Pattern 04Auto lendingFixes recommended · Control next

The ProcessArc Pattern Library

Why approved auto loans never fund and how to win them back.

A pattern we see across banks and credit unions. Members get a yes, then hear nothing useful, and the dealer funds the car.

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Chapter 1 of 7 · The pattern

Your approval is one offer among several.

A member applies for a direct auto loan and gets approved. Then the clock starts. They're still shopping, often at a dealership with its own financing ready to sign that afternoon.

Pull-through isn't lost at the decision. It's lost in the silence after the yes.

When application demand holds steady but fewer approved loans fund, the problem is the process and the experience, not the rate.

This pattern walks through one real engagement. Not because it's unusual, but because it isn't.

Chapter 2 of 7 · How to spot it

6 signs this pattern is in your operation.

If three or more sound familiar, the rest of this pattern is probably about you.

01
Steady demand, falling funding
Applications hold up, but the share that turn into funded loans keeps slipping.
02
Digital lags the branch
Online applications fund at a much lower rate than branch or phone ones.
03
No price until the end
Members can't see a rate range or terms until they're deep in the application.
04
Slow, generic follow-up
After approval, outreach is manual, late, and the same for every member.
05
Members call to ask
A big share of inbound calls are members checking where their loan stands.
06
Dead-end applications
Credit freezes, unclear loan purpose or missing vehicle details stall files nobody closes out.

Next step · Self-assessment

Does this pattern sound like your operation?

8 yes/no questions, scored out of 9. It isn't a scientific instrument: it's a fast way to see whether this pattern applies to you. Your score is free.

0–2: Ahead of the pattern
3–5: Moderate exposure
6–9: Strong match with this pattern

Question 1 of 8Pattern 04: Auto lending

Has your direct auto loan process gone more than 12 months without being mapped end to end, step by step, across every channel?

Counts double. An unmapped process is where the other problems hide.

Takes about two minutes

Next step · ROI calculator

Put your own number on it.

You have already paid to win every approved application: marketing, staff time and the credit pull. Enter your own numbers to see what each point of pull-through is worth, then register to see your result.

Auto loan applications a yearDirect auto applications, all channelsCurrent pull-through%Funded loans ÷ applications

Average loan amount$Average funded direct auto loanTarget lift in pull-throughptsIn percentage points, e.g. 23% to 25% is 2

Pre-filled with an illustrative example: 20,000 applications a year at 23% pull-through and a $25,000 average loan. Replace the numbers with your own.

Your numbers

Funded loans a year today: •,•••
Extra funded loans a year: +•••
Extra originations a year: $••,•••,•••

See your numbers, and get the full pattern with them.

Name and work email. Your numbers stay with ProcessArc.

Chapter 3 of 7 · What it costs

Where the loans went, and what it cost.

Application demand held steady. What fell was the share of applications that turned into funded loans.

28% → 23%pull-through (funded loans ÷ applications) over two and a half years
15% vs 26–30%digital pull-through, against branch, phone and video channels
50%+of approved digital loans never funded

~2,100

fewer funded loans

a year at today’s pull-through

~$52M

a year in originations

that went somewhere else

The online application, step by step

Started100%
Personal details88%
Loan features82%
Disclosures72%
Completed72%

28% of members who start an online application never finish it; 12% leave at the very first step.

Chapter 4 of 7 · Why it happens

The yes comes fast. Everything after it doesn't.

We mapped every channel end to end: 76 steps and 12 decision points between application and funding, and 13 gaps.

Intent found too lateLoan purpose and vehicle details are captured late, so guidance arrives after the member has moved on.
No early priceWith no rate range or terms up front, members drop out in the first screens.
12% first-pass yieldOnly about 1 in 8 applications went from start to funding without rework.

Digital

Friction in the first screens: 12% leave at step one
Human contact comes too late to rescue the application
Generic outreach misses the moment of decision

Branch and phone

Stronger upfront intake leads to better funding
Manual, inconsistent follow-up loses approved members
Legacy systems force manual workarounds

After approval

Credit freezes found late, after the credit pull
Unclear when a change needs full re-underwriting
Stalled applications never closed out

The root cause.The process was built to reach a decision, not a funded loan. After the yes, nobody owned the member's next step, so approved demand leaked away to whoever followed up first.

