Your best application for artificial intelligence (AI) might be finding opportunities you never knew existed.

Credit unions are exploring AI-based technology solutions to:

• Identify worthy loan applicants who might otherwise face rejection.
• Boost loan volume with automated decisioning.
• Improve security through voice recognition.
• Integrate voice, video, and smart speaker channels.
• Predict potential risk within loan portfolios.
• Explore the possibilities hidden within their data.

The projects are varied, but they share a common goal: to go beyond business as usual while gaining the AI experience required to remain competitive.

Getting started

AI is a branch of computer science that blends computers’ data capabilities with human-like intelligence to complete specific tasks. AI solutions often include “machine learning” algorithms to capture specific data from interacting with human users, which enables an AI tool to improve over time.

John Best, CEO of Best Innovation Group, advises credit unions to take advantage of their “superpower of collaboration” to explore AI through credit union service organizations and joint projects with financial technology (fintech) companies.

He says credit unions should approach AI with the same intensity allocated to a core processing conversion. The first step is strengthening data analytics and developing data leaders.

“If your data analytics people don’t already have a seat at the table, you’re behind,” Best says. “This is a culture shift in the organization.”

He adds that credit unions must also think about what’s possible with AI.

Increasing loan acceptance

Northern Hills Federal Credit Union in Sturgis, S.D., began using an AI-based loan decisioning tool to increase approved loan applications by a projected 25% to 40%.

Floyd Rummel III, CEO at the $125 million asset credit union, says members used federal stimulus payments to increase savings and pay off loans during the pandemic. That dropped Northern Hills Federal’s loan-to-share ratio from 78% in 2020 to 68% in June 2021 and reduced interest income.

The credit union uses a loan decisioning tool to reverse that trend by sorting applications into three categories:

1. Green applications qualify for automatic approval based on credit score so members can get quick, after-hours approval online.

2. Red applications fail to meet lending standards and are declined with an offer of help and information. 

3. Yellow applications don’t qualify for automatic approval but might qualify after the credit union gathers more information. The tool relies on LexisNexis data to add information about utility bill payments, address changes, and other factors.

Previously repaying a credit union loan also impacts decisions.

Rummel says Northern Hills Federal focuses on “yellow” applications with the goal of approving more loans more quickly. As the credit union reviews and eventually approves or declines these applications, the AI tool learns how to handle similar applications in the future and place more of them in the right category without employee intervention.

“As the yellow category becomes smaller, my loan people have additional time to spend with these applicants,” Rummel says.

Northern Hills Federal prepared for launch by:

• Compiling five years of loan application data through the AI tool to confirm it’s reviewing loans appropriately.
• Adjusting parameters for acceptable levels of charge-offs and delinquencies, which are expected to increase along with loan volume.
• Reassuring employees that AI will reallocate resources, not eliminate jobs.

Rummel says the biggest challenge was integrating the AI tool with the online service bureau the credit union uses for core processing. He hopes Northern Hills Federal’s efforts will prompt other small credit unions using the same service bureau to pursue AI.

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