01 The beginning
At the desk
Loan origination system
- Amount financed
- $19,369.26
- Application
- App 7409
- Dealer
- Crestline Auto Outlet
- Borrower
- Travis Hutchins

Your last loan
App 7409 · Charged offYour next deal
App 9871 · ConditionalFor subprime auto lenders
Underbot connects your loan reports and underwriting, so what happened to your book informs the next deal.
In daily use. At a multi-state auto lender.
Two systems. One history.
Your loan origination system (LOS) holds what you knew when you bought the deal. Your loan management system (LMS) holds the payments and what followed.

01 The beginning
Loan origination system
One connected history

02 The outcome
Loan management system
Your reports show what happened; your underwriting puts those lessons to work on the deal in front of you.
See it in practice
Pick the question on your mind. Each short film shows the product at work.
01 · The dealer
Put the business a dealer sends beside what those loans became. See production, past-due balances and losses together before the next dealer conversation.
Explore Dealer Review02 · The loans behind the number
Start with the past-due total, then open the loans that make it up. Your team can see the accounts, balances and days behind that need attention.
Explore Collections03 · What came back
Follow the dollars back to the accounts. See what has been collected and where the remaining recovery work stands.
Explore Recovery04 · The next deal
Apply your credit policy consistently, with the reasons in view. Bring the history of your book to the desk, while your underwriter keeps the final call.
Explore the Underwriting Engine05 · Proving the policy
Replay past deals using only what was known when you bought them. Compare the calls with what happened, including the good loans you would want to keep.
Explore Policy BacktestThe films, stills and examples drawn on this page use fictional lenders, people and figures. Background photography, narration voice and music are AI-generated. Pressing play loads YouTube.

Part of the working day
At a multi-state auto lender, the Underwriting Engine and the Dealer Review, Collections and Recovery reports are in daily use.
For the underwriting team
100 base + 7 factors + 0 bonuses - 45 penalties = 62
Maya Chen62 · Conditional
Alex Morgan62 · Conditional
Different underwriters. The same policy call.
App 7409 · $16,101.74 loss
Review context, separate from the score.For the reporting team
App 7409 · $16,101.74 loss
The loan above. Outside the past-due total.Follow a number to its loans.
Bring what happened into the next decision.
One connected history. A better-informed next decision.Illustrative product excerpts. Fictional loans and underwriters.
Fits the way you work
Start small. One sheet, ten deals, no names. Back in three business days.
The review sheet has no box for a name, a Social Security number, a VIN or a dealer. Files, exports and connections wait for a signed NDA.
Underbot reads your records. It never writes to your systems of record.
Your files are encrypted from the moment they arrive.
Your data is never used to train or fine-tune AI models.
A memo comes back. The final call stays with you.
Nothing needs replacing. Underbot can use a connection your system already provides, called an API, read-only access to your records, or the export you already produce.
Read about data handling
Your next step
See what your last ten deals can teach you about the next one.
Any ten finished deals. The best mix: a few that paid, a few that went bad, a few you declined and one your team argued about.
No names. No Social Security numbers. No dealer. The sheet asks about the deal, never about who.
Your memo comes back within three business days.
If we can't show you at least one thing about your own book you didn't already know, we'll tell you straight.
The sheet has no box for a name, an address, a Social Security number, a birth date, a VIN or a dealer. Want an NDA first? Ask and it's in your inbox the same day.
See a sample findings memo01 / Ten deals re-scored
Each deal gets a score, a decision and the reasons behind it. Here is one example from the films.
10 files. The same policy. Every reason in view.
A closer look App 9871
A different structure. A different decision.
02 / The math behind every score
Deal 3 scores 100 + 67 + 15 - 45 = 137. Tier A, Approve.
Helps most: job tenure of 5+ years (+20), DTI under 35% (+15), owns home (+12).
Hurts most: LTV of 110 to 119% (-10), a 72-month term (-10), one or two 30-day lates in 12 months (-8).
It passes, but the risk stack is hot enough to review before funding.
03 / A plain-English findings memo
The original structure falls short of the policy. More cash down brings it into the conditional tier.
Confirm the borrower can meet the terms and complete the stipulations before making the call.
04 / The 30-minute walkthrough