Capabilities · Credit Union Consulting
A decision-intelligence consulting practice for credit unions. We work on the problems your team brings us — from credit and fraud to member growth, data, and automation — built and governed on NexML where the work is productized, and delivered by an embedded pod where it isn't. All explainable, examiner-ready, and running on your own servers.
02 · The work we take on
The list isn't exhaustive — but in the first 30 minutes of a working session, a credit union's situation usually maps to one of these. Each is tagged with the capability that solves it.
Self-employed, thin-file, and near-prime members get turned away by generic scores that can't read their situation. You lose good loans, and the members, to a lender that looked closer.
NCUA and SR 11-7 don't scale down because you're smaller, but a full MRM function rarely pencils out. Every exam becomes a scramble to reconstruct evidence that should already exist.
Manual checks miss fabricated identities and document inconsistencies until the loss is booked. The patterns are there in the data — they just aren't being read in real time.
By the time an account is flagged, the window for a supportive, low-cost intervention has closed. Outreach is a reaction, not a plan — and losses that were predictable become realized.
Falling transaction frequency and balance drift signal attrition long before a member leaves. Without a model watching, retention spends land everywhere except where they'd change the outcome.
The signal you need for any model is spread across systems that don't talk to each other. Every project starts by rebuilding the same data plumbing before the real work can begin.
Document intake, verification, and routine member requests eat staff time and slow decisions. The repeatable parts could be automated — with a human still on every exception that matters.
The ambition is there; the staffing isn't. Hiring data engineers, modelers, and an AI leader is out of reach. The work stalls for want of a team to carry it — not for want of a plan.
03 · How we work
Mechanism 01
For decisions we've productized — credit, fraud, collections, churn — built, deployed, and governed on the NexML platform, running in your own environment. Usage-based: you pay for the decisions it scores in production, not a license.
Mechanism 02
For work that spans many decisions or is still being shaped — a senior data/AI lead plus delivery team inside your credit union, on a retainer. Composition is designed per engagement, and your people take on more as their capability grows.
04 · What we can build for a credit union
The full Innovatics capability set, translated for credit unions. Start with one decision on NexML and expand from there — the platform, the data beneath it, and the team to run it all connect.
Lending, fraud, collections, and churn models built, deployed, and monitored on one governed platform — trained on your own history, explained at decision time.
Documentation, lineage, explainability, and maker-checker approvals generated at decision time and assembled into examiner-ready binders — model risk management without a full MRM team.
Unify core, loan origination, cards, and digital-banking data into one governed warehouse — the foundation every model and report depends on, built once and reused.
Propensity, next-best-product, deposit and pricing optimization, and member lifetime value — the analytics that grow wallet share and fund the balance sheet.
Loan-document intake, verification, and routine member requests handled by supervised agents — with a person on every exception and a full trail behind every action.
Everything runs on your servers with no member-data egress — SSO, RBAC, SIEM, and KMS integrations aligned to how your security team already operates.
A dedicated data and AI pod that operates as part of your credit union, and a fractional AI officer for leadership — so you get the capability without standing up a department.
05 · FAQ
Five things we get asked early. The honest answers are here, so you can decide whether a working session is worth your time.
If the decision is clear and productized — credit, fraud, collections, churn — it's built and governed on NexML. If the scope spans many decisions or is still being shaped, an embedded pod fits. We settle this together in the first working session and tell you which we'd recommend.
The models, documentation, and data work run within your environment and are yours to operate. NexML itself is usage-based — you pay for the decisions it scores in production rather than a fixed license — so the platform stays supported while the outputs stay in your hands.
Yes. Documentation, lineage, explainability, and maker-checker approvals are generated at decision time and assemble into examiner-ready binders, aligned to NCUA model risk guidance and Federal Reserve SR 11-7 principles. It supports your compliance posture; it doesn't replace independent validation.
No. We can operate as an embedded pod or provide a fractional AI officer, building the models and owning monitoring and audit evidence while your own team takes on as much of the work as it wants over time.
Model work on NexML is usage-based, with the first model built in a pilot at no upfront cost. Data, automation, and embedded engagements are scoped as focused work. We size budget directly in the working session, once the problem and timeline are clear.
06 · Insights
Discover how AutoML and MLOps revolutionize financial services with scalable, compliant AI systems. Learn key strategies for effective implementation.
Read article
AI in credit unions helps predict delinquency, prevent fraud, and deliver personalized member services. See how credit unions use predictive analytics to stay competitive.
Read article![Will Your Credit Union Pass The Next NCUA Model Risk Exam? [2025 Guide]](https://cdn.sanity.io/images/ez9tvume/production/727533000a86c04049d6bd2e44a9294538462ae9-732x393.png)
NCUA’s 2025 model risk exams require real-time monitoring, model drift detection, and explainable AI. Learn how credit unions can use automated monitoring, AutoML, and continuous validation to pass exams, reduce loan losses, and improve compliance confidence
Read articleConsulting that ends with a governed model in production — not a slide deck.
08 · Ready when you are
A 30-minute working session with a senior team member who understands credit unions, your examiners, and the members you serve. We'll map your situation to the right capability — and prove the first model before you commit to anything.
Founded 2020 · Governed ML for regulated finance · Engagements across North America, Australia, and India · ISO 27001 certified
