This book presents the reader with a complete and comprehensive picture of what is happening today in banks and other financial institutions in terms of expert systems implementation. In addition it helps in refining the reader's thoughts on how to build an environment for the successful implementation of expert systems in banking - and how to sell this concept to management including risks and opportunities.

Throughout the industry, financial institutions seek to eliminate cumbersome authentication methods, such as PINs, passwords, and security questions, as these antiquated tactics prove increasingly weak. Thus, many organizations now aim to implement emerging technologies in an effort to validate identities with greater certainty. The near instantaneous nature of online banking, purchases, transactions, and payments puts tremendous pressure on banks to secure their operations and procedures. In order to reduce the risk of human error in financial domains, expert systems are seen to offer a great advantage in big data environments. Besides their efficiency in quantitative analysis such as profitability, banking management, and strategic financial planning, expert systems have successfully treated qualitative issues including financial analysis, investment advisories, and knowledge-based decision support systems. Due to the increase in financial applications' size, complexity, and number of components, it is no longer practical to anticipate and model all possible interactions and data processing in these applications using the traditional data processing model. The emergence of new research areas is clear evidence of the rise of new demands and requirements of modern real-life applications to be more intelligent. This book provides an exhaustive review of the roles of expert systems within the financial sector, with particular reference to big data environments. In addition, it offers a collection of high-quality research that addresses broad challenges in both theoretical and application aspects of intelligent and expert systems in finance. The book serves to aid the continued efforts of the application of intelligent systems that respond to the problem of big data processing in a smart banking and financial environment.

The disciplines of knowledge engineering and knowledge management are closely tied. Knowledge engineering deals with the development of information systems in which knowledge and reasoning play pivotal roles. Knowledge management, a newly developed field at the intersection of computer science and management, deals with knowledge as a key resource in modern organizations. Managing knowledge within an organization is inconceivable without the use of advanced information systems; the design and implementation of such systems pose great organization as well as technical challenges.

This volume is a collection of cutting-edge research and applications chapters dealing with Expert System (ES) technologies in finance. Expert Systems in Finance and Accounting provides a cross-section of materials dealing with the application of ES in both finance and accounting areas ranging from variance analysis and audit selection in accounting to commodity trading, computerized trading and credit risk assessment in finance. The book identifies issues and opportunities for applying Expert Systems technology to financial management, portfolio and investment analysis and financial institutions.

Throughout the industry, financial institutions seek to eliminate cumbersome authentication methods, such as PINs, passwords, and security questions, as these antiquated tactics prove increasingly weak. Thus, many organizations now aim to implement emerging technologies in an effort to validate identities with greater certainty. The near instantaneous nature of online banking, purchases, transactions, and payments puts tremendous pressure on banks to secure their operations and procedures. In order to reduce the risk of human error in financial domains, expert systems are seen to offer a great advantage in big data environments. Besides their efficiency in quantitative analysis such as profitability, banking management, and strategic financial planning, expert systems have successfully treated qualitative issues including financial analysis, investment advisories, and knowledge-based decision support systems. Due to the increase in financial applications’ size, complexity, and number of components, it is no longer practical to anticipate and model all possible interactions and data processing in these applications using the traditional data processing model. The emergence of new research areas is clear evidence of the rise of new demands and requirements of modern real-life applications to be more intelligent. This book provides an exhaustive review of the roles of expert systems within the financial sector, with particular reference to big data environments. In addition, it offers a collection of high-quality research that addresses broad challenges in both theoretical and application aspects of intelligent and expert systems in finance. The book serves to aid the continued efforts of the application of intelligent systems that respond to the problem of big data processing in a smart banking and financial environment.

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.

An industry-specific guide to the applications of Advanced Analytics and AI to the banking industry Artificial Intelligence (AI) technologies help organisations to get smarter and more effective over time – ultimately responding to, learning from and interacting with human voices. It is predicted that by 2025, half of all businesses will be using these intelligent, self-learning systems. Across its entire breadth and depth, the banking industry is at the forefront of investigating Advanced Analytics and AI technology for use in a broad range of applications, such as customer analytics and providing wealth advice for clients. AI and the Future of Banking provides new and established banking industry professionals with the essential information on the implications of data and analytics on their roles, responsibilities and personal career development. Unlike existing books on the subject which tend to be overly technical and complex, this accessible, reader-friendly guide is designed to be easily understood by any banking professional with limited or no IT background. Chapters focus on practical guidance on the use of analytics to improve operational effectiveness, customer retention and finance and risk management. Theory and published case studies are clearly explained, whilst considerations such as operating costs, regulation and market saturation are discussed in real-world context. Written by a recognised expert in AI and Advanced Analytics, this book: Explores the numerous applications for Advanced Analytics and AI in various areas of banking and finance Offers advice on the most effective ways to integrate AI into existing bank ecosystems Suggests alternative and complementary visions for the future of banking, addressing issues like branch transformation, new models of universal banking and ‘debranding’ Explains the concept of ‘Open Banking,’ which securely shares information without needing to reveal passwords Addresses the development of leadership relative to AI adoption in the banking industry AI and the Future of Banking is an informative and up-to-date resource for bank executives and managers, new entrants to the banking industry, financial technology and financial services practitioners and students in postgraduate finance and banking courses.