Superseded, September 2, 2026. The counts below are counts of a buying-propensity scorecard's own output. That scorecard was later tested against vendor adoptions that credit unions announced publicly, and it did not rank them. Take one credit union that announced an adoption and one that did not. In two yearly test groups, the score ranked the adopter higher only 51 and 54 times out of 100 pairs. That is a coin flip. Ranking by asset size alone got 68 and 67. The technical figures are on the disclosures page. Read the tables here as a record of how one score was spread in Q1 2026. They do not measure who was about to buy. This quarterly series is discontinued, and nothing replaces it in the same shape. What replaced the scorecard reports observed relationships: which credit union runs which platform, and since when. A register like that has no quarterly count to publish.
Scores by category
As of Q1 2026, the panel (our quarterly dataset of credit-union financials) held 2,405 credit unions above $50.0M in assets. The table counts how many scored 60 or higher in each category. The scorecard treated 60 as the point where a sales conversation was worth having this quarter. The test described above found no support for that. Digital banking and engagement had the most, with 69 institutions.
| Category | Scoring 60+ | Share of universe | Median propensity |
|---|---|---|---|
| Lending / loan origination | 27 | 1.1% | 11 |
| Collections, fraud and risk | 24 | 1.0% | 5 |
| Digital banking and engagement | 69 | 2.9% | 1 |
| Treasury and liquidity | 15 | 0.6% | 5 |
| Core and reg-tech | 32 | 1.3% | 0 |
Propensity was never a stated intention. The scorecard read each balance sheet for patterns it assumed come before a purchase in a category. One was a loan book growing faster than the staff who approve loans. Another was delinquency rising before collections capacity does. A third was assets nearing a size that changes what a credit union must report. The test found that these patterns did not rank the credit unions that went on to buy.
Top-scoring category per institution
For each credit union, the scorecard also picked the category where it scored highest. It offered that category as the best way in, a claim that rests on the same failed scores. This is how those top categories were spread:
| Entry category | Institutions | Share |
|---|---|---|
| Lending / loan origination | 850 | 35.3% |
| Collections, fraud and risk | 550 | 22.9% |
| Digital banking and engagement | 369 | 15.3% |
| Treasury and liquidity | 359 | 14.9% |
| Core and reg-tech | 273 | 11.4% |
Scores by asset tier
Budget and the propensity score are different things. A tier could score high and still buy nothing. The score looked for signs of need in the balance sheet, not for budget or buying authority.
| Asset tier | Institutions | Category scores 60+ | Median propensity |
|---|---|---|---|
| $50M-$100M | 577 | 16 | 0 |
| $100M-$500M | 1,070 | 41 | 2 |
| $500M-$1B | 284 | 40 | 7 |
| $1B-$10B | 450 | 66 | 5 |
| >$10B | 24 | 4 | 6 |
What changed this quarter
| Category | Last quarter | This quarter | Change |
|---|---|---|---|
| Lending / loan origination | 54 | 27 | -27 |
| Collections, fraud and risk | 61 | 24 | -37 |
| Digital banking and engagement | 66 | 69 | +3 |
| Treasury and liquidity | 25 | 15 | -10 |
| Core and reg-tech | 51 | 32 | -19 |
The scorecard was built on the idea that movement matters more than level for a sales team. Credit unions that newly crossed 60 were meant to be fresh leads. Because the scores did not rank buyers, these changes describe the score, not a shift in demand.
How the score is built
Each of the five categories had its own scorecard. Each read balance-sheet changes that were assumed to come before a purchase in that category. Scores were set against the median of each credit union's peer group, not against fixed values. So a $90M credit union and a $4B one were each compared with their own peers, not with each other. Each scored account carried a plain-English note naming the changes behind its score.
This post reports on the system as a whole. By design, it names no credit union.
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.