The language pattern learning, predictive and generative ability as well as time-saving efficiency promise incredible benefits to every sector, including banking. But like any new, shiny penny, both the rewards and the risks need to be considered before the tech is implemented.

Here’s a highlight from our Partner Predictions Report of the opportunities and hurdles presented by generative AI in financial services.

From speeding up in-depth research to guiding strategy, conducting analysis and mining insights from datasets, we are just scratching the surface of the possibilities generative AI offers to banking, both internally and externally.

Advanced language models will transform customer experience by understanding sentiment, personalising support and driving innovation while other AI applications will increase employee productivity through accurate reporting, analysis of risk and tailored portfolio design.

Alpesh Tailor, Executive Director at GFT, believes these language models will deliver the most profound effect; “The advent of generative AI based on Large Language Models (LLMs) will be the key driver shaping the technological landscape of banking in 2024.”

AI promises, and largely delivers, greater operational efficiency, which means massive spikes in productivity. For example, back-office interaction is brought down to practically nothing when generative AI deploys virtual client agents, freeing up employees to tackle other tasks that require their attention. At its best, AI holds the power to relieve both analysts and marketers of time-consuming recons and deep data dives as LLMs speedily and efficiently compare, collate, and integrate copious data, generating accurate reports that are free of human error.

As we all know, with great power comes great responsibility, and generative AI is no exception. Along with advances that boost profitability and customer satisfaction, it’s predicted that there will be a significant rise in fraud and identity theft, scams, and other financial crime. The likelihood is that most organisations will not be prepared for these kinds of attacks, which leaves both businesses and people vulnerable. Cyber criminals are also constantly learning with the technology and rapidly finding workarounds and loopholes to beat preventative measures.

Philipp Pointer, Chief of Digital Identity at Jumio, highlights the importance of biometrics in secure identity verification: “Security and risk management leaders must ensure their identity verification solutions also continuously evolve and should consider additional features beyond the core identity verification process.”

In order to safeguard against potential threats, change needs to occur outside of just implementing AI. Regulation and compliance laws will undoubtedly develop, and so financial services will have to balance innovation with responsibility and caution, creating new positions to oversee upskilling as well as new security measures. Fintech firms will play a big role here, especially for small to mid-size banks in keeping them competitive, equipped, and compliant.

Like all revolutions, there is risk to every approach: a risk to adopting generative AI and a risk to putting it on ice until it’s ‘safe.’ Conservative bankers may worry about the privacy challenges it poses, but the danger of being left behind while competitors sweep up prospects is just as anxiety-inducing.

While a lot of the detail needs fine tuning, it is safe to say that generative AI’s potential is one of the most exciting developments of our time in tech.

This year will be a key milestone in not only how it will shift our experiences in banking but in how many organisations sink or swim because of its arrival. As VeriPark’s CEO Ozkan Erener says, “active implementation of AI technology within financial services has surged from 7% to 17%. For most banks, it’s not a matter of “if” but “when” they’ll embrace generative AI.”