A leading North American property and casualty insurer chose Monitaur to transform AI governance from a bottleneck into a catalyst for innovation. Facing fragmented AI visibility, manual governance overhead, and scaling challenges, they implemented Monitaur to deliver AI governance at scale with impressive results that include:
One of North America's major property and casualty insurance providers viewed increasing regulatory pressure on AI as an opportunity to lead in AI governance, aiming to leverage AI for business growth.
The insurer faced several critical challenges that threatened to slow the pace of its AI innovation due to:
Without a centralized view of AI systems, the insurer found themselves unable to effectively track models across the enterprise or comprehensively demonstrate compliance to regulators. Their AI models were scattered across multiple disconnected systems throughout the organization, which made it virtually impossible to maintain proper accountability or provide the comprehensive documentation required for regulatory oversight and internal governance processes.
Monitaur created a single, unified source of truth for all AI initiatives across the organization, providing complete transparency and visibility across the entire AI landscape. This comprehensive approach achieved several critical outcomes:
“Monitaur helped to operationalize our AI Governance goals and objectives. Their software and expertise enhanced our capabilities to steer a consistent and thoughtful approach to model governance that meets the needs of internal and external stakeholders.” ~Associate General Council
Manual governance processes created significant overhead for the insurer's AI teams, consuming valuable time and resources that could have been spent on innovation. Before implementing Monitaur, every single model change—no matter how minor—required data scientists to manually re-evidence controls. This meant repeatedly gathering documentation, validating compliance requirements, and updating governance records for each iteration of a model.
This labor-intensive approach pulled talented data scientists away from their core work of developing and refining AI models. Instead of focusing on innovation that could drive business value, they were bogged down in repetitive compliance tasks. The manual process not only consumed valuable resources but also created delays in model deployment, slowing the pace of AI adoption across the organization.
Additionally, the manual approach made it difficult for governance teams to maintain visibility into compliance status. They had to rely on periodic updates and manual reports, making it challenging to quickly identify compliance gaps or respond to audit requests. This created risk and uncertainty around the organization's AI governance posture.
Monitaur transformed this process by introducing automation throughout the model lifecycle. The platform reduced the governance burden in three key ways:
This automation transformed the workflow. Data scientists were freed from repetitive compliance tasks to focus on innovation and model development. Hours or days of manual effort now happened automatically, accelerating AI development.
Governance teams gained real-time visibility into compliance status across all AI initiatives, enabling quick identification of gaps and confident responses to audit requests. Automated documentation provided audit-ready evidence, reducing governance overhead while improving oversight comprehensiveness.
The insurer maintained rigorous governance standards while accelerating AI innovation—proving compliance and speed can coexist with the right automation.
The insurer faced overwhelming review volumes and frequently changing models that threatened to slow AI innovation. After establishing an AI governance program, Monitaur helped them accelerate governance using automation across the entire model lifecycle including critical functions: pre-deployment validations, continuous monitoring, decision logging, model version retention, and objective bias assessments.
This delivered impressive results—44 models connected across production and pre-production environments, processing over 9 billion transactions. The implementation created greater transparency within the data science community, giving teams a comprehensive understanding of model performance, business value, and organizational impact. The solution also supports an extensive inventory of over 180 projects and 4,400 implemented controls, demonstrating governance at enterprise scale.
Using Monitaur's automation capabilities, the insurer built a scalable foundation for responsible AI that meets regulatory requirements while accelerating innovation. They created a centralized repository of AI projects and implemented standardized controls that ensure compliance with both industry regulations and internal policies, positioning themselves as leaders in responsible AI adoption.
“Using Monitaur Govern has created broader transparency within our larger Data Science community. Through the implementation process, we have developed a broad understanding of model performance, including value and business impact company-wide.” ~AI Capabilities Leader for Claims IT
By partnering with Monitaur, the insurer transformed three critical challenges that threatened its AI innovation. They shifted from fragmented AI visibility to centralized transparency, eliminated manual governance overhead through automation, and scaled governance across the enterprise. The results:
To learn more about how your organization can achieve similar results, contact us.
