INTERNAL

Soft prequal: how the estimate works

Before a borrower reaches Sales Onboarder, we estimate their chance of a loan offer from three things they already tell us in the Lightning App. Here's exactly how the number is calculated.

Data last pulled: October 14, 2026

Why this matters: the loan carrot

If borrowers know they're likely to get a loan, they have a reason to keep going. Showing the estimate early works like a carrot dangled in front of them: it makes finishing and submitting the application feel worthwhile, so more people continue the process.

This is our working hypothesis.

The pipeline

1
Pull past applications
The last 24 months of sales-assisted Lightning App applications that have all three answers: time in business, credit score range and annual revenue.
2
Bucket them
Each application lands in one time-in-business × credit × revenue group, for example 1–2 yr · 650–699 · $250–500K.
3
Check what happened
For every application sent to a lender, we check whether that lender made an offer.
4
Calculate the rates
Per group, per lender and for “any lender”: offer rate, plus average and median offer amount. Saved as a lookup table.
5
Match a new borrower
We put them in the same group and show the matching row. No model, just a lookup.

Internal tool

Cohort stats

How offer rates change by industry, requested amount, requested share of revenue and state. Pick a dimension, then filter by lender or sample size. Each row is the share of applications in that group that got at least one offer.

LenderGroup sizeSearch

Applications

43,278

15 of 15 groups

Overall offer rate

62.1%

26,897 offers

Highest

72.0%

Health Services

Lowest

47.2%

Travel & Transportation

Top lenders by offer rate in this view (100+ applications)

By industry


4,108	2,958	72.0% +9.9 pts	$136,917	$97,400
4,665	3,193	68.4% +6.3 pts	$113,954	$75,000
1,792	1,196	66.7% +4.6 pts	$113,179	$70,000
3,236	2,075	64.1% +2.0 pts	$104,147	$60,000
2,643	1,679	63.5% +1.4 pts	$92,711	$55,600
683	422	61.8% −0.3 pts	$111,398	$68,800
4,995	3,079	61.6% −0.5 pts	$129,656	$72,000
8,124	4,963	61.1% −1.0 pts	$104,593	$65,000
5,351	3,239	60.5% −1.6 pts	$112,258	$67,500
131	79	60.3% −1.8 pts	$105,243	$60,920
727	434	59.7% −2.4 pts	$112,762	$70,000
547	324	59.2% −2.9 pts	$97,152	$60,500
369	216	58.5% −3.6 pts	$138,626	$75,000
2,287	1,331	58.2% −3.9 pts	$92,257	$53,600
3,620	1,709	47.2% −14.9 pts	$65,029	$35,000

Select a row to see how each lender did in that group.

Groups and lenders with fewer than 20 applications are left out of the data, so totals understate the full volume. Small groups swing a lot, so use the group size filter before reading anything into a rate.
The pts column compares each row to the overall rate of the rows in view, so it moves as you filter. These factors overlap (for example, larger requests often come from larger businesses), so one factor alone can overstate its own effect.
Not an approval rate. An offer means at least one lender made an offer on a submitted application.