Meet The Lending Finalists For The 2022 Innovation Series

This year’s lending solutions provide inventive ways for credit unions to serve members.

Think of it as Shark Tank, but with a credit union spin and it’s just been renewed for another season.

Read about the finalists by clicking on the links below.


The 2022 Innovation Series from and Callahan Associates is underway. Every year since 2018, this series has offered a select group of suppliers 10 minutes each to impress an audience of credit union decision-makers. It’s simple: Each vendor pitches its offerings and attendees vote on their favorites.

The Innovation Series was a hit from the get-go and continues to grow in popularity. This year’s focus areas include digital solutions, lending, and member experience.

Read on for more from this year’s lending finalists, then click here to registerfor the webinar.


Describe your innovation.

Mike Horrocks, VP of Product Management, Baker Hill

Mike Horrocks: Baker Hill NextGen is a single unified platform that streamlines loan origination and portfolio risk management for commercial, small business, and consumer lending, delivers sophisticated analytics and marketing solutions, and is the expert solution for relationship management and analytics for financial institutions.

What opportunity or challenge does it address?

MH: If credit unions don’t modernize their traditional approach to lending with technology, they risk losing market share to the online lenders who have adapted. Baker Hill NextGen makes multiple, disjointed, manual systems a thing of the past by allowing credit unions to meet their members where they’re at, whether that’s online, in a branch, or a hybrid of both.

How does it increase member value?

MH: With Baker Hill NextGen, members have renewed access to their credit unions. With tools like the Banker Application, Online Loan App, and Client Portal, Baker Hill NextGen allows for more communication between the credit union and the member. These tools reduce the number of times that a member has to input information, reducing both paperwork, errors, and the amount of time it takes to accomplish tasks.

What differentiates this innovation from competitors?

MH: Baker Hill is built by bankers, for bankers. With decades of experience in the financial technology industry, Baker Hill NextGen has the resources to anticipate what credit unions need in order to generate growth and profitability. Other solutions are often contracted out, meaning the company that sells them isn’t the one building or supplying the solutions. Others are cobbled together, meaning they don’t work as efficiently and have little room for configuration. For more information on how Baker Hill stands out from its competitors, visit


Describe your innovation.

Wesley Zauner, VP of Product, MeridianLink

Wesley Zauner: MeridianLink Debt Optimization / Cross-Qualification: This innovative product feature utilizes known debt and liabilities from a mortgage application to pre-qualify the member / consumer for consumer loan opportunities (auto, personal, credit card) available through the financial institution. Debt Optimization uses the pre-qualified consumer loans to see if refinancing of existing debt would allow the consumer or member to qualify for a better mortgage (I.e., lower rate, lower closing costs, better PMI). Cross-Qualification after the mortgage closes can help free up additional cash flow for the member or consumer, which provides a superior customer experience and increases application volume for the financial institution. Consumer or member applications can be generated from either Debt Optimization or Cross Qualification with data that is pre-populated from the mortgage application.

What opportunity or challenge does it address?

WZ: From a borrower’s perspective, there is the potential to lower monthly payments on existing debt or qualify for more loans, with a greater likelihood of receiving more funds at better rates through the restructuring of debt. Debt Optimization / Cross Qualification is the only solution that we are aware of that pairs mortgage eligibility and pricing with consumer eligibility and pricing. This combination provides a more comprehensive approach which enables the lender to provide superior customer service. Members and consumers may not realize there are often separate mortgage and consumer departments at credit unions, so Debt Optimization / Cross Qualification provides a better experience for them to know the full range of offerings. Plus, with Debt Optimization / Cross Qualification the mortgage loan officer is more informed of offerings than they would be traditionally, so there is a more streamlined experience for all parties.

How does it increase member value?

