Credit union merger factors

A plain, complete description of the model behind the Merger Finder, the Merger Screener, and the Combined-CU preview. It names no credit union. As of 2025Q4.

What this is - and what it is not

A merger is usually a strategic choice, not a failure. In our own data, 77% of the 1066 completed credit-union mergers since 2019 were voluntary “expanded services,” not distress. So these tools are about finding a good merger partner, not a death watch.

They score how closely a credit union’s finances resemble the historical profile of a credit union that acquired another, and (separately) the profile of one that completed a merger. It is a propensity (a ranking against a historical pattern), not a prediction that any particular credit union will merge, and not a statement about its safety, soundness, or regulatory standing. About 3.5% of credit unions merge in a given year, so even a top-ranked credit union most likely will not.

Data

Two public sources, both used exactly as reported: the NCUA 5300 Call Report (each credit union’s quarterly financials) and the NCUA Merger Activity & Insurance Report (every completed merger, with the continuing and merging credit unions). Nothing is estimated or blended; every input is a regulator-reported number.

The model (transparent by design - no black box)

A logistic-regression scorecard on the features below, each read from a credit union’s most recent complete fiscal year. We trim features at the 1st/99th percentile (so one outlier can’t distort the scale) and standardize them. Each feature’s effect is a fixed, disclosed weight; a credit union’s score is just the sum of its features’ contributions, which is why every result on the Finder shows its own factor breakdown.

In plain terms: acquirers tend to be larger, have prior acquisitions, and run efficiently; succession candidates tend to be smaller, slower-growing, and thinner on earnings. Direction and relative weight are shown; the exact coefficients live in the code (cu411/mergers.py).

How we validated it (before we showed any score)

We trained the model only on 2019–2023 mergers and tested it out-of-time on mergers it had never seen (2024–2025). It is a ranking tool, so we measure ranking quality, not false precision:

“Top-decile lift 3.6×” means the 10% of credit unions the model rated highest went on to do roughly 3.6 times as many deals as an average group - a useful ranking, never a certainty about any one credit union. We show a fit band (weak / moderate / strong), never a per-credit-union percentage.

The Merger Screener - your factors, your weights

The cross-credit-union Merger Screener is a tool you drive: pick any of the features above, choose whether you want them ranked higher or lower, set a weight, and every credit union is ranked by how its public figures fit your criteria. Each factor is scored on its population percentile, and the “match” is the weighted average of those percentiles - true facts sorted by your recipe, exported with the recipe baked in. The two “Historical pattern” presets simply fill the weights from the disclosed model coefficients above; the output is described as “meets N of M factors more common among credit unions that acquired / completed a merger, 2019–2025” - a past-tense description of a historical pattern, never a label on a credit union’s future.

The Combined-CU preview - arithmetic, not a forecast

The Combined-CU preview adds two credit unions’ latest annual call reports and recomputes the ratio suite (net worth ratio, loan-to-share, delinquency, return on assets, operating expense) from the summed numerators and denominators, alongside the combined asset band and rank. It is a straight combination of two public call reports; actual merger accounting differs (fair-value marks, purchase accounting, and integration costs we cannot see), so it is an illustration, never a projection.

Bank targets - a separate, rules-based screen

The Bank targets tab is different, and we flag it plainly. There is no public, labeled set of credit-union-buys-bank deals to train and validate on (those ~20-a-year transactions are compiled by hand from press coverage, not a downloadable file), so that ranking is not a backtested model like the two above. It is a disclosed, rules-based attractiveness score: a fixed weighting of deposit franchise (30%), size fit (20%), capital (20%), credit quality (15%), and profitability (15%), each scored from public FDIC Call Report data for community banks (the relative factors as a percentile among community banks; size fit as an absolute target range). It is a screening heuristic to focus a buyer’s homework - never a prediction, and never a claim that a bank is for sale.

Fairness & privacy guardrails

• We never attach a “succession candidate” label to another credit union. The cross-credit-union product is the user-driven Merger Screener (true facts sorted by criteria you choose), not a platform verdict. A platform-branded, named-credit-union succession label remains held behind a legal review and is off by default.
• Mission-designated credit unions (NCUA low-income or CDFI-certified, small-by-design in service of their mission) are set aside from the merger-pattern screen by default (you can include them, but they are always tagged for context).
• Your own credit union’s read is yours. A member can see their own credit union’s acquirer and merger-fit self-read after a one-time acknowledgement, and can flag any figure - an open flag suppresses the read while we verify it.
• Nothing about a named credit union’s merger likelihood is public. The public pages show only completed mergers (the merger tracker) and a factual “merged into X” note on a merged credit union’s profile. The screening tools are members-only and gated.
• We refresh the model each year as new Call Report and merger data publish.