The $7.3 billion Kearny Bank is expanding its use of artificial intelligence (AI) to include customer data analysis after the bank was won over to the technology by the Bank Secrecy Act and anti-money laundering (BSA/AML) solution it already employed. BSA/AML products help identify fraudulent accounts or transactions.

“We do use an anti-money laundering product that has AI, and that’s kind of what turned us on to AI,” Kearny Chief Executive Craig Montanaro told Bank Automation News. “We did a lot of it manually. We have a very large BSA staff, but we’re currently going to be able to grow without adding new people because of the AI part of our BSA/AML product.”

Unlike big banks that build their own automation solutions, the Fairfield, N.J.-based bank is partnering with vendors to adopt AI. The bank is not alone: Senior Analyst Leslie Parrish of the Aite Group surveyed executives at 22 banks, credit unions and fintechs and found 30% planned to adopt AI for collections. The survey, half of which were at institutions of at least $30 billion in assets, also found 44% intend to invest in collections management software to automate.

“For collections, lenders mentioned using AI to better segment customers in certain communication and treatment strategies, trying to keep them out of that collections process, if at all possible,” Parrish said.

Financial institutions also plan to increase their use of AI in the loan cycle, she said. Forty percent reported they would use AI for originations, and 55% of the responding banks said they are already using AI for both marketing and fraud detection, the survey found.

While Montanaro would not say which vendor the bank had partnered with for its BSA/AML solution, Kearny in July announced a partnership with Neocova, a cloud-based AI startup that specializes in solutions for community banks and credit unions, to analyze its customer data.

The partnership is not surprising, given that Kearny is one of several banks that funded the St.Louis-based startup’s $9.5 million series A round. The funding round was composed entirely of banks, including Coastal Community Bank, First Financial Bank, Bank of St. Elizabeth, the Provident Bank and Sunwest Bank.

Neocova was founded to help smaller banks compete, Chief Technology Officer Dino Pietropaolo told BAN. In addition to its BSA/AML module, the company offers several AI- and machine learning-based tools, including an open API enterprise technology platform that runs in parallel to a financial institution’s main core; an AI-based data analytics/visualization module; and a tool that interfaces with the core for general ledger, reporting and other functions.

Most banks the vendor deals with “understand that to remain relevant … with their customers and to keep pace with larger banks, that modernization is essential,” Pietropaolo said.

Kearny’s goal in partnering with the vendor is to automate what has been a manual manipulation of data, replacing a business analytics system “from one of the major data processors” that was not delivering what the bank needed, Montanaro said.

“What we found was the analytics piece is very manual; it’s not very user-friendly, it’s very basic,” he said. “AI can handle the volume of data coming in. It is the perfect example of why you would use AI with this platform: to crunch the data, manage it, look at it, categorize it and get some insights on the customers and their behaviors,” he added.

The CEO’s vision is to be able to overlay different types of customer information from outside the bank’s core information to achieve a better understanding of its customer base. Montanaro estimated it will take six months to get enough customer data to have the AI tool up and running, to gain insight into customer behavior.

For example, Kearny might have a customer’s checking and savings account, but not their mortgage account, and ACH transaction data would reveal whether they were paying a mortgage to another bank. With that knowledge, Kearny might be able to target the customer with offers for refinancing or a home equity line of credit. Using AI to perform the data analytics can help fill in the picture of what customers are doing and what products the bank can offer them, Montanaro noted.

And Kearny plans to continue investing in AI: Its next project will be introducing an AI-powered chatbot on its website to help ease traffic away from its call center.

“We’ll use AI to track what the questions were from customers, what potential issues we could have with products, and I can take that data and help us sift through it so we can focus on issues or problems, or trends with products or trends with customers that are having issues … so that we can improve the customer service levels and the customer interaction,” Montanaro said.