In 2024, the European Union (EU) announced the implementation of the EU Artificial Intelligence Act (EU AI Act), the world’s first ever artificial intelligence (AI) regulation, which came to life on 1 August 2024. The regulation sets out a clear set of risk-based rules focusing on specific use cases of AI which businesses and AI-developers must follow. These use cases range from high-risk to minimal risk, with the financial services sector falling under the high-risk category due to the huge amount of personal data the sector collects and stores.
Although, the EU AI Act comes at a perfect time where the use of advanced technologies is accelerating, there is a catch! If businesses fail to adhere to the regulation, it could result in severe financial penalties of up to €35,000,000, or up to 7 percent of the business’ total worldwide annual turnover, whichever is higher.
With the next EU AI Act deadline in August approaching, all businesses, particularly financial services organisations, must review their strategies to meet the stringent requirements. Not only that but organisations should also avoid complacency and continue innovating as customers will still hold them accountable to address their demands for more personalised offerings. The key to ensuring businesses strike the right balance between remaining compliant and competitive is through AI.
The role of AI in banking
Financial services organisations must constantly innovate and digitally transform their operations to stay competitive whilst addressing customer demands in a timely fashion. AI underpins this transformation with banks using the technology in a number of ways throughout their operations.
For example, internally, financial services can use AI to automate workflows, to guarantee that the right decisions are made quickly, and customers receive resolutions in real-time. By using AI to automate routine and repetitive tasks, employees can focus on complex and value-added projects instead. As a result, this has the potential to drive increased revenue to the bank.
Further, as data is a critical element of financial services, businesses use AI to streamline the way information is collected, sorted, and analysed. By using AI, banks can speed up the pace of their product and solution development to address customer demands more accurately and efficiently.
Not only that, but data also enables these businesses to understand their customers on a much deeper level. In this, financial services organisations are able to predict future customer behaviour by analysing past interactions, purchases and so on. This is particularly helpful as organisations have the opportunity to offer more proactive and tailored support, driving better customer service.
AI-driven predictive modelling also plays a significant role in the sector. It can be used to ensure customers, and their assets are safeguarded against fraud. This is done through banks having much stronger insight into customer behaviour and so having better insight into their potential risks. Financial services organisations can now automatically flag and block any suspicious transactions and so protect their customers and their own reputation.
The financial services sector has continued to leverage AI to not only drive quicker and better innovation, but also to enhance customer experience and risk assessment. Nevertheless, within all of this innovation, banks must make sure that they remain compliant to industry regulations.
AI challenges to overcome
Regulations like the EU AI Act are meant to ensure that AI is being used in a safe and ethical way. With that said, it is critical for a strong human oversight to exist. Having the human element monitoring the type of information the AI tool uses reduces any chances of outdated information generating biased decisions. Human oversight also guarantees that AI operates ethically, responsibly, and in compliance with the Act.
In addition to this, AI hallucinations represent a significant challenge for the sector. This is where the AI tool produces information that seems to be correct, but is not. These hallucinations stem from the data used to train the models proving, yet again, the importance of having accurate and unbiased information. AI hallucinations undermine both industry and customer trust in AI models and their outputs.
Thriving through regulation
In a world of tighter regulations around AI, it is important for these models to be trusted. To achieve this AI models must be trained on data that is reliable, transparent, and justified. The data which is driving these models should be ethically sourced, complete, and of high quality.
Alongside this, employees should have access to robust AI literacy and training courses. These programmes should outline the current abilities of AI, and the potential of this technology should be clearly defined. Customers should also have access to training materials to better understand how the technology works, how the bank uses it and its impact.
Regulations like the EU AI Act are in place to ensure that AI is used ethically. This means that banks must find the right balance between driving innovation with AI and using the technology in a responsible manner. The financial services organisations that are able to successfully accomplish this will thrive in the market.
