Weeks spent manually tuning models, complex handovers between data science and engineering teams are key reasons why models fail audits that credit unions face today.
No—hybrid/on-prem deployment ensures data remains on your servers/VPC. You maintain complete control over your data and intellectual property while meeting credit union compliance AI requirements.
Yes—model cards, lineage tracking, approval workflows, and audit logs export to PDF/HTML format for regulatory review, fully compliant with NCUA compliance tools standards and audit-ready AI requirements.
Yes—local explanations generate compliant reason codes for regulatory requirements and customer transparency through credit risk AutoML credit unions.
Built-in diagnostics with configurable thresholds, automated alerts, and mitigation workflows to ensure responsible AI deployment as part of our comprehensive AI risk management approach.
Yes—register, monitor, and document your existing models alongside new NexML models in a unified model governance software US credit unions can rely on.
Yes—keep your existing data science stack while we add governance, deployment capabilities, and production monitoring through our MLOps for financial institutions platform.
