Correction, 2 September 2026. This post argued that balance-sheet divergence precedes a software purchase closely enough to rank buying intent. In September 2026 we tested that claim for the first time, against publicly announced vendor adoptions, and it did not hold. The scorecard built on the reasoning below ranked announced adopters at AUC 0.509 and 0.543 across two annual cohorts — the coin-flip band — where ranking the same institutions by asset size alone scored 0.677 and 0.665, and where not one of the 25 highest-ranked institutions announced an adoption in the year that followed. The test observes announcements rather than purchases, so a zero may be a quiet buyer and the measured precision is a lower bound; that qualifies the result, it does not rescue it. The post is left standing rather than removed, because the reasoning is worth reading and because a claim published in public should be corrected in public. What replaced it does not infer intent from financials at all: it records observed relationships — which institution runs which platform, since when, and when a contract can be shown to come up.
By the time a credit union publishes an RFP, the useful part of the sales cycle is over. A committee has already agreed there is a problem, already talked to two or three vendors while framing it, and already written requirements that reflect those conversations. The vendors who arrive at the RFP are competing to be the cheapest version of a solution someone else scoped.
The interesting question is what the institution looked like six to twelve months earlier, when the problem became undeniable inside the building but nothing had been published yet. That period leaves marks on the quarterly financials.
The general shape
Software gets bought when a capability stops keeping up with the volume flowing through it. On a balance sheet that appears as a divergence: one quantity growing materially faster than the thing that has to service it.
That is the whole idea. Not "this institution is big, so it buys things" — that is a list sorted by assets, which every competitor already has. The signal is a rate of change out of line with its own history and its own peers.
Five categories, five distinct divergences.
Lending and loan origination
A loan book growing considerably faster than the institution's overall balance sheet means origination volume is climbing against a fixed underwriting capacity. Manual processes that were adequate at the old run rate stop being adequate, and the symptom inside the building is turnaround time, not cost. Growth concentrated in a single loan category compounds it, because a specialized workflow that was an exception becomes the main line of business.
Collections, fraud and risk
Delinquency rising faster than the loan book is the classic tell. Collections capacity is staffed against a historical delinquency rate; when the rate moves and the staffing does not, something has to give. Charge-offs climbing alongside it shortens the timeline, because the cost of not acting becomes a number the board sees.
The important nuance: this signal fires before the losses are large. An institution already in serious credit trouble has bigger problems than software, and is a worse prospect, not a better one.
Digital banking and engagement
Member growth diverging from asset growth is the signal here, in either direction. Members growing faster than assets means a widening base of thinner relationships — the digital-onboarding problem. Assets growing while membership shrinks means a concentrating base of aging relationships — the retention problem. Both get solved with the same category of product and both are invisible if you look at either number alone.
Treasury and liquidity
Covered in detail in the loan-to-share piece: a balance sheet crossing into the loaned-up band, with cash thinning or deposits shrinking, has just acquired a funding problem it did not previously have to manage actively. That is when treasury workstations, liquidity forecasting and participation platforms stop being nice-to-have.
Core and reg-tech
This one is threshold-driven rather than trend-driven. Certain asset levels change what an institution is required to report and how it is supervised, and approaching one of those lines from below — or having just crossed it — creates a compliance and reporting workload that arrives on a schedule. Growth rate matters here mainly because it tells you when the line gets crossed.
Why peer-relative is not optional
The single most common failure in scoring buying intent is comparing institutions to each other rather than to their peers.
A $90M credit union and a $4B credit union are not in the same business. Their expense ratios, growth rates, delinquency levels and member behavior differ structurally, not because one is performing better. Rank them on the same absolute scale and the score becomes a proxy for size — which is to say, a list you could have produced with a spreadsheet sort and no model.
Scoring against peer-group and asset-tier medians fixes this. The question stops being "is this ratio high?" and becomes "is this ratio high for an institution like this one?" — which is the question a salesperson is actually asking. It also surfaces the mid-size institutions that absolute ranking buries: a $300M credit union whose loan growth is in the 95th percentile of its tier is a far better call than a $5B institution sitting at its own tier's median.
The "why now" is the deliverable
A propensity score of 84 is not usable on a call. What is usable is the sentence underneath it: loans up 14% year over year against 4% asset growth, delinquency up 40 basis points, both in the top decile of the peer group.
That sentence does three things a score cannot. It tells the rep what to open with. It tells them what to ask about, so the first call is a diagnosis rather than a pitch. And it lets them discard the account quickly if the reason does not hold up — which is worth as much as a good lead, because the expensive failure in enterprise sales is not the call you skip, it is the quarter you spend on an account that was never going to move.
Any intent product that gives you a number without the reason is asking you to trust it on faith, and it will be wrong often enough that faith is the wrong posture.
What this cannot see
Quarterly financials do not record contract expiry dates, and a core conversion is governed more by when the current agreement ends than by anything on the balance sheet. They do not record a new CIO's mandate, a board's strategic plan, or the fact that a peer institution's CEO recommended a vendor at a conference. They do not see budget.
What they do see is pressure — the accumulating operational strain that eventually makes someone raise the issue. Pressure is what a scoring model reads well, and it is a genuinely leading indicator. It is not a purchase order, and treating a score as one is how a sales team learns to distrust the whole tool.
Used as a ranked ordering of where to spend the quarter's attention, with the reason attached so a rep can qualify out fast, it is the difference between working a territory and working a list.
Scores described here are model estimates computed from the quarterly panel. They are not investment, credit or merger advice and not a recommendation about any institution. See the disclaimer and disclosures.