ValidMind

The PRA’s Supervisory Statement SS1/23 sets clear expectations for how firms manage model risk, including models that leverage AI and machine learning. But translating regulatory principles into practical, operational workflows remains a challenge for many institutions.

Join us for a focused discussion on how banks can operationalize SS1/23 across AI, GenAI, and traditional model portfolios, without slowing innovation.

This session will explore how to align governance frameworks, validation processes, documentation standards, and inventory controls to meet supervisory expectations while enabling responsible AI adoption.

## What You’ll Learn

✔ Translating SS1/23 from policy into operational AI governance

✔ Embedding risk classification, accountability, and lifecycle controls into AI systems

✔ Best practices for independent validation and documentation

✔ How to generate audit-ready evidence without manual overhead

✔ Strategies for accelerating AI innovation while maintaining regulatory confidence

## Who Should Attend

*   Heads of Model Risk Management
*   AI Governance Leaders
*   Validation & Independent Review Teams
*   Risk & Compliance Executives
*   Chief Risk Officers
*   Internal Audit Leaders

## Why This Matters Now

Regulators are increasing scrutiny of AI-enabled models, governance accountability, and independent oversight. Institutions that operationalize SS1/23 effectively will not only reduce supervisory risk, they will create a foundation for scalable AI adoption with measurable ROI.

## About ValidMind

ValidMind is the enterprise AI governance platform built on decades of Model Risk Management rigor. We help regulated institutions govern, validate, and monitor AI, GenAI, and traditional models at scale, providing centralized oversight, accelerating AI adoption, and delivering measurable ROI.
