influence many aspects of life today. This report identifies some of their shortcomings and associated policy risks and examines some approaches for combating these problems.
As e-commerce continues to increase in usage and popularity, safeguarding consumers private data becomes critical. Strategic innovations in artificial intelligence and machine learning revolutionize data security by offering advanced tools for threat detection and mitigation. Integrating AI and machine learning into their security solutions will allow businesses to build customer trust and maintain a competitive edge throughout the growing digital landscapes. A thorough examination of cutting-edge innovations in e-commerce data security may ensure security measures keep up with current technological advancements in the industry. Strategic Innovations of AI and ML for E-Commerce Data Security explores practical applications in data security, algorithms, and modelling. It examines solutions for securing e-commerce data, utilizing AI and machine learning for modelling techniques, and navigating complex algorithms. This book covers topics such as data science, threat detection, and cybersecurity, and is a useful resource for computer engineers, data scientists, business owners, academicians, scientists, and researchers.
In these highly competitive times and with so many technological advancements, it is impossible for any industry to remain isolated and untouched by innovations. In this era of digital economy, the banking sector cannot exist and operate without the various digital tools offered by the ever new innovations happening in the field of Artificial Intelligence (AI) and its sub-set technologies. New technologies have enabled incredible progression in the finance industry. Artificial Intelligence (AI) and Machine Learning (ML) have provided the investors and customers with more innovative tools, new types of financial products and a new potential for growth.According to Cathy Bessant (the Chief Operations and Technology Officer, Bank of America), AI is not just a technology discussion. It is also a discussion about data and how it is used and protected. She says, "In a world focused on using AI in new ways, we're focused on using it wisely and responsibly."