Model Documentation for structured governance and audit readiness
A reliable model risk management framework requires consistent, complete and structured model documentation.
Yields Model Risk Management software includes a document generator that standardizes the development of documentation, validation reports and monitoring reports throughout the model lifecycle.
Why is good model documentation important
Without structured documentation, organizations cannot ensure that model information is complete, consistent and aligned with governance requirements. This typically results in:
As a result, documentation becomes a manual and time-consuming exercise, requiring significant effort to compile, update and review reports.
A structured and automated document generator
Yields Model Risk Management Software includes a document generator that allows you to generate documents directly in the platform, or upload your own finalized documents. The choice is yours.
Generate documents directly in the platform using structured model data
Define your own templates in Word with dynamic placeholders
Automatically populate reports with data from models, metadata, and descriptions
Upload your own finalized documents if you prefer working offline
Import data from Excel or CSV via API, SDK, or CLI
Store, tag, and manage everything in one central repository
How it works
Capture model information
Update model information manually or perform bulk updates via API, SDKs/CLIs or file uploads. Validators can push quantitative evidence directly from Python or R environments using the Yields SDK.
Define documentation templates
Upload and manage templates for Development, Validation and Monitoring documentation. Define the chapter structure and specify what content should appear in each section using placeholders.
Generate documentation automatically
Placeholders populate the document with structured information captured in the platform, ensuring consistency and alignment with internal standards.
Manage documents centrally
Upload and organize documents using tags, comments and descriptions. Maintain a central repository for all lifecycle documentation.
Retrieve and download documentation
Search documents by tag and model properties. Download multiple documents in bulk in ZIP format for audit or regulatory requests.
Designed for regulated environments
Yields is built specifically for Model Risk Management in highly regulated industries.
The document generation and document management functionality support structured governance, audit readiness and alignment with internal policies and regulatory frameworks.
Transform your model documentation into a structured governance process
FAQ
Model documentation refers to the structured documentation of a model throughout its lifecycle.
It typically includes information about model development, methodology, assumptions, data, validation, monitoring and governance decisions.Model Documentation ensures that model information is complete, consistent and aligned with internal governance requirements and regulatory expectations.
It enables organizations to demonstrate proper model development, validation and monitoring.
Yields Model Risk Management Software supports the generation of standardized documentation based on predefined templates.
Organizations can generate, for example:
Development documentation
Validation reports
Monitoring reports
Templates are managed within the platform and can be defined in Word or LaTeX format. Using placeholders, documents are automatically populated with structured information captured in the platform.
The document generator automatically populates documentation templates using structured model information stored in the platform.
This eliminates manual copy-paste, reduces repetitive work and ensures that documentation can be generated and updated significantly faster.
By centralizing model information and quantitative evidence, documentation becomes a structured and efficient process instead of a time-consuming manual exercise.
Yes. Yields Model Risk Management Software supports integration with existing systems through a user-friendly API specified using OpenAPI.
Model information and quantitative evidence can be uploaded via API, SDKs/CLIs, or imported from Excel and CSV files. Validators can push results directly from Python or R environments using the Yields SDK.
This allows organizations to integrate documentation processes into their existing workflows while maintaining structured governance within the platform.