AI and the Future of Banking là quyển sách của tác giả Tony Boobier được xuất bản lần thứ nhất bởi NXB Wiley. Sách được trình bày qua 10 Chương tập trung khai tác các chủ đề liên quan như dữ liệu và quản lý dữ liệu, học máy (machine learning), trí tuệ nhân tạo (AI) và ứng dụng ngân hàng (Apps), ngân hàng mở (Open Banking) và công nghệ chuỗi khối (blockchain),...
Phần tóm lượt nội dung các Chương:
Chapter 1 provides an
insight into the evolution of money to what has now become perhaps no more than
a form of digital commodity in a near-cashless society, and offers the reader
an understanding about current banking roles and the likely impact of AI on
these in the future.Chapter 2 considers
current imperatives within the banking industry, comparing and contrasting them
to imperatives in other key industries of retail, telecom and healthcare and
suggests a set of future imperatives for the banking industry going forward.
Chapter 3 is a data and
analytics ‘primer’ to help readers understand not only the hierarchy of
analytics but how value is extracted from data.
The next three
chapters take the reader deeper into the subject of advanced analytics and AI
specifically for the banking industry.
Chapter 4 discusses the
key elements of banking analytics, covering issues such as financial
performance management, customer analytics, risk management and operational
efficiency, and gives readers a strong insight into the importance and current
usage of analytics for banking. Content is organised by imperative rather than
type of bank.
Chapter 5 takes the insight to a higher level, providing a background to the development of the concept of AI and then leading on to machine learning and its applications, including apps used in banking.
Chapter 6 focuses more specifically on AI and the importance of branding in banking. The chapter links strongly to the customer analytics element of AI. It recognises that different generations currently have different expectations of banks and that these will be fulfilled by both the brand and ultimately by the bank’s service extension. The chapter paints a picture of banks getting much closer to the consumer through AI and considers the issues involved.
Chapter 7 considers the impact of AI on issues of leadership and employee transformation and discusses leadership in an AI-infused age, the attributes of AI-infused leaders, training and personal coping strategies. It also deals with the evolution of the banking employee and creates a persona for a banking employee of the future.
Chapter 8 is about how banks might change physically, especially at branch level, and gives five scenarios for typical Banks of the Future, including transformation of the investment bank.
Chapter 9 deals with the topics of Open Banking and Blockchain, both of which are major issues in the banking industry in their own right and which will be affected by the impact of AI. The chapter also considers the impact of banking expansion in other continents.
Chapter 10 looks at issues of innovation and implementation, broadly considering topics such as new job roles, bootcamps and how banks work with Fintech companies. It also reflects on why innovation and implementation fail and provides possible mitigation strategies.
Chapter 11 rounds off with the difficult area of cybercrime, recognising that its management is a critical factor in the implementation of AI. It provides a broad explanation of the problem together with mitigating tactics, and concludes by looking specifically at the use of analytics and AI in banking fraud.
