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As community banks grow, their vendor partnerships usually also do, which can lead to challenges with organization, data security and more. To address these issues, some community banks have turned to artificial intelligence.
By Elizabeth Judd
The dazzling possibilities of artificial intelligence (AI) have captured the public imagination. Think Scarlett Johansson’s voice as an AI-assisted virtual assistant and romantic interest in Her, or Janet on The Good Place.
In finance, too, AI has been held up as the answer to any number of challenges that community bankers face. And yet, some industry experts have observed that AI is not yet being used to its full advantage in vendor management—one of the thornier problems that community banks are wrestling with today.
If a community bank has just a handful of vendors, managing those vendors is fairly straightforward. Keeping track of vendor relationships through emails, spreadsheets and client relationship management (CRM) software is adequate for a small vendor ecosystem.
But because each vendor has its own set of contacts, contracts, processes and approaches to data security, the challenges of overseeing third parties mushroom as the number of vendors grows.
“Today’s banks may have many vendors, and each vendor has to submit a large number of documents to comply with [bank requirements],” says Robert Johnston, founder and CEO of Adlumin, a Washington, D.C.-based cybersecurity technology firm.
The true power of AI makes itself known when “extracting conclusions from large data sets,” he says. “Data science can make an impact in every industry segment, including vendor management.”
Improving communications
Natural language processing (NLP), an offshoot of AI and machine learning, can be an effective tool for vendor management, says Johnston. That’s because NLP can analyze text based on knowledge of how human beings speak and write.
“If you’re analyzing a contract for risk, you could train an NLP algorithm to recognize groups of words that represent what you’re looking for in a contract, like indemnification terms that are negative or that do not meet the company’s requirements,” Johnston explains. In such a scenario, NLP would allow a community bank to speed traditional processes dramatically.
“So much more data is in the cloud today. We’re using vendors that are ‘living’ in Amazon servers …
Our data is not just in our walls anymore.”
—Greg Ohlendorf, First Community Bank and Trust
Reviewing contracts is not the only AI play for streamlining vendor interactions.
“To automate communication with vendors, think about a chatbot,” suggests Johnston. “A chatbot helps you solve your problems without ever having to introduce a service person.”
Chatbots have the added attraction of being an AI-enabled product that many bankers already know, says Emmett Higdon, director, digital banking, for Javelin Strategy & Research. “Chatbots,” he explains, “are one of the first places where smaller banks will dip a toe into artificial intelligence.”
Safeguarding data
Community banks wrestling with vendor management soon find themselves fretting about data security. “So much more data is in the cloud today,” says Greg Ohlendorf, president and CEO of First Community Bank and Trust in Beecher, Ill. “We’re using vendors that are ‘living’ in Amazon servers … Our data is not just in our walls anymore.”
For Ohlendorf, using AI for data security is critical but not something that he’d tackle on his own.
“We’re not building AI solutions in our $200 million-asset community bank,” says Ohlendorf. He uses fintech providers to deploy AI to foil hackers and to guard against ransomware attacks for its vendors and the bank itself.
“Third parties can pose a significant security threat to an organization,” explains Adlumin’s Johnston. For instance, third parties that have been given access to a bank’s systems or its core can increase exposure to breaches. AI, which excels at analyzing reams of data and pinpointing suspicious activities, can be instrumental in safeguarding data and strengthening cybersecurity.
AI and innovation
Using AI to manage vendors has broader implications than simply solving a series of back-office or security headaches.
Many community bankers are keen to devise ways to distinguish themselves within a crowded field by being bold and experimental. If AI smooths the path to taking on more vendor partnerships, then it becomes a strategic imperative of its own.
“Smaller banks are not hesitant to try new stuff,” says Higdon, noting that AI is among the solutions he’s observed community banks experimenting with. “When we look for innovators,” he says, “often we hear that it’s not coming from the big-name banks. It’s the smaller banks that want to innovate and will try new things.”
Behind the scenes of AI
Thanks to a growing number of relationships with third parties, community banks may already be using AI solutions for vendor management.
That’s because outsourcing tricky problems to vendors has become so commonplace that even the task of managing these vendors is increasingly being outsourced as well.
Newcomers like Venminder, based in Elizabethtown, Ky., and Ncontracts in Brentwood, Tenn., offer solutions that simplify vendor management for community banks by using AI.
Banks currently outsourcing the whole vendor management process may be relying on AI without even knowing it, according to Adlumin’s CEO Robert Johnston. “Often, all that banks see,” he says, “is a faster, more streamlined and probably cheaper vendor-management product.”
Elizabeth Judd is a writer in Maryland.
