Use Case

Model Inventory for complete oversight and systematic risk identification

A reliable Model Risk Management framework starts with one essential capability: a complete, accurate, and structured model inventory or model catalogue.

Yields provides a centralized, configurable Model Inventory solution that gives you full visibility across all models, AI systems, and analytical tools throughout their lifecycle.

Model inventory Yields

Why is a model inventory important?

Without a systematic, centralized inventory, organizations cannot ensure that every model is properly governed and managed, leading to regulatory exposure and potential financial loss. In the wake of regulations like SR 11-7, SS1/23, and the EU AI Act, an undocumented model is a regulatory liability.

Models tracked in spreadsheets across departments
Inconsistent metadata and missing documentation
No clear ownership or accountability
Manual tiering and risk classification
Limited audit trail of changes
No clear overview of findings and remediation status

As model complexity increases and regulatory scrutiny intensifies, these gaps create operational risk and compliance exposure.

A centralized, intelligent model inventory

Yields provides a dedicated model inventory that serves as a single source of truth for all models and AI use cases across the organization.

Capture all model metadata in a structured way

Define mandatory fields and governance controls

Assign model owners, validators, and stakeholders

Assign model owners, validators, and stakeholders

Track findings, recommendations, and action plans

Maintain a complete audit trail of all changes

Model inventory with Yields Model Risk Management software

How It works

Yields provides a structured way to govern every model across its lifecycle. You can centralise and organise:

Structured model registration

Register models using configurable templates aligned with your MRM framework. Capture metadata such as purpose, methodology, risk tier, dependencies, limitations, and production details.

Role-based governance

Assign stakeholders including model owners, developers, validators, and approvers. Access rights are fully configurable and aligned with your internal governance model.

Automated risk tiering

Use configurable questionnaires or scoring logic to assign risk tiers consistently. Reassess tiers at any point in the lifecycle with full versioning and auditability.

Integrated workflow

Trigger validation, monitoring, documentation, and remediation processes directly from the inventory. The model inventory becomes the starting point of every lifecycle event.

Complete audit trail

Every update, field change, and tier reassessment is logged automatically. Bulk uploads and API integrations are fully supported.

Designed for Regulated Environments

Yields is built specifically for Model Risk Management in highly regulated industries. Our Model Inventory solution supports compliance with frameworks such as SR 11-7, SS1/23, EU AI Act, Internal MRM policies and plenty more.

Model Risk management audit ready

Transform your model inventory into a dynamic governance engine.

FAQ

What is a model inventory?

A comprehensive and accurate model inventory is the foundational requirement for any effective Model Risk Management (MRM) program. It provides a single source of truth, establishing clear scope, ownership, and criticality for every model within an organization.

Why is a centralized model inventory important?

Without a centralized inventory:
- Models are tracked in spreadsheets across departments
- Ownership is unclear
- Risk tiers are inconsistent
- Documentation is incomplete
- Regulatory reporting becomes manual and time-consuming

A structured inventory creates transparency, accountability, and audit readiness.

How does Yields structure model metadata?

Yields provides configurable templates that allow you to define:

Mandatory metadata fields
Risk tier logic
Stakeholder roles
Model dependencies
Documentation requirements

All changes are logged with full version control and audit traceability.

Can the Yields model inventory support both traditional models and AI systems?

Yes. The inventory is model-agnostic and supports:
- Statistical models
- Machine learning models
- AI systems
- User-developed tools
- Third-party models

Different templates can be configured per model type.