For credit unionsThe member file is exactly what staff .
Social Security numbers, account and routing numbers, loan records: this is the segment RedactWall serves deepest. It covers data leaving through AI tools and email, and reports the sensitive files sitting in your cloud drives. Your examiner gets evidence they can check themselves.
Where AI risk enters a credit union
Four situations, and what happens next.
- A member-services rep pastes an account note into a chat assistant → checked before it leaves, and the decision is on the record.
- Loan-ops automation calls a model API → the request and the answer are both checked against the policy your risk owner approved.
- Someone emails a member list to a personal account → refused before the message is accepted for delivery.
- Member files sit in a shared drive nobody has reviewed → you get a report of what is in them, without the contents leaving.
What your examiner ends up holding
- A sealed record for the period they asked about, and nothing outside it.
- Who reviewed each held incident, what they decided, and when. A reviewer signs in again before deciding.
- The policy that was in force during that period, and the risk owner who approved it.
- A check your own staff run to confirm the record is intact, on your own systems. How that works →
Detection built for what you hold
MEMBER RECORDS
Member and loan identifiers, mortgage and consumer-credit numbers, and the identity documents onboarding captures.
PAYMENTS
Routing numbers, IBAN and SWIFT codes, and the card data that PCI DSS forbids storing at all. Each number is checked for validity, not just shape.
YOUR OWN RECORDS
Matching against your actual member records, from a copy that cannot be read back into the original data.
Stop the leak. Not the work.
Pilots start with the surface you care about most.
- One setting change per application
- Your members’ data is never stored
- Evidence your own team can check