WZ: This innovation increases member value in several meaningful ways:

  • Improve the approval rate for mortgage loans for members
  • Improve the interest rate and/or decrease the closing costs
  • Free up additional monthly cash flow for members
  • Streamlines the cross-selling of mortgage applications into consumer products offered by the credit union

Added benefits for credit unions include:

  • All these positive changes lead to an increase in overall loan volume
  • Improve customer satisfaction

Many mortgage loan programs have eligibility and pricing rules that depend on debt-to-income ratio. By utilizing Debt Optimization, you can avoid the debt-to-income denial rules or pricing hits. Many consumers have existing credit card debt or auto loans, making Debt Optimization relevant to most members.

What differentiates this innovation from competitors?

WZ: Debt Optimization / Cross Qualification bridges the traditional silos within a financial institution between consumer and mortgage departments. Additionally, this innovation increases the likelihood of future business with members and consumers when they have a valuable experience. To deliver this innovation, a financial institution needs both a mortgage LOS (Loan Origination System) and consumer LOS, mortgage PPE (Product and Pricing Engine) and consumer PPE. Also, it is necessary to have a mechanism for transferring credit between all of these. MeridianLink currently has the technology to bring all these together, without which this feature would not be possible. Of note, the MeridianLink Mortgage Debt Optimization solution is patent pending.


Describe your innovation.

Jeff Keltner, SVP, Business Development, Upstart

Jeff Keltner: Upstart is a leading artificial intelligence (AI) lending platform designed to improve access to affordable credit while reducing risk and costs. We partner with credit unions to leverage our innovative credit model to approve almost twice as many borrowers, with fewer defaults. In addition, our white-label digital experience allows our credit union partners to provide applicants with a highly automated loan process for both personal and auto loans, leading to higher conversion rates and happier customers.

What opportunity or challenge does it address?

Jeff Keltner: Four in five Americans have never defaulted on a credit product, yet less than half have access to prime credit. The implication is eye-opening. Upstart’s mission is to enable effortless credit based on true risk by enabling our credit union partners to deliver an all-digital consumer lending experience powered by AI. The Upstart Consumer Lending Platform employs powerful AI technology enabling higher approval rates, lower loss rates, and a highly automated digital loan approval process for both personal and auto loans.

How does it increase member value?

Jeff Keltner: With Upstart’s innovative technology, credit unions can transform their consumer lending program and grow their loan portfolios, while effectively managing risk. Upstart’s offering allows credit unions to identify and approve more creditworthy members – helping to put members on a more stable financial footing while also growing loan originations and balances. In addition, Upstart’s platform allows credit unions to provide a simple process for new members to join a credit union while applying for a loan – helping CUs not only serve existing members, but grow their member base as well.

What differentiates this innovation from competitors?

Jeff Keltner: Upstart’s AI model uses over 1,600 variables including credit experience, employment history, educational background and more to create a more holistic view of the borrower. The Upstart AI model employs AI and machine learning techniques that excel when there are many variables and the interaction effects between them are complex and subtle. As a result, Upstart can provide up to 8x more accuracy over simple credit models and the decision can be made in seconds. Unlike many loan purchase programs, Upstart is able to consistently generate between $1-50M per month of profitable loans for credit union partners, helping them deploy excess liquidity. In just one year, Upstart’s originations grew by 244% YoY, leading to over $3.13B in personal loan originations available to lending partners.

In addition to the increased accuracy and speed of the credit decision model, Upstart offers an all-digital lending experience to borrowers so that they can apply any time, from anywhere, and on any device, including a desktop, mobile phone, or tablet. Identity verification is automated by Upstart’s fraud detection model which uses AI to pull data from hundreds of sources and cross reference them to verify the person’s identity, achieving a fraud rate of less than 30bps. With this combination, Upstart is able to approve nearly 70% of fully automated loan applications without any human intervention.


Describe your innovation.

Mike de Vere, CEO, Zest AI

Mike de Vere: A fast-growing share of credit unions is switching to AI-driven lending using Zest software. Why? Because they want to say yes to more members while giving a better lending experience. The power of AI-driven lending covers those two bases without adding risk. Big banks and fintechs are taking share from credit unions in part because they have more advanced AI credit underwriting models. They’re using better math to spot the 620s who are going to perform like 720s. Zest software lets credit unions of any size tap the power of AI and transcend the limits of traditional credit scoring. This kind of decisioning has been out of reach of most credit unions but Zest has automated all the work of building, validating, and deploying advanced AI lending models so that any CU can adopt this technology.

