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Improve the Experience for Turn-Down Applicants

Updated: Jan 25, 2022

What percentage of loan applicants at your Credit Union are turned down? Based on what we've seen, this figure typically varies somewhere between 25 - 50% depending on the demographic attracted, region, and charter.


While Credit Unions focus on providing a "good lending experience for borrowers", they often neglect their "turndowns", i.e. applicants for whom they have nothing to offer. Many applicants receive a hard "No" and an adverse action letter without direction or other offerings.


More infuriating even - or at least infuriating to the author - new startups have emerged that effectively reach this turndown segment, approve higher interest loans with origination fees, and then resell these debt portfolios back to Credit Unions as "seasoned loans".


In this article we’ll go through:

  • What the average Credit Union "turndown" looks like

  • How Credit Unions can serve their turndown audience most effectively

  • How to use new FinTech players to reduce "bad turndowns"


The Profile of a Turndown


A Credit Union turndown is very different than the typical turndown of a broad based lending platform or auto lender. The chart below illustrates the credit score distribution for 19,000 applicants, who applied for an auto loan across a group of Credit Unions:

The average Approved applicant had a credit score of 717 compared to the Rejected applicant with an 630 average. Coincidentally, 25% of rejected applicants still had scores above 700.


If we examine income distributions of these applicants, we see smaller gaps between approvals and rejects:

The 50th percentile applicant had $47,000 in annualized income, compared to $59,000 for the average Approved applicant.


Most auto lenders would kill for applicants with a credit profile this high. Below is a comparison to some well known auto lenders:


  • The average used car buyer in the U.S. has a credit score of 665¹, closer to rejection average than to acceptance average for most Credit Unions.

  • Carvana - the second largest used car dealer in the U.S. - securitizes their loan portfolios. The average credit score ranges from 634 to 636².


The Turndown Experience


There’s a host of reasons an applicant might be turned down. No matter what the reasons, the experience of being turned down can be embarrassing and discouraging:


Most Credit Union Loan Origination Systems don’t give applicants immediate loan decisions. Instead, the applicant will receive a "pending" decision, commonly referred to as "Deferred". If the loan officer ultimately declines the application, the applicant receives some form of adverse action notice via letter, email or all of the above.


Some applicants receive offers for "credit builder loans" as a cross-sell, completely unrelated to the actual monetary needs of the applicant. As you can imagine, a turndown is a lose-lose:

  • the applicant doesn't get the financial product (s)he is applying for

  • the Credit Union misses out on the opportunity to acquire a new Member

  • the applicant's financial well-being will only go down from here


The share of turndown volume surprised us. A large portion of the turndown applicants:

  • still have moderate income and high debit card spend

  • are credit-migrating upwards, i.e. on a trajectory to improve their credit scores and

  • end up choosing worse loan products without the benefit of financial education from the Credit Union

We are on a mission to help Americans with their financial well-being. We are therefore heavily investing into products to help Credit Unions find alternative "homes" for their turndown applicants while allowing them to become a Member.


Direct-to-Consumer FinTechs are Monetizing your Turndowns


It would be naive to think that applicants simply "don’t need to get credit" once they’ve been turned down. We have observed that turndown applicants revert to online platforms such as Credit Karma and LendingTree to satisfy their financial need:

The Direct-to-Consumer FinTechs who are "buying" their traffic from these online platforms use a combination of advanced approval algorithms and applicant vetting to instantly provide loan decisions. When funding the loan, some of these FinTechs charge high loan origination fees and directly connect to the borrowers' payroll to reduce loan servicing costs.


Eventually, these Direct-to-Consumer FinTechs sell the "seasoned" loan portfolio to Credit Unions. Credit Unions basically buy the loans and pay exorbitant origination fees for debt they initially rejected. The Member is left in the worst position:

  • Feeling a form of embarrassment that the primary financial institution rejected his/her loan application

  • Ending up with a worse offer where the lender

    • pays a "lead fee" of $100-200 to the online platform

    • charges a large origination fee to the borrower

    • charges excess interest spread and then re-sells this same portfolio to the Credit Union who first rejected the same borrower


We are here to help!


How can we help Credit Unions improve the experience for turndown applicants? While our next piece will have very concrete recommendations, here are three themes that we've seen as best-in-class among our clients:


Step 1: Think beyond "the loan" and consider "the Member" as a whole.


Many of our clients think about the applicant in a very holistic way. Rather than simply accepting or rejecting a loan application, we've observed how many Credit Unions did an incredible job at looking at the Member as a whole.


By investing in the applicant's financial well-being, we've seen many underserved consumers quickly migrate upwards in credit thanks to the faith the Credit Union put in them. Some of these applicants for example started their membership with a debit card and an auto refi. We've seen Credit Unions give these same Members credit cards and unsecured loans within months of "building credit history".


Step 2: Credit Unions also can use "advanced algorithms".


Upstart, Upgrade, and LendingTree have huge data science teams attempting to squeeze every last bit of margin out of a given applicant. These Direct-to-Consumer FinTechs have to become very good at modeling credit because the product they're selling is "money", i.e. the ultimate commodity. Credit Unions, instead, have inherent advantages:


As tax-exempt non-profits, Credit Unions can forego larger margins on a per loan basis and instead focus on the Members' well-being. Nevertheless, we are strong proponents of continuously improving credit decisioning and have identified a number of companies who are selling "credit models as a service".


These companies pool credit and loan performance data from several Credit Unions and thereby reach a much larger scale than any individual institution ever could. Let us know if you're interested to learn more and we'll put you in touch.


Step 3: Outsource the loan, insource the Member:


The applicant came to you for a loan. That's amazing! Direct-to-consumer FinTechs pay fortunes to acquire users. Instead of rejecting the applicant, we are building a platform that connects (white-label) lenders across the entire credit spectrum.


Through participating in this digital marketplace, a Credit Union can refer loans to other (white-label) lenders while keeping the relationship with the consumer. When the time/credit is right, the Credit Union can recapture the loan via refinancing and everyone wins.


What does this mean for my Credit Union?


What can I as a Credit Union leader do today to help turndown applicants, increase Look-to-Book and grow my Membership?

  • Look at your applicants as Members and not as loans

  • Explore approaches to more advanced loan decisioning

  • Onboard the Member by outsourcing the loan until the time/credit is right to recapture

Our next piece will examine even more concrete opportunities to increase look-to-book and monetize your existing loan application volume! As always, if you’d like to discuss potential solutions and how digitized lending experiences can help, feel free to reach us out at contact@withclutch.com.

 

¹ Experian 2021 Study cited by Nerdwallet https://www.nerdwallet.com/article/finance/credit-score-needed-to-buy-car#:~:text=A%202021%20report%20released%20by,loan%20or%20lease%20was%20732.


² SPCGlobal collateral comparison for CVNA Securitized notes: https://www.spglobal.com/_assets/documents/ratings/research/11865844.pdf


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