Season 1 Episode 4 – How AI Helps Credit Unions in Today’s Changing Market
Justin Wickett, CEO and co-founder of Informed.IQ met with host Frank Diekmann for a special Origence podcast recorded at Lending Tech Live ‘23. Justin shared insights on how automation, machine learning, and cutting-edge AI helps credit unions become more efficient in today’s evolving market. Below are excerpts from the podcast. You can listen to the full recording here.
Frank: There’s a lot of discussion about efficiencies and new technologies, etc. Artificial Intelligence is a pretty broad term. Can you tell us what it means to you? What is machine learning and how does it help credit union lending?
Justin: AI is all about emulating human behavior. And machine learning is a subcategory that gets into the underlying software and heuristics associated with presenting that emulation. So at Informed, AI has been core to everything that we do. We are teams of computer scientists from companies like Google, Salesforce, Microsoft. we’ve worked for seven years on US indirect auto loans, turning the documents and data into decisions for faster funding.
Frank: And you have a relationship with Origence. Can you tell us what is involved with that?
Justin: It’s a fantastic partnership. We are like the “Intel inside” of Document Process Automation (DPA). That’s the initiative that Origence is rolling out to credit unions nationwide. We have pre-trained AI models on over a billion different data points across 50 million loan jacket documents.
Frank: I’d be curious to know where you find confusion or misunderstanding around what AI is and what it can do. What have you found?
Justin: Often, AI is perceived as a magic silver bullet that will solve all problems in the organization. And it’s really important to distill down to the specific use case where you will deploy AI. You need model risk management controls to validate the AI’s precision, any biases associated with the AI and model drift. That’s why it’s important to partner with a vendor with extensive experience providing AI solutions to others in your industry.
Frank: If I’m a credit union, and I want to take advantage of that recipe for success, and I approach Origence and informed, how do you respond? What do they need to do first in order to begin a relationship?
Justin: Well, the beauty of the partnership with Origence is that so many credit unions already use the CUDL platform to receive credit applications and send back credit approvals to close to 20,000 car dealers across the country. They can instantly take advantage of the DPA solution and can speed up their loan funding process. They can remove some of the inaccuracies and issues that come up when funding indirect auto loan.
Frank: I have to ask a follow up question. There’s a lot of fear around AI. Is it anything for a credit union to be concerned about if they enter into such a relationship, or some of those fears, just overblown?
Justin: No, I don’t think that the fears are overblown. It’s really important to to think about your use cases and prioritize those in which your organization is going to be deploying AI. AI has the potential for huge efficiency gains, but you can also get into trouble trying to deploy AI in certain parts of your origination’s operations, working with the wrong vendors that don’t have the right controls in place to monitor accuracy and bias.
Frank: You mentioned the efficiency gains the credit unions with which you and Origence have worked. What are they seeing?
Justin: We’re able to reduce manual data entry by about 80% from the loan jackets that credit unions receive. The AI is capable of automating the tasks – the manual verifications that would otherwise have to be done. So those are huge efficiency gains for credit unions. And we think about how do we strengthen the credit unions’ value proposition to its members and dealers. If we can free up staff within the credit union so they can provide that human touch, that delightful member experience, or strengthen the relationship with the dealers, that’s an incredible value.
Frank: How has AI changed the decision making process in regard to lending, especially around someone who may oversee a lending department?
Justin: There’s an opportunity for real time experiences. Before a car dealer would submit a credit application that could take hours if not days to get a response back. With AI there’s the opportunity for instant decisions. But once the car dealer gets their credit decision and they decide they want to continue working with that credit union, they want to get paid for the vehicle that was just financed. It can take up to 30 days. Often the average time to funders 14 days at a credit union and Informed enables that funding experience to get compressed down to a matter of literally minutes.
To hear more of the podcast, listen here.
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