Forget ChatGPT: Why AI Agents Are The Real Game-Changer For Financial Services

AI agents – next-generation autonomous AIs capable of complex tasks – are about to upend every industry. Financial services companies, which have always been very successful at spinning new technologies into gold, will be among the most deeply affected.

Their industry is built on digital networking, structured data, fast-flowing transactional records and competition to offer better services to customers. Agentic AI has the potential to shake things up dramatically in these areas.

So, let’s take a look at how banks, hedge funds, insurance companies and traders will put it to work in the hope of building the next generation of finance businesses.

AI Agents: Reality And Opportunity

AI agents are the latest buzzword in business technology. Essentially, they’re AI applications capable of learning how to carry out complex, multi-step processes with minimal human intervention.

So, while a conventional AI chatbot – like ChatGPT, for example, can generate ideas about what to have for dinner or where to go on holiday, an agentic equivalent can:

Plan meal schedules, shop for groceries and have them delivered to your door.

Plan and book a holiday, including arranging flights and accommodation across different providers.

Manage household tasks, interfacing with cameras and robotic appliances to perform chores and identify areas that need maintenance.

This is because they can adapt their tactics and goals while on the job – during the “inference" stage when the AI has been given a task and is working on it. By comparison, a non-agentic generative AI chatbot only learns while it’s being trained.

On top of this, they can also learn to interact with external systems. Current genAI chatbots can only talk to other systems when they’re given access through an API. AI agents, like OpenAI’s Operator, can learn how to do it themselves, using computer vision to “see” how a system works.

As you can imagine, there are plenty of ways this could be useful in financial services, and I believe it’s where we will find many of the leading use cases in the coming years.

AI Agents In Financial Services

AI agents will function as autonomous analysts and investment advisors, analyzing market conditions, risk factors, and strategies in real-time to identify trends and opportunities. Importantly, this isn’t because they’re explicitly programmed to do so but because they autonomously find the most effective ways to maximize financial gains, dynamically adjusting their strategy whenever a better opportunity emerges.

Likewise, for risk assessment and credit scoring jobs, AI agents will go beyond “traditional” AI algorithms by identifying the best sources of financial or behavioral data in real-time and even detecting emerging risks and threats they weren’t originally told to look out for.

A big part of the financial services workload involves keeping on top of compliance and regulatory requirements. Here, agents are able to autonomously scan for compliance risks, continuously updating themselves on changes to regulations or statutory obligations. Think of it like this: While an AI algorithm can analyze a document to check it is compliant, an AI agent can create a strategy to ensure all of an organization’s documentation is consistently compliant and put processes in place to ensure it stays that way.

And they’ll help financial services companies create new customer experiences; think highly personalized agents that go far beyond chatbots, able to learn about our individual requirements and habits, and autonomously adapt the way they deliver services to fit our lives.

According to research by Citi, “Historically, banks are the biggest spenders on technology outside of the tech industry. This trend will likely continue with genAI and agentic AI too.”

And Kirsty Rutter, fintech investment director at Lloyds Banking Group, predicts that agentic AI will enable more personalized and efficient financial services, from automated customer support to sophisticated investment strategies.”

Future Agents

We’re still at a very early stage in the evolution of AI, and it’s important to remember that today’s agents will look very basic compared to those that will be around in two or three years’ time.

Agentic AI is often seen as a step towards AGI – artificial general intelligence – the holy grail of developing machines that can generalize their skills and knowledge to complete any task, much like we can.

As we approach that goal, we can expect to see agents in financial services becoming capable of increasingly complex tasks. Inevitably, this will lead to job losses—200,000 are predicted to be lost on Wall Street alone.

New jobs will be created for people capable of working with AI, but this change to the employment landscape is just one challenge society will have to face up to.

Frameworks will also need to be established to ensure that AI agents operate ethically, transparently and with accountability.

And the security implications of widespread adoption of agentic AI in finance need to be properly assessed and managed, too. New technology always means new opportunities for cybercriminals, and this is doubly true when the technology can access our assets and make decisions for us.

If the industry gets all of this right, then we could be on the cusp of a hugely transformative era for banking, insurance and financial services. It could increase access to fintech services, allow fairer insurance and credit scoring, and enable businesses to develop more resilient investment strategies, ultimately benefitting us all.