By Tara E. Buck

Banking and financial services leaders see great opportunity to improve the bottom line thanks to artificial intelligence, particularly in the areas of process automation and fraud detection, according to a recent article for Forbes by AI developer Dmitry Matskevich.

July report from Capgemini’s Digital Transformation Institute predicts the financial sector could add $512 billion to their global revenues by 2020, and increase costs savings by 10 to 25 percent, thanks to intelligent automation.

“In 2017, financial firms quietly introduced a range of practical machines that think. Some banks added AI surveillance tools to thwart financial crime, while others deployed machine learning for tax planning,” PwC reports. “Wealth managers can now offer automated investing advice across multiple channels, and many insurers now use automated underwriting tools in their daily decision-making.”

But are all but the largest banks doomed to sit on the sidelines until AI tools become more ubiquitous — and affordable — in the standard IT infrastructure mix?

Wealth Management

As AI continues to evolve, its benefits now appear within reach of many business types, not just the largest and best-funded corporations that made up the majority of early adopters a few short years ago.

“Between chatting with bots on your bank’s website, to checking your account balance over the phone with digital voice assistants, you’ve probably encountered more AI in your recent banking experience than you thought,” Kylee Wooten wrote recently for Sageworks. “There’s no doubt that AI is going to continue to be leveraged in more aspects of bank operations, and offerings and will likely change the landscape of banking as we know it.”

Wooten asks, and we also wonder, exactly what can community banks expect to see?

Will Community Banks Capitalize on AI?

“On a surface level, community banking and AI can seem like something of a mismatch in concept,” a recent article at PYMNTS.com states. “Community banking is all about relationship-lending — forging personal and lasting connections directly with a consumer — while AI — particularly embodied by chatbots and voice assistants — focuses primarily on digitally mediating that personal relationship.”

But AI should be seen as an opportunity for community banking, one that could be a game changer for community banks over the next five years, says Tina Giorgio, president and CEO at ICBA Bancard.

“There is tremendous potential with the advent of AI to help level the playing field in the financial services space,” Giorgio told PYMNTS. “Use cases are rapidly growing and they are showing that they can really streamline the customer experience in a number of ways while strengthening those personal relationships between the bank and its customers.”

She points out that the AI-enabled future also includes Internet of Things technologies, voice assistants and fraud protection or AI-backed cybersecurity tools — all of which can seem daunting to community banks that must deploy new IT to fully utilize them. Still, they represent the tools of banking’s future, and it behooves community bank leaders to explore them.

What’s on the Horizon for Community Banks and AI?

Smaller institutions are likely to start slow, first setting up systems to provide customers with simple account information through conversational banking through devices such as Amazon Alexa or Google Home, Marc DeCastro, a research director for IDC Financial Insights, told BizTech for a previous report.

Others will incorporate AI into chatbot features that allow customers to make name and address changes or other services often handled by a bank employee. In the near future, for example, an automated system could notice that the bank has not received a copy of a credit applicant’s driver’s license and ask them to take a picture to send in order to complete the application.

“Providing actionable advice where the bank will do research for the customer is closer than one thinks, and it truly is an omnichannel approach in using AI,” DeCastro says. “The likelihood is that smaller banks will remain conservative and take a ‘wait-and-see’ approach, but they will not be far behind the larger banks and will rapidly catch up.”

How Should Banks Prepare for AI?

Only 4 percent of respondents to Gartner’s 2018 CIO survey indicated they have invested in and deployed an AI-based solution, Matskevich points out. “So, if you don’t have an AI-based solution yet, don’t panic.”

He advises leaders to look deeply at the business need and determine the pain points or other challenges that can be eliminated through AI solutions. Banks and business leaders must also understand the risks associated with AI — and the risks inherent to any new technology implementation.

Machine Learning

Critically evaluate every failure,” Matskevich writes. “It will help you understand your risk factors and give you data to make better decisions in the future.”

In addition to uncovering the appropriate AI developer support, he also advises business leaders to take time to hire the right people and build the right culture.

“While it’s expensive to invest in new technology and new talent, it’s worth it,” he says. “It can transform your business.”

“Every community bank has different needs, because every community is different, which means there is no single roadmap that community banks must take when they start building out their uses for AI,” PYMNTS points out. “As community banks increasingly tap into the mountains of data they collect, they need to be more aware of the challenges that data protection entails. That is even more important with regulators increasingly scrutinizing data usage.”

“Community banks looking to wade into the AI waters early need to be selective when it comes to picking the most relevant use cases and finding the vendors most sufficient to fill those needs. That is real work that needs to be done with care,” Giorgio advises.

PwC highlights a few foundational questions for banking leaders to address as they uncover what AI-based solution is right for them, as well as the infrastructure required to support it:

  • What controls should we apply to AI systems that decide and act in nanoseconds?
  • How much authority should AI have?
  • How do make sure machines uphold their fiduciary duty?
  • Who should serve on the AI audit team?

Along those lines, Microsoft’s recently hired AI ethicist — Tim O’Brien, general manager of AI programs — advises businesses to promote AI ethics within their companies. Among other insights, he told CIO Journal that businesses should be aware of the dangers of AI bias, which could prove particularly problematic for community banks that use AI tools in reviewing lending applications. Banks must ensure their AI tool does not discriminate against groups of people. It’s also important to ensure diversity on the team building any AI products.