AI is fast becoming a game-changer for banks, and 2023 saw a greater integration of these tools, especially in areas such as fraud detection and customer experience. The data-driven nature of the banking industry provides exactly the right environment for rapid and effective AI deployment.
As we enter 2024, it is likely that there will be expeditious growth in both adoption and effectiveness in the areas where it is already used, with banking continuing to remain at the forefront of the “real-world” adoption of AI.
1. Generative AI
The rise of generative AI promises to unleash a wave of innovation, efficiency, and personalisation for banks and their own customers. This can revolutionise how banking operations and services are delivered. It can also create novel and unique services, deliver huge efficiencies for banking operations, and change the way end users interact with banking.
According to McKinsey, across the banking industry, the technology could deliver value equal to an additional $200 billion to $340 billion annually. This can result from various use cases and applications, allowing huge efficiencies in the banking backend. Banking customers are also going to witness improved support as well as unique banking services and experience.
2. Responsible AI
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With the increased use of AI in banking and finance applications, there will be a need to have truly explainable AI models that can be easily understood, analysed and augmented by both business stakeholders and regulatory authorities. In addition, there is a need for the outputs of these models to be easily understood and analysed by the lay user.
We also need to make sure that the outputs of these models are not biased (against any customer segment or demographic) and that they are fair and safe. Responsible AI is the only way to ensure its widespread deployment in banking.
3. AI governance
Most governments and regulating authorities all over the world are working on tight AI governance that will allow access to the full power of AI while dealing with it as a safe and useful technology with its own regulation and governance to safeguard any inadvertent repercussions.
There will be an increased need for tight governance and compliance processes for the safe use of AI in different banking and financial institutions.
4. AI to realise financial wellbeing
Financial wellbeing will be a very important concept that explainable AI can help to realise for banks and financial institutions. For instance, managing bank end processes, intra-day liquidity forecasting, sentiment analysis, etc.
It will also be of benefit to customers, by forecasting cash flow and support in case of financial difficulty, or help to pick the best suitable mortgage or help in wealth advice, for example. Explainable AI will help underpin stable financial markets, as well as healthy finance support for banking end customers.
5. Expanding data sources
With the rise of the Internet of Things (IoT) and social media, more data will become available about the banking industry and its end customers. AI can play an important role in extracting full value from unstructured social media data and huge volumes of IoT data and fuse this with the customer banking data.
This will allow the banking apps to help and support the banks and their end customers in extensive ways which allow the production of novel unique services which can change the face of banking for the years to come.
Hani Hagras is Chief Science Officer and Head of the AI Business Unit at Temenos, the banking software company. Temenos is a world leader in Explainable AI and developing Generative AI with ethical and responsible deployment in banking. Hani is also a Professor of Artificial Intelligence at the University of Essex, where he is Director of the Computational Intelligence Centre and Head of the AI Research Group.
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