Co‑authored by Gregory Haardt, Co‑Founder & CTO, Vectice, and Utkarsh Jain, Director of Product Management, ServiceNow.
Why This Matters Now
Risk teams and boards are sharpening their focus on AI governance. SR 11‑7 (U.S.), OSFI E‑23 (Canada), PRA SS 1/23 (UK) and the recently legislated EU AI Act all require complete, contemporaneous records of model development, review, and monitoring. GenAI initiatives and agent‑based model architectures have moved to the top of the project queue, prompting organizations to adapt their development processes. Without a scalable way to capture data provenance, parameters, and validation artifacts, MRM, governance, risk and compliance teams spend countless hours chasing evidence, stretching approval SLAs and inflating operational‑risk capital charges.
Key takeaway: Documentation and lineage elevate model governance from a checkbox exercise to a supervisory control explicitly required by SR 11‑7, OSFI E‑23, PRA SS 1/23 and the EU AI Act. Plus it reduces remediation costs, protects capital, and accelerates compliant time‑to‑production.
Documentation: The Foundational Control
In regulated sectors, the canonical record is often a Model Development Document (MDD) paired with a Model Validation Document (MVD) where a dedicated validation or assurance function exists. Outside banking, the same discipline applies even if job titles differ (e.g., AI Governance Lead, Risk & Controls Manager). A robust MDD should include:
A living, continuously updated MDD/MVD lets governance and risk teams challenge models, satisfy supervisors, and justify decisions to auditors and regulators.
Evidence Lineage: The Traceability Backbone
Documentation tells what was done; evidence lineage proves how, when, and by whom it happened:
- Data Lineage – Source‑to‑sink trace from raw feeds through ETL to model‑ready features, including schema versions and quality scores.
- Model Lineage – Immutable hash of each artifact (code, weights, prompts) stored in a registry and linked to the exact MDD/MVD.
- Decision Lineage – Inference logs tied to model version, input payload, and outcome for post‑hoc investigations or dispute resolution.
Graph‑based lineage lets MRM, governance and operational‑risk teams traverse from any production decision back to the originating dataset in seconds—crucial for regulatory findings, customer complaints, and root‑cause analysis.
Quantified Uplift
Institutions using Vectice to automate documentation with Vectice and lineage throughout the development lifecycle and within their CI/CD pipelines report:
- 60–90 % reduction in preparation time for MDDs/MVDs or equivalent governance packages
- >30 % faster review and approval cycles for MRM and governance functions, thanks to on‑demand evidence packs
- Fewer model freezes during supervisory exams or external audits because artifacts are traceable and reproducible
Automation converts documentation from an annual fire‑drill into a continuously updated control.
Documentation: Tablestakes for all Emerging AI Standards
Building on these operational gains, global frameworks—ISO 42001 (AI Management Systems) and the NIST AI RMF—have moved from “forward‑looking guidance” to table stakes requirements. Both mandate evidence traces and granular technical documentation. Organizations that operationalize lineage and documentation today align with these mandates out of the gate and avoid costly rework as regulators embed them into formal rules.
Next Steps
ServiceNow® Integrated Risk Management (IRM) centralizes control frameworks, issues and approvals. Through its new integration with Vectice, enterprises can:
- Auto‑populate MDD/MVD (or equivalent) templates with real‑time artifacts
- Map lineage evidence to SR 11‑7, E‑23, the EU AI Act, ISO 42001, or internal control frameworks, then push findings into IRM workflows
- Offer auditors and regulators a single governed workspace instead of ad‑hoc file shares
To explore a reference implementation—or to discuss compressing your AI‑governance cycle time—reach out to your ServiceNow account team or visit vectice.com/servicenow.
