Regulations Push Firms to Boost AI, ML Spend

Financial services must keep up with technological developments that could grow their business, streamline operations, or completely change the game.

Artificial intelligence and machine learning alongside the recent advances in Large Language Models (LLMs) like ChatGPT are examples.

The potential AI applications for financial institutions are almost endless, from consumer-facing financial literacy assistance to back-of-house risk mitigation algorithms, and the industry is figuring out the best use for this technology.

A recent FIS survey found the vast majority (92%) of executives across the US and UK plan to increase or maintain investment in AI and machine learning technologies for processing, while 91% were for increasing or maintaining their investment in generative AI.

Transition to a Testing Phase

Melissa Cullen, global head of strategy, product and commercialization of banking solutions at FIS, says financial services firms have long relied on tech to solve some of their most pressing challenges, so it’s natural that as the pressures to manage costs while also growing assets intensifies, the promise of AI is generating a lot of attention.

“Whether it’s applying machine learning to strengthen the accuracy of which new service should be offered to a banking customer or applying generative AI to help a call center agent quickly resolve a question about retirement investments, AI has us re-thinking the way financial interactions happen -- both with customers and inside the walls of a financial institutions,” she explains.

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She notes the urgency being seen now is that providers are transitioning from “wait and see” to a “test and explore” mode where they are making investments in preliminary but very deliberate use cases.

“While the most common use cases for AI still appears to be in data collection and analytics, we’re seeing more firms beginning to test it on improving the customer experience and reducing operational expenses,” Cullen says.

Taking a Cautious Approach

Unlike some industries, though, financial services are highly regulated, given the industry’s stature as the modern economy’s backbone.

“The industry as a whole must be cautious about adopting new technologies given the myriad of rules and regulations at play,” cautions Joe Robinson, CEO, Hummingbird. “Financial institutions can plan to leverage the opportunities that AI presents but must do so carefully.”

He says by using explainable algorithms, auditable decision-making processes, and/or human-in-the-loop reviews, they can take advantage of the potential of AI while ensuring that regulatory obligations are met.

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“As with many new technologies, it's best to start small, observe outcomes, and scale up thoughtfully and pragmatically,” he says.

Cullen adds it’s critical to ensure the needed talent infrastructure is in place.

“Determine where you should hire and where you may need to augment, especially in relation to the evolving regulatory landscape,” she says.

AI Applications Abound in Finance

According to FIS research, financial services providers generally investing for the right reasons -- consumers want a more streamlined experience in their investing, payments, money management processes and executives are responding by leaning into customer experience (CX) and automation.

However, the report did highlight a disconnect on what “streamlining” and improved CX looks like.

While consumers said access to a single platform to manage all their financial services activity across providers was a top priority, financial services companies are instead looking to add new tools and capabilities or augment those already existing.

Between consumer-facing AI applications and back-of-house functions, there are numerous potential applications of AI.

On the consumer side, LLMs could be used to educate consumers about various financial products and services, increasing financial literacy.

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“Imagine a trusted, smart assistant that could meet you at your knowledge level and help you understand core personal finance topics -- LLMs can already provide this, and consumers can be convinced of its benefits if they believe the technology has been adopted safely and responsibly by the financial institution,” Robinson says.

In back-of-house operations, AI can help with a variety of applications to help the financial institution increase adoption of its products and services, mitigate risk, and increase efficiency in operations.

“Imagine having AI applied to Know Your Customer (KYC) compliance in financial institutions,” he says. “The technology could enable a more thorough and efficient understanding of the customer and help the financial institution avoid hidden risks.”

Cullen agrees there are “huge opportunities” for utilizing AI in customer onboarding and ongoing support.

She notes if consumers are to be won over through interactions powered by AI, they will need to be useful, accessible, reliable and contextualized.

“We’ve come to expect highly personalized experiences that feel seamless when we’re shopping for something mundane online, so the expectations of a company we’ve entrusted with our life savings are even higher,” she says.

And while consumers may begrudgingly tolerate incorrect information when it comes to the accuracy of a shipping date, the consequences of incorrect data in insurance underwriting or investment advice could be disastrous.

“Therefore, maintaining a level of human oversight in the application of AI and ML is essential to winning and retaining consumer confidence,” Cullen adds.