Chris Wyatt
Venture Concept · Supplier Credit
Essay

Pulse Underwriting

Card networks and issuers cannot underwrite long-tail B2B suppliers because they cannot see eighteen months of bank statements. Pulse is the real-time underwriting layer that turns live AR/AP signal into a synthetic credit file, unlocking commercial card acceptance for the suppliers most B2B platforms reject today.

$89T
Global B2B payment flow, 2024
Juniper Research
$575B
US commercial card purchase volume, 2023
Nilson Report
$1.6T
B2B working capital trapped in payable terms
PYMNTS-American Express

01 · The problem

Half the B2B supplier base is invisible to commercial-card underwriting

Visa, Mastercard, and the major issuers can profitably issue commercial cards to suppliers with eighteen months of clean bank data. The other half of the supplier universe (newer entities, sole proprietors, complex ownership structures) cannot get underwritten at all. The result is the largest under-served credit market in B2B.

18 months
Bank-statement requirement for traditional issuance
Industry standard
9-12 days
Median manual underwriting cycle for SMB issuance
Operator estimate
60%+
Of small US suppliers cite credit access as primary growth barrier
Federal Reserve SBCS, 2024

02 · The thesis

Live AR/AP signal beats eighteen months of bank statements

A supplier's AR aging, payment-terms history, and customer concentration tell you more about their next-90-days credit than eighteen months of bank statements ever did. The data exists, scattered across ERPs, AP platforms, and bank feeds.

Pulse aggregates that signal, normalizes it, and emits a real-time underwriting score issuers can plug into their existing flow. Synthesis is what's missing. Modeling capacity is not.

03 · The product

What it does

01

Live AR/AP signal aggregation

Pull from ERPs, AP platforms, bank feeds, and B2B network metadata into a unified credit profile.

02

Synthetic underwriting score

A real-time, explainable score callable from any issuer's underwriting flow, with feature-level provenance.

03

Continuous re-underwriting

Credit lines adjust on AR aging signal, not on annual review cycles. Defaults compress.

04

Embedded finance API

Drop-in endpoint for B2B platforms that want to extend payment terms to suppliers their card processor would otherwise reject.

04 · Why now

The timing case

  1. 1

    Visa and Mastercard have publicly committed to expanding commercial-card acceptance into the long tail. The underwriting bottleneck is the constraint.

  2. 2

    Open banking and ERP API access are now production-grade in the US, removing the data-acquisition cost that historically made this uneconomic.

  3. 3

    Embedded-finance infrastructure has matured. B2B platforms now expect to issue credit themselves rather than route customers to a third-party issuer.

05 · Why I see it

The view from inside the work

I built Finexio's supplier enablement engine on top of J.P. Morgan rails and have spent a decade on the issuer-network side of the market. The constraint is not credit appetite. It is underwriting input.

06 · Comparable references

What's already in the market, and where the gap is

An honest read on the adjacent landscape. Not every comparable is a competitor. Some are partners. Some are the market the venture displaces.

Reference
Dun & Bradstreet, Experian Business
What they do
Static commercial credit bureaus built on tradeline reporting.
Gap
Backward-looking. Pulse uses live AR/AP signal that updates daily, not quarterly.
Reference
Plaid, Codat, Rutter
What they do
Financial-data aggregation across bank and accounting systems.
Gap
Sells the data feed. Pulse sells the underwriting score on top of it.
Reference
Resolve, Balance, Slope
What they do
Embedded B2B trade-credit products with proprietary underwriting.
Gap
Bundle the underwriting with the credit balance sheet. Pulse is balance-sheet-agnostic and underwrites for any issuer.
Reference
Issuer-internal underwriting
What they do
Manual review on bank statements and tradelines, 12-day cycles.
Gap
The status quo Pulse compresses. Two weeks becomes two minutes.

07 · Key risks

What could break the thesis

Operator-grade pre-mortem. Surfaced because the buyers and partners worth talking to will surface them anyway.

Risk · 01

Issuers are slow to adopt third-party underwriting inputs.

Mitigation

Position as feature-augmentation in the existing underwriting flow, not replacement. The issuer keeps the decision. Pulse expands the input set.

Risk · 02

Long-tail supplier data is fragmented and inconsistent.

Mitigation

The fragmentation is exactly what makes the integration work expensive enough to deter the next entrant. The cost compounds for the second mover, not the first.

Risk · 03

Default rates on AR-signal underwriting are unproven at scale.

Mitigation

Run a parallel underwriting program with an issuer partner first. Earn credit-loss credibility before committing to any volume guarantee.

08 · Proof of motion

What I've already shipped on this thesis

The artifacts that turn this from an essay into something with traction. Published work, working-group seats, operator scars.

09 · Questions partners ask

The next three follow-ups

Pre-empted because the buyers and partners worth talking to will surface them anyway.

Why won't Plaid or Codat just add an underwriting score?

They might. Both sell the data feed today and could add scoring on top. The bet here is that an underwriting score that issuers will actually underwrite to requires more than a logistic regression on bank-statement data. It requires the AR/AP signal stack and the operator credibility to defend it under loss review. The data feed is necessary but not sufficient.

Why don't issuers just build this themselves?

Issuers want the answer, not the build. The Visa and Mastercard commercial-card programs are publicly committing to expand acceptance into the long tail. They do not want to expand their underwriting team to do it. A scored input that plugs into their existing flow is the path of least friction.

Status

Pulse Underwriting is a published essay, not a stealth company. I am running Finexio. The thesis is here so the right operator or investor can find it and we can talk.

Of the eight ventures I've published, two are in discovery and I expect to operate one of them after Finexio. The rest, including this one, are pattern recognition I want in the open. If you read this and want to start it yourself, that is the outcome I'm hoping for.

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