How should banks prepare for agentic AI in payments?

Imagine having a financial assistant pay your bills on time, alert you of any suspicious transactions and rebalance your investment portfolio based on real-time market data. That assistant could handle the accounts payable function for your business, including verifying invoices and purchase orders with delivery confirmations and automatically initiating payments.

That “assistant” is agentic AI.

AI agents can be thought of as assistants, though they can be proactive and autonomous. They have the ability to understand, plan and complete actions to achieve targeted goals. In banking, they can manage complex, multistep financial workflows, such as credit underwriting and fraud detection, and learn from interactions with minimal human input to improve efficiencies and enhance customer experiences. For example, an AI agent could alert you to a suspicious transaction, then complete a funds transfer upon a verbal approval.

With agentic AI payments, financial transactions are performed autonomously by AI agents – software that acts on instructions, using context, on behalf of businesses, devices and users. Agentic payments empower AI to make real-time decisions about if, when and how money should be moved based on predefined rules, machine learning and user intent.

For banks already using the technology, results show up to a 40% reduction in costs and a 30% increase in revenue.¹

How is agentic AI reshaping e-commerce experiences?

A primary focus and use of agentic AI is in the digital marketplace. Known as agentic commerce, this model uses AI agents to power online shopping on a person's behalf. The technology anticipates customer needs – searching and comparing products, negotiating deals and completing transactions – all based on a person's defined preferences and intent.

Are consumers in favor of machines making their purchases? According to one study, agentic AI is set to influence more than $1 trillion in e-commerce spending.²Additionally, 81% of U.S. consumers expect to use agentic AI tools to shop, which is projected to influence more than half of all online purchases in the near future.

A stark advantage of the technology is that agents can operate across multiple vendors, tabs and merchants, evaluating options based on a person’s preferences, then completing a transaction.

The process of bringing AI agents to life is already well underway, according to Jack Hilger, Senior Director of North America Product, Visa®.

What are the biggest risks of deploying agentic AI in banking?

With its vast potential, major banks are already starting to embed agentic AI into their offerings. Like any up-and-coming technology, however, it’s not without risk and uncertainty.

What role does data quality play in effective AI deployment?

When it comes to achieving favorable outcomes from your AI systems, it’s all about monitoring the information that’s going in and out of your models. This ensures the effectiveness of your agents that rely on clean, complete and high-quality data. Since agents operate autonomously, errors or biases in the data could be amplified, leading to inaccurate outcomes.

Poor inputs produce poor outputs, according to Ken Viciana, Head of Data and Analytics, FIS® Total Issuing™ Solutions.

How can banks build customer trust in agentic AI?

By giving automated AI agents the power to make decisions, could companies create a gap between humans and machines?

Take the case of Swedish fintech provider Klarna. The company launched an AI assistant it claimed could do the work of 700 full-time contact center agents. After a year, however, there was a decrease in customer service and experience standards, according to Bloomberg. Klarna then pivoted, turning back to people to handle more customer service work so customers had the option to speak with a live person.

The lesson was that AI does well when you augment it with humans and vice versa, according to Arun Ramanathan, Senior Generative AI Strategist, Amazon Web Services.

“Oftentimes we’re so involved at using technology to transform processes and improve efficiencies in our daily lives that we do not think about human interaction,” Arun said. “How can banks boost efficiency without sacrificing that human connection?”

Finding a middle ground that focuses on the customer.

“In payments, you must have a very human-centric and strategic ethical deployment to make sure it’s successful,” Arun said. “You can be not only efficient, but also empathetic. That’s going to be key.”

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