Model Validation Software for Heads of Model Validation | Yields
For Heads of Model Validation

Rigorous validation. At any scale.

The number of models and AI systems keeps growing. Your team stays the same size. Yields gives you the structure to validate consistently, independently, and with the evidence to back every conclusion.

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Category Leader in the Chartis 2025 RiskTech Quadrant for Model Validation.
Head of Model Validation at work
Model Validation Software for Heads of Model Validation | Yields
The validation challenge

More models. Same team. Higher expectations.

Validation teams are being asked to do more with the same capacity, across a model landscape that is growing faster and becoming harder to validate.

Without Yields

  • Every validation starts from scratch, with no shared structure or templates.
  • AI and machine learning models validated differently, or flagged as out of scope.
  • Findings and assumptions scattered across documents, emails, and shared drives.
  • Reports assembled manually before every review cycle.

With Yields

  • Standardised validation workflows that scale across the full model portfolio.
  • One framework for traditional models and AI, with consistent rigour throughout.
  • Every finding, assumption, and limitation logged automatically as you work.
  • Validation reports generated from the work already done. No reconstruction.
The questions your team faces every cycle

Validation should answer questions. Not create them.

Do you have a consistent validation framework that applies to both traditional models and AI?
Can you validate more models without growing the team, or compromising independence?
Is every finding traceable to the validator, the test, and the date it was logged?
Can you produce a complete, regulator-ready validation report without starting from scratch?
Do you have a clear view of which models are pending validation and which are overdue?

With Yields, the structure is in place before the question arrives.

See it in action
How it works

Consistent validation across every model and AI system.

01

Structured workflows

Define your validation methodology once. Yields applies it consistently across every model, so every validation follows the same rigorous process regardless of who runs it.

02

Automated evidence capture

Findings, assumptions, limitations, and test results are logged as you work. Nothing needs to be reconstructed later. The audit trail builds itself.

03

Reports without the effort

Generate complete, structured validation reports directly from the work already captured. Ready for the model owner, the CRO, and the regulator.

Model validation team at work
Independence preserved. Capacity extended.

Validate AI the same way you validate everything else.

AI and machine learning models present new challenges for validation teams: harder to interpret, faster to change, and increasingly scrutinised by regulators. Yields brings AI into the same structured workflow as your traditional models, so independence and rigour are never compromised.

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How HSBC approaches model validation
We automated the calculation of quantitative metrics and the drafting of reports, freeing up senior validators to focus on high-level analysis and critical review. The end-to-end timeline for a validation has shrunk from 2 to 3 months down to just 3 to 4 weeks.
Philip Preuss
Global Head of Independent Model Review, Wholesale IRB, HSBC
HSBC
57%
reduction in validation effort
3-4w
down from 2 to 3 months
Automated report generation from raw validation data
Globally consistent report quality across all regions
Senior validators focused on analysis, not administration
Read the full story →

Validation that scales. Evidence that lasts.

See how Yields helps validation teams validate faster, cover AI, and stay regulator-ready without growing the team or cutting corners.

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