Credit Unions
Member value, loan book health and social impact you can actually show.
Credit unions carry the reporting burden of a bank on a fraction of the resource. The ledger holds the truth but not the history, member value is asserted rather than measured, and the board pack is somebody's weekend. We make the book and the membership legible without adding headcount.
The numbers that matter here
What we'd connect here
Whatever it is and however it exposes itself — API, database, nightly file, or a spreadsheet somebody maintains by hand. We only ever need read access, with personal data excluded.
What we do about it
Where it hurts
- Core banking system holds balances, not the history behind them
- Board pack assembled manually from several exports
- Member value and social impact claimed but not evidenced
- Arrears trend impossible to see because only today's position is stored
What Acta builds
- Loan-book position rebuilt over time, so arrears and provisioning trend properly
- Member lifecycle view: joining, saving, borrowing, staying
- Social impact reporting built from the ledger rather than estimated
- A board pack that regenerates itself every month
What you get
A board pack that stands up to a regulator and a member AGM alike.
Live in months rather than years, from £5k a month, on your own Google environment — handed over to you, or run by us.
Inside a credit union engagement
A credit union carries the reporting expectations of a bank on a fraction of the resource. The core banking system holds today's balances but not the history behind them, the board pack is assembled by hand from several exports as somebody's weekend, and member value and social impact are asserted in the annual report rather than measured. Arrears look like a single current figure because only the current position is stored, so the trend that would let you act early simply is not there.
We take the ledger events into your own BigQuery and rebuild the loan-book position over time, so arrears and provisioning trend properly and a developing problem is visible while it is still small. Alongside that we build a member lifecycle view — joining, saving, borrowing, staying — and social impact reporting drawn from the ledger itself rather than estimated. None of it needs a new hire or a platform migration; we work in your own environment and read from the systems you already run.
What the board gets is a pack that regenerates itself every month and stands up to a regulator and a member AGM alike, because every number traces back to the underlying data. Loan-book value, arrears, member growth, savings per member and the cost-income ratio all come from one definition, so the conversation moves from assembling the numbers to deciding what to do about them.
Common questions
Can a credit union afford this without adding headcount?
Yes — the point is to get bank-grade reporting without bank-grade resource. Solving one area is £60k a year at £5k a month, in your own Google environment, with no new hire to make or manage. The board pack that used to be someone's weekend regenerates itself.
Our core banking system holds balances but not history — can you still trend arrears?
Yes. We rebuild the loan-book position over time from the ledger events, so arrears and provisioning trend properly instead of showing only today's figure. That history is what lets you see a problem developing rather than reporting it after it has arrived.
Can you evidence member value and social impact for the AGM?
We build social impact and member-value reporting from the ledger itself rather than from estimates, alongside a member lifecycle view of joining, saving, borrowing and staying. It stands up to a regulator and to a member AGM alike because every number traces back to the data.
Which credit unions systems do you connect to?
Whatever you already run — it makes no difference whether a system exposes an API, a database view, a nightly file or a spreadsheet somebody maintains by hand. In credit unions that usually means: Core member and loan system; BACS and Faster Payments files; Loan decisioning; Member registers still kept in Excel; In-house SQL database. We only ever need read access with personal data excluded, and the layer is built in your own Google environment rather than ours.
Other sectors
Bring one decision your data should be helping you make.
30 minutes, no deck. We'll tell you on the call whether we're the right partner, and exactly what we'd ship in the first 30 days.