Vendor relationships4 min readAs of Q1 2026

Vendor demand across the credit-union system, Q1 2026

Superseded. These are counts of a buying-propensity scorecard that was later tested against announced vendor adoptions and did not rank them.

Published · Computed from the quarterly panel by the CUSignals pipeline and reviewed before publication.

Superseded, 2 September 2026. The counts below are counts of a buying-propensity scorecard's own output, and that scorecard was afterwards tested against publicly announced vendor adoptions and did not rank them — AUC 0.509 and 0.543 across two annual cohorts, against 0.677 and 0.665 for ranking by asset size alone. Read the tables here as a description of how one score was distributed in Q1 2026, not as a measure of who was about to buy. This quarterly series is discontinued. Nothing replaces it in the same shape, because what replaced the scorecard reports observed relationships — which institution runs which platform, since when — and a register does not have a quarterly count to publish.

Demand by category

Across the 2,405 credit unions above $50.0M in assets, the panel as of Q1 2026 scores this many at or above 60 — the threshold at which a category is worth a sales conversation this quarter rather than next year. Digital banking and engagement leads, with 69 institutions.

CategoryScoring 60+Share of universeMedian propensity
Lending / loan origination271.1%11
Collections, fraud and risk241.0%5
Digital banking and engagement692.9%1
Treasury and liquidity150.6%5
Core and reg-tech321.3%0

Propensity is not a stated intention. It is the degree to which an institution's balance sheet has moved into the shape that precedes a purchase in that category — a loan book growing faster than the staff that underwrites it, delinquency turning before collections capacity does, an asset base approaching a threshold that changes what the institution is required to report.

The best entry point per institution

Where one category is materially hotter than the rest for a given institution, that is the door to knock on. Across the universe, the hottest category breaks down:

Entry categoryInstitutionsShare
Lending / loan origination85035.3%
Collections, fraud and risk55022.9%
Digital banking and engagement36915.3%
Treasury and liquidity35914.9%
Core and reg-tech27311.4%

Demand by asset tier

Budget and buying propensity are different things, and the tier table is where they separate — a tier can score high and still buy nothing, because the score reads the balance sheet's need rather than its purchasing authority.

Asset tierInstitutionsCategory scores 60+Median propensity
$50M-$100M577160
$100M-$500M1,070412
$500M-$1B284407
$1B-$10B450665
>$10B2446

What changed this quarter

CategoryLast quarterThis quarterChange
Lending / loan origination5427-27
Collections, fraud and risk6124-37
Digital banking and engagement6669+3
Treasury and liquidity2515-10
Core and reg-tech5132-19

The movement matters more than the level for a sales team. A static list is worked down and exhausted inside a quarter; the institutions that newly crossed the threshold are the ones nobody has called yet.

How the score is built

Each of the five categories has its own scorecard reading the balance-sheet dynamics that precede a purchase in that category, scaled against peer-group medians rather than against absolute values — a $90M institution and a $4B one are compared to their own peers, not to each other. Every scored account carries a plain-English "why now" naming the specific movements that produced it.

This post reports the system. It names no institution, by design — the counts and distributions here are the free half, and the ranked, named, exportable list underneath them is what a subscription opens.

Caveats

Every figure above is a model estimate computed from the quarterly panel as of the quarter named at the top of this post. Scores are not investment, credit or merger advice, and nothing here is a recommendation about any institution. The scorecards, their published weights and their known limitations are set out in the disclosures.

See this in your own territory

Which institutions run which platforms, since when, and when a contract plausibly comes up — plus the test that found financials cannot predict a purchase. The ranked, named list behind this analysis — with the reason each institution scored where it did — is what a subscription opens. See the pricing ladder, or email admin@infinidatum.net with a question about this post.

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Figures in this post are model estimates computed from the quarterly panel as of the date shown. They are not investment, credit or merger advice and not a recommendation about any institution. See the disclaimer and disclosures. You may quote and cite this post with attribution and a link — see content use.