Overview

Bankers, Markets, Investors (BMI) Special Issue

Artificial Intelligence, Machine Learning and Banking services

Guest Editors

Aurélie Sannajust, Associate Professor, Kedge Business School Mohamed Arouri, Professor, Université Côte d’Azur.

Artificial Intelligence (AI) is one of the most exciting technology trends happening in the 21st century. As of 2023, the global AI market is valued at over $136 billion, and the industry value is projected to increase by over 13x over the next 7 years. The market size is expected to grow by at least 120% year-over-year. AI is transforming many industries in the economy including the financial services industry. AI is changing the nature and quality of the products and services offered by the banking industry. The size of AI in the banking industry was estimated at a value of $3.88 billion in 2020 and is projected to reach $64.03 billion by 2030.

With the introduction of ATMs, the banking industry was confronted with a shift in site visit preferences. These machines allow cash deposit and withdrawal without any human assistance. Banks also faced the digitization with mobile banking, real-time money transfers and similar services. This trend has contributed to the growth and demand of artificial intelligence. Furthermore, banks have to provide systematic compliance management and operations. A fast-track strategy is required with Artificial Intelligence, which is a key attribute for the sector to deliver affordable and dependable banking services. Furthermore, Machine learning (ML) is increasingly used by banks to detect and prevent fraudulent transactions in real time.

AI is also being increasingly used by banks for numerous other reasons such as improving customer service through the use of virtual assistants or for credit scoring. Integrating Artificial Intelligence into the banking industry helps banks deal with the high competition with the FinTech members. AI also presents the advantage of managing huge volumes of data with high frequency. Furthermore, AI enables banks to identify the preferences of their customers through their knowledge with their customer database and emotional intelligence. The implementation of AI in the banking industry will create a higher cyber-attacks risk and actors have to react in order to increase cyber security. Of course, the emergence of this new technology creates new forms of competition as well as new challenges and concerns.

Objectives and Scope

This Special Issue is aimed to improve our understanding of the implementation of artificial intelligence and machine learning in the banking industry and to disseminate scientific knowledge and strategic ideas and create greater awareness of the new challenges the banking industry is facing.

We welcome the submission of empirical, theoretical or critical papers that tackle the challenges associated with the implementation of AI/ML in the banking industry. Specifically, we call for papers addressing, but not limited to, the following topics:

• AI and cybersecurity in the banking sector
• AI and the customer database in the banking sector
• AI and the prediction of future outcomes in the banking sector
• AI and the risk management in the banking sector
• AI and frauds in the banking sector
• AI, Machine learning and costs savings (automation and optimization) in the banking sector
• AI/ML and banks’ products and services
• AI/ML and banks’ performance
• AI/ML and ethics in the banking industry
• AI/ML and decision making in the banking industry
• AI and the data privacy and security in the banking sector
• Machine learning, chatbot and consumer behavior
• Risks and concerns associated with using AI/ML in the banking industry.