Chapter 5 of 7 · What fixes it

What to automate, and what to keep human.

Make the next step obvious, fast and personal, and let the system carry the routine follow-up.

Automate

Real-time status messages by text, email and app
Credit-freeze checks before the credit pull, with clear next steps
Early rate ranges and terms from initial inputs
Re-engaging members who abandon an application
Closing out stalled or incomplete applications

Keep human

A structured first contact for every approved online application
Guidance tailored to the loan's purpose: purchase or refinance
Exceptions and re-underwriting decisions

Guiding principle

The yes is the start of the sale, not the end.

Every approved application gets an owner and a clear next step within hours, in the channel the member chose.

Six fixes ranked by impact, and a simpler path to funding.

Thirteen gaps were sorted by effort and impact. These six went forward as business cases.

Business caseExpected impact

Structured first contact for approved online applicationsHigh: the 50%+ approved-not-funded gap

Re-engage abandoned applicationsHigh: 28% of started applications

Real-time, status-based messagesMedium: fewer status calls

Credit-freeze check and alert before the pullMedium: no dead-end files

Clear loan-purpose and title rulesMedium: less rework

Requirements for the new loan platformLong-term: fixes built in

About 25% of inbound lending calls were members checking their loan's status.

A simpler path to funding

76 → 40 steps from application to funding.
12 → 8 decision points.
The redesigned journey, built into the new loan platform, gives every channel the same predictable route from approval to funding.

Chapter 6 of 7 · Where it stands

Target impact, and where this stands.

The goal: lift pull-through on direct auto loans by 1 to 2 points.

23%

pull-through at the start, down from 28%

+1 to 2 pts

the target lift in pull-through, from process and experience fixes

~$11M–$21M a year

In extra originations from a 1 to 2 point lift, at the same application volume. Each point is roughly 420 more funded loans a year. Two paths: near-term fixes delivered on today’s systems, and structural fixes written into the requirements for a new loan origination platform.

Project status

Define, Measure, Analyze, Improve, Control (DMAIC): the five phases of a Lean Six Sigma project.

Define, Measure, AnalyzeComplete
ImproveFixes recommended
ControlNext

Figures are estimates from the project's own channel data. Measured results will be added to this pattern.

Chapter 7 of 7 · The pattern, restated

This wasn't unique to one institution, one loan system, or one channel.

It's what happens when a process is built to reach a decision instead of a funded loan. Approved members rarely say no. They just stop hearing anything useful, and someone else funds the car. The fastest gains are in the digital channel, where the loss happens early and is driven by experience, not price.

Next step · Structured thinking template

The 5 questions we ask, in order, every time.

You don't need a Black Belt to start. You need honest answers.

01DefineWhat is the goal in plain numbers (for example, +1 to 2 points of pull-through), which channels are in scope, and who owns the funded loan, not just the decision?
02MeasureWhere do applications drop out, channel by channel and step by step? How long after approval does a member hear from you, and how many calls are status checks?
03AnalyzeWhich screens lose members before they submit? What stops approved members from funding: no early price, credit freezes, unclear loan purpose, or silence?
04ImproveWho owns the first contact after approval? Which messages, credit-freeze checks and rate ranges can the system deliver? Which stalled files should be closed out?
05ControlWhich measures will show the fix is holding six months from now (pull-through by channel, step-by-step drop-out, status-call share), and who owns each one?

Take it with you

Pattern 04: Auto loan pull-through, with diagnostic toolkit (PDF, 14 pages)

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Chapters 3 to 7: what it costs, the root cause, what to automate and what to keep human, and where it stands
Your own result from the ROI calculator
The structured thinking template we use on every engagement
Pattern 04: Auto loan pull-through, with diagnostic toolkit (PDF, 14 pages), to share with your team

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Why approved auto loans never fund and how to win them back.

Your approval is one offer among several.

6 signs this pattern is in your operation.

Steady demand, falling funding

Digital lags the branch

No price until the end

Slow, generic follow-up

Members call to ask

Dead-end applications

Does this pattern sound like your operation?

Put your own number on it.

Read the rest of Pattern 04: Auto lending.

Every pattern starts with a conversation.