Zest is powerful. Models built with Zest software always outperform generic scores like FICO and custom-built logistic regression scorecards, delivering best-in-class borrower assessment. Zest is compliant. Our end-to-end model explainability has been called the gold standard by regulators, delivering transparent decisions and reason codes with confidence and compliance. Zest is swift. Intuitive automation handles all the routine model validation tasks, business analysis, and risk documentation for a smooth adoption. Zest is easy. Streamlined data ingestion and parsing make modeling preparation simple. Plus, flexible deployments and integrations make implementation and operation easy.

What opportunity or challenge does it address?

Mike de Vere: Every credit union large and small wants to identify more good borrowers. They know that millions of Americans are too hard to score and are being overlooked and underserved by legacy credit scoring, especially in low-income communities. Credit unions see it as their mission to enrich their communities, but they need to do it safely. And, for efficiency’s sake, CUs need faster and more automated decisions they can trust in order to keep up with their growth initiatives. AI can help achieve those goals.

VyStar, one of the largest credit unions in the US, needed a solution that would expand product portfolios faster and more efficiently without taking on additional risk. Using over 500 variables, Zest’s underwriting model helped improve risk assessment accuracy with deeper insights into potential borrower populations. This increased VyStar’s confidence in widening the thresholds for auto-approvals, allowing them to accept more members. GreenState Credit Union in Iowa also wanted a way to say yes to more members, especially members in low-income communities, and increase their volume of instant approvals. Its new Zest-built auto lending model delivered a 25% increase in approvals for women and more than a 25% increase in approvals for protected-class citizens.

How does it increase member value?

Mike de Vere: Credit unions that lend using Zest-built models have seen 25% to 30% increases in approval rates with no added risk by using more of their data and the advanced math of machine learning. It lifts approvals across all credit segments, channels, and products: mortgage, auto, personal loans, and credit cards. We typically see clients increase their auto-decisioning rates by fivefold after switching to Zest. But the best part is that CUs can get up and running quickly. We worked with HawaiiUSA FCU to build, analyze and deliver the model in under a week. A credit bureau is going to quote four to 4.5 months of effort. A consultant could help you build it on your own and fully document it but you’re talking about a year and hundreds of thousands of dollars. Our customers are enjoying turnarounds in weeks. Speed matters not only because CUs get a faster return for their members, but they can stay on top of their new models more easily with Zest automation and make changes quickly if the economy changes. The megabanks and credit card companies used to be the only ones able to do that. Now CUs can, too.

What differentiates this innovation from competitors?

Mike de Vere: If anything, I’d say it’s our approach to earning our client’s business. Credit unions are a show-me culture; so we put skin in the game. That means building every credit union a model tailored to its footprint, for free. If you like the prospective results, we go into partnership together to refine the model with member and non-member data, because expanding the credit box means including the performance of loans you never scored. With Zest, you get models trained on and tailored to your community and regional economy. How is a generic national score that’s one-size-fits-all good for both credit unions in Hawaii and Maine? The end result will be a model that is yours, and won’t be sold to anyone else. And every Zest model is actively monitored so that if there is a change in the market, we can quickly (within a week) refit the model and redeploy it. Our software produces models that are transparent and fully documented.

Our competitors may not be able to show you a model risk management document that fully aligns with SR 11-7? With Zest, you also have the confidence of knowing that your new model will have been tested for fairness including a disparate impact review and a search for a less discriminatory alternatives. You’ll know you’re doing your part to ensure all of your members are getting a fair shot at access to credit. With Zest you’ve got a powerful model, fully documented, tested for fairness, and monitored. But we don’t just drop off a model and run. Zest assigns every client a success team to help them through the implementation and offer advice on using the new model. This team works side-by-side with CUs all the way through live scoring and beyond for the next two, three years.

February 8, 2022

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