Agentic AI and the future of fintech and banking automation
Barely a week can pass in financial services without a new AI innovation bursting onto the scene. While some show more promise than others, all share a mutual mission in trying to alleviate some of the industry’s biggest pain points.
Agentic AI refers to creating intelligent AI “agents” that make autonomous decisions to carry out tasks
A quick glance through some of the latest headlines will reveal applications in the areas of backend automation, cybersecurity, portfolio management, and personalisation.
Notable recent developments include BNP Paribas’ multi-year partnership with Mistral AI, BBVA’s deployment of ChatGPT with OpenAI, and Franklin Templeton’s work in building an “advanced financial AI platform” with Microsoft.
The industry’s appetite for AI is more ravenous than ever, and while the full possibilities presented by GenAI are still being discovered, agentic AI is emerging as a new focal point for the financial services industry.
In a nutshell, Agentic AI describes creating intelligent AI “agents” capable of autonomous decision-making to carry out tasks, enabling businesses to completely automate historically arduous, lengthy, and labour-intensive processes.
Here, FinTech Futures speaks with industry experts to lift the lid on agentic AI and its promises of seamless automation.
Beyond data outputs
In the publication Artificial Intelligence: A Modern Approach, Peter Norvig and Stuart Russell cite an agent as “anything that can be viewed as perceiving its environment through sensors and acting upon that environment through actuators”.
How does this differ from more traditional forms of AI? For Matt Roberts, head of data at ClearBank: “Agentic AI is not just about data outputs.”
Roberts has led a team building AI and data infrastructure at ClearBank since 2022, and previously worked at Lloyds Banking Group for over a decade, predominantly in the field of data science.
“It’s about taking actions and automating whole processes that might previously have been considered too complex due to the potential number of outcomes or the expert knowledge required to reach those outcomes. In contrast, traditional AI is very much focused on data outputs,” he tells FinTech Futures.
Roberts says the concept of AI agents completing actions within an environment has been “supercharged” by two related developments in the sector – large language models (LLMs) and GenAI.
LLMs have enriched models with access to unstructured text and the ability to distil vast data sets, while GenAI has given rise to pre-trained models able to input data and create, improve, and iterate formulas.
“You can also teach an agent what actions to take with reinforcement learning – a process where the agent is given access to an environment/system/programme, and then through trial and error, it repeats the action until the correct outcome is achieved,” Roberts explains.
Many hands make light work
Agentic AI could have the potential to deliver the level of automation the financial industry has been dreaming of, if refined and harnessed correctly.
Marqeta’s Fouzi Husaini describes agentic AI as like having an unlimited number of “really smart interns”
And despite still being in the early stages of development, optimism around agentic AI continues to spread across the industry, as Fouzi Husaini, CTO and chief AI officer at Marqeta, explains:
“The rapid pace at which we’re seeing innovation and new products coming in the market is remarkable. We’re still in the nascent early days of really going all in on agentic AI, but I think that the idea of it and the possibility of it is very exciting and interesting, especially in the fintech space.”
He says agentic AI is like having an unlimited number of “really smart interns” in discussing the benefits anticipated for fintechs, with the “very tedious, manual, human tasks” of backend operations being prime targets of first applications.
And not surprisingly, it is the tech giants that appear to be currently leading the charge in this department.
Google notably capped off the end of last year with the launch of Gemini 2.0, which CEO Sundar Pichai said at the time will “enable us to build new AI agents that bring us closer to our vision of a universal assistant”.
For Husaini, developers’ experimentation with agentic AI will last throughout H1 2025, with further commercial lift-off expected “towards the end of this year and then early next year”.
Frontrunners seem to have hit the ground running last month, especially on 23 January, when OpenAI debuted its first AI agent called Operator, which can “can go to the web to perform tasks for you”, while Anthropic CEO Dario Amodei took to the stage at the World Economic Forum to confirm the company’s work on a “virtual collaborator”, all in a single day.
Risk and reward
While the industry moves quickly, it must also move carefully, as it’s easy to get swept up by the hype around new technology.
Regulators have attempted to keep a close eye on the industry’s increasing ties with AI, as noted through the EU AI Act, which commenced a two-year implementation phase in August with an emphasis on pioneering explainability and human oversight.
Ed Maslaveckas of Bud Financial urges regulators to not tie down AI innovation
The depth of agentic AI’s intersection with financial services, one of the most highly regulated sectors in the world, will centre on the industry finding the right balance between innovation and regulation.
Ed Maslaveckas, CEO and co-founder of Bud Financial, tells FinTech Futures that risk-seeking fintech start-ups “with everything to gain and nothing to lose” will be one of the main propellers of the industry’s increasing intake of agentic AI, while expecting their larger rivals to branch out into agentic-focused sister brands and ultimately reduce the potential reputational risk.
“That’s the power of a big bank, especially going into the future. It’s more about the brand equity and less about the technology advantage, because they have zero, in my opinion. They just have the brand equity advantage, and the trust,” Maslaveckas says.
Maslaveckas emphasises the need for regulators to action “a big push on AI in general” to help spur innovation.
“We need to see governments take a much more hand-on approach to being leaders in AI across industries and not try to shut things down locally by creating regulations that are so burdensome that they drive away innovation and talent.”
He points to the UK Financial Conduct Authority’s AI Lab, launched in October, as one of the positive movements in the regulatory response to agentic AI, as well as the shifting “risk on” attitudes of President Trump’s new administration in the US.
“You can’t tie down innovation,” Maslaveckas continues. “There’s always going to be a regulatory body somewhere that sees an opportunity.”
Bud Financial, a late-stage fintech start-up based out of New York, has lately made its own advances with the technology by launching its first agentic banking capability in September last year.
The capability combines the company’s data intelligence platform with a new consumer agent to suggest and action tailored financial products for consumers.
“Our agentic capability removes a lot of the apathy around financial products,” he explains. “It can identify opportunities to boost your financial life, then make a recommendation, while the agentic capability will be able to carry out the recommendation for you, and that makes life really very easy.”
These benefits could also apply to banks’ back-office operations, Maslaveckas adds: “I think an agentic AI capability inside an organisation will have a huge impact, because it allows a lot more documentation and process following to be done automatically through these agentic AI models.”
Maslaveckas forecasts that “the bank of the future will be a cluster of agentic models, with humans in the loop to double check that the models haven’t gone and done something crazy”.
Shaping the future
Agentic AI has the potential to revolutionise the financial sector by automating complex tasks and oiling the thousands of cogs that power everyday decision-making.
While the larger tech giants appear to be leading the charge in this space, supported by the innovative agility of nimble fintechs, the industry as a whole must look to balance innovation with careful regulation to manage risks and uphold trust.
As agentic AI innovation continues to pick up speed, it’s almost certain that the next few months will determine how effectively it can reshape financial services and elevate new levels of efficiency and compliance.
