AI is fast becoming a game-changer in the banking industry, and 2023 sees deeper integration of these tools in areas such as fraud detection and customer experience. The data-driven nature of banking provides an ideal environment for rapid and effective AI deployment.
As we move into 2024, it is likely that both adoption and effectiveness will grow rapidly in areas already in use, and the banking industry will remain at the forefront of "real-world" applications of AI.
1.Generative AI
The rise of generative AI promises to bring a wave of innovation, efficiency, and personalization to banks and their customers. This can revolutionize the way banking and services are delivered. It can also create new and unique services that bring significant benefits to the banking business and change the way end users interact with the bank.
According to McKinsey, across banking sectors, this technology could provide between $200 billion and $340 billion worth of additional revenue per year. This can be achieved through a variety of use cases and applications, enabling tremendous efficiencies on the backend of the bank. Bank customers will also witness enhanced support as well as unique banking services and experiences.
2.Responsible AI
With the increased use of AI in banking and finance applications, there is a need to have truly explainable AI models that can be easily understood, analyzed, and enhanced by business stakeholders and regulators. In addition, the output of these models needs to be easily understood and analyzed by the average user.
We also need to ensure that the output of these models is unbiased (for any customer group or demographic) and that it is unbiased and secure. Responsible AI is the only way to ensure its widespread deployment in the banking industry.
3.AI governance
The majority** and regulators around the world are working to develop strict AI governance that aims to harness the full power of AI while treating it as a safe and useful technology with appropriate rules and regulations in place to prevent any unintended consequences.
The secure use of AI across different banks and financial institutions will increase the need for rigorous governance and compliance processes.
4.Artificial intelligence for financial well-being
Financial well-being will be a very important concept that can be helped by banks and financial institutions through explainable AI. For example, managing end-of-bank processes, intraday liquidity**, sentiment analysis, and more.
This will also be beneficial to clients, such as cash flow and support in times of financial difficulty, or to help choose the most suitable mortgage or wealth counseling. Explainable AI will help underpin stable financial markets, as well as provide healthy financial support to bank-end customers.
5.Expand your data**
With the rise of the Internet of Things and social networking**, more data will be available about the banking industry and its end customers. AI can play an important role in extracting unstructured social** data and massive amounts of IoT data and fusing it with customer banking data.
This will enable banking applications to help and support banks and their end customers in a variety of ways, providing new and unique services that can change the face of banking in the future.
Hani Hagras is the Chief Scientific Officer and Head of the Artificial Intelligence Business Unit at Temenos, a banking software company. Temenos is a world leader in explainable AI and the development of ethical and responsible deployment in the banking industry. Hani is also a Professor of Artificial Intelligence at the University of Essex, UK, where he serves as Director of the Centre for Computational Intelligence and Head of the AI Research Group.