Verified Governance

Discover AI Trust & Governance Center

Defensible architecture, transparent model risk controls, privacy-by-design data handling, and responsible AI governance engineered for regulated financial institutions.

Model Risk Management & Regulatory Alignment

Discover AI designs and documents machine learning models to strictly satisfy the three core pillars of the Federal Reserve’s Supervisory Guidance on Model Risk Management (SR 11-7) and OCC Bulletin 2011-12:

1. Conceptual Soundness

Every model is grounded in verified financial crime domain theory. We utilize interpretable tree structures with monotonic constraints to eliminate non-intuitive score anomalies.

2. Ongoing Monitoring

Automated telemetry tracks Population Stability Index (PSI) and Characteristic Selectivity Index (CSI) post-deployment to alert validators to concept drift.

3. Outcomes Analysis

Out-of-time backtesting and champion/challenger comparison ensure models perform reliably across changing economic conditions and seasonality.

Responsible AI & Investigator Primacy

Discover AI firmly rejects autonomous decision-making in high-stakes regulatory environments. Our core architecture enforces human oversight:

Decision Support, Not Autonomous Adjudication: Models prioritize cases and recommend draft narratives; certified human investigators make all final case determinations and regulatory filing decisions.
Evidence Grounding & Citation Auditing: Generated narrative drafts must cite verified primary records (transaction IDs, KYC docs). Any ungrounded assertion is flagged.
Immutable Audit Trails: Every recommendation, prompt version, investigator edit, and supervisor sign-off is logged in cryptographically verifiable audit trails.

Synthetic Data Standards & PII Protection

In compliance with Charter Section 2 (Principle 7), all product demonstrations, public exhibits, and sales sandbox environments utilize mathematically synthesized financial data generated by Discover AI Data Lab:

Zero Real-World PII: Names, account numbers, addresses, tax IDs, and corporate entities shown on this website and in demonstration sandboxes are entirely synthetic. Any resemblance to real persons or entities is purely coincidental.

Enterprise Security & Privacy Architecture

Discover AI is architected with enterprise-grade isolation, supporting hybrid and private VPC customer deployments:

Tenant Isolation

Strict database and compute separation ensures no cross-contamination between client tenants.

Least-Privilege Access (RBAC)

Granular permission controls enforce segregation of duties between primary analysts and QA supervisors.

Accessibility (WCAG 2.2 AA)

Our corporate website and web gateway are engineered to adhere to WCAG 2.2 Level AA accessibility standards.