The future of banking is AI

Imagine being able to perform an analysis that once would take a week in the middle of a board meeting. That’s the picture painted by Octavio “O.J.” Laos, AI lab practice leader at Armanino LLP, one of the nation’s largest independent accounting and consulting firms. “It isn’t just the instant breakdown, but also new ideas or ways to analyze data you never would have thought of,” he says. 

In the future of banking, artificial intelligence plays a starring role. As AgileThought puts it: “We’ve just scratched the surface of what data and AI can do for the banking sector.” 

Even so, “we are now in the AI-powered digital age,” says Christine Parker, founder and managing partner of Crossroads Advisory Partners, a boutique advisory focused on designing and delivering revenue and operational scale through innovation and purpose-led strategy. “Artificial intelligence technologies are increasingly integral to the world we live in, and banks of all sizes need to deploy these technologies at scale to remain relevant.” 

This will, she continues, “require purpose-led, holistic transformation across the organization. It must be a coordinated effort versus applying AI for the sake of AI. The up-front investment and transformation path will be an investment; however, the results should set up banks to thrive in the ever-evolving digital economy, serve customer expectations with on-point products and services and operate more efficiently.” 

The global market size of AI in banking was valued at $3.88 billion in 2020 and is projected to skyrocket to roughly $64 billion by 2030, growing at a CAGR of 32.6% from 2021 to 2030, according to Allied Market Research. 

“Artificial Intelligence has brought transformative advancements to data analysis in financial services institutions. Key among these is the ability to process and analyze large volumes of data at unprecedented speeds,” says Michelle Delker, founder of the William Stanley CFO Group, a boutique fractional CFO and financial services firm. 

The potential uses and benefits are widespread. “AI has the potential to revolutionize how businesses use data to drive decision-making, uncover new trends or opportunities and gain a competitive edge,” says Zachary Jarvinen, vice president of Exact Payments, an embedded payment solutions company, and author of “Enterprise AI For Dummies.” “AI algorithms are capable of processing vast amounts of data quickly and accurately to identify patterns that would otherwise go unnoticed.” 

It’s well-known that banks and credit unions have vast amounts of untapped customer data within their organizations. For a time, the analytics discovered from all that data was ahead of the curve. No longer.   

“Data analytics have been used for several decades now, and by leveraging the power of AI, financial institutions can gain an even keener competitive edge, gain operational efficiencies and make more informed management decisions in a rapidly evolving industry and customer and talent management landscape,” Parker says. AI-infused data analysis offers several key benefits in the financial services industry and will “supercharge” those capabilities, she adds. “These include accelerated solutions for improved operations, reduced costs, enhanced fraud detection, automated regulatory compliance, reduced risk and faster decision-making.” 

What’s more, according to Jarvinen, “AI can drastically improve the accuracy, speed and scalability of data analysis. AI algorithms are able to identify patterns in data much faster than humans, and they can also process vast amounts of data at once. In addition, AI tools are capable of automatically learning from past experiences and adapting to new situations, which can lead to better decision-making.” 

AI algorithms can identify correlations between different types of data and discover insights that would otherwise go unnoticed. “This makes it possible to uncover valuable trends and new opportunities more quickly than ever before,” he adds. Think about it like this: “Using AI and machine learning, these organizations can monitor for specific activities, like marriage, a credit inquiry or a new baby, that would  trigger customer communications. When they can unlock those insights, AI can help them double their output and productivity, and they’ll grow because they are reaching out with the right offering at the right moment of opportunity,” says Joe Welu, CEO and founder of Total Expert, a fintech software company that launched the first customer experience platform purpose-built for modern financial institutions. “By surfacing insights that trigger personalized outreach, AI and machine learning technologies allow agents to focus on doing what they do best—building relationships and connecting with customers.” 

“AI will work as a ‘copilot’ for every professional; enhance what humans are able to do on their own, in terms of quality of service, financial advice and timing; make sales and marketing people more efficient; create guidelines to ensure people aren’t crossing compliance lines; and support retention as it helps create context for customer-facing teams,” Welu says. 

Not everyone is on board yet. Allied Market Research reports that “about 32% of banks are already using AI technologies such as predictive analytics, voice recognition and various others to have a competitive advantage in the market.” A spokesman for one credit union stated that “we are not using AI in this way at the moment,” while another’s response was that “we certainly have not used AI for any of our marketing or data analysis.” 

Indeed, several of the larger banks with their bigger tech budgets are ahead of the curve. But there is room for all. “As far as credit unions, they have a unique position in all of this. While they may not have the same resources as the larger banks, credit unions can still leverage AI for data analysis,” says Jason DeReuter, chief product officer of Verkend. “Collaborative efforts, partnerships with technology providers and embracing innovative solutions can help credit unions stay competitive and provide better localized services to their members.” 

Whether large or small, “banks not capitalizing on AI tools are lagging,” Delker points out. In time, they’ll undoubtedly dip their toes in the water. Of course, no one is promising this will be a seamless and simple process. “It’s important to remember that these technologies are still in their infancy,” AgileThought notes in a blog post. “There will be bumps along the way as we figure out how best to use them and integrate them into our daily lives. But this doesn’t mean we should stop exploring new ways of using these technologies!” 

As DeReuter puts it: “The AI revolution in data analysis is well underway, and it’s going to be an exciting journey for the industry as a whole.” 

Dawn Wotapka is a BAI contributing writer.  

We offer actionable insights on other data and analytics topics that can benefit financial institutions in the BAI Executive Report, “The insights of data and analytics.”