Artificial intelligence and model governance built for insurance
The latest artificial intelligence models add to the complexity of your existing modeling systems. From GLM to LLM, when model governance is done correctly as part of the full model lifecycle, teams see a higher achievement of business objectives, organizational alignment, and acceleration of modeling projects.
Governance is also the key to the quality and performance of modeling systems. Adapt quickly to both current and ever-changing industry and regulatory requirements that apply to the entire modeling system, including statistical, machine learning, and generative AI models.
"Where AI governance frameworks are implemented, AI governance has resulted in more successful AI initiatives, improved customer experience and increased revenue"
- Gartner Peer Community, AI Governance Frameworks for Responsible AI
Quality, performance, and risk management for complex modeling systems
Model filings, market conduct, NAIC, ORSA, ASOP, 56 DOI’s, and insurance jurisdictions - We get you!
Regulatory transparency
The simple realization is that many companies are not prepared to adhere to the changing regulatory requirement landscape at global or industry levels. In the US, the recent bulletin from NAIC and the technical requirements from NIST highlight the complexities of compliance.
AI model quality and business outcomes
80% of AI projects do not achieve business objectives (McKinsey, 2023). This shatters the myth that models must be fully developed before employing governance strategies. The foundation models that you see today are evolving. Models that check other models also need to be governed. How are you thinking about the entire AI system?
Model governance is not isolated to regulation. When done correctly, robust governance enables higher achievement of business objectives, organizational alignment, and acceleration of modeling projects.
Industry experts agree: Insurers need to evolve their practices to achieve success with AI
Software that operationalizes AI governance
Monitaur software establishes your risk framework and control library according to best practices in model risk management. Model development teams achieve greater success while also aligning with standards and regulations.
The policies and integrations embed in your developer lifecycle and give all stakeholders direct visibility and oversight across AI projects. Our risk and controls policies already deliver coverage and mapping to NIST, SB-169, and the most recent NAIC model bulletin.
The Monitaur “policy to proof” roadmap for AI governance frameworks
Uniting every stage of your AI and model governance journey with our software. Turn the concepts in AI governance frameworks into actionable governance practices that your company can roll out at scale.
DEMO: Good AI needs great governance
To succeed with AI, model governance and model risk management take on a new urgency. Monitaur was created to solve this problem. And we have the most comprehensive and effective AI and model governance solution available.
Scalable human oversight across high-risk models
Take the steps necessary to govern the fair, safe, and trusted models your business needs.
Continuously validate model performance
Leverage Monitaur's libraries and API's to connect to your models and model infrastructure and gain automation of controls and continuous objective validations.
Watch the Demo
Customers trust Monitaur's software and expertise to simplify governance
- Policy setting -> Proof in less than 100 days
- Faster sales & regulatory cycles
- Improved data science alignment & workflows through automation
Model systems in insurance are prevalent, but with increasing and competing demand among data products, industry regulations, and compliances, you need automated help to provide evidence of governance for your AI models.
Speed and efficiency matter when your product and customers are at stake. See how CAPE Analytics goes beyond good intentions for governance with Monitaur.
The latest research takes note
Hype Cycle for Data and Analytics Governance, 2024*
Gartner, June 18, 2024 - Discover how governance can drive innovation in your data and analytics strategy. Gartner customers can explore specific research on AI governance, addressing key challenges and offering best-practice recommendations.
Emerging Tech: TechScapes for Early-Stage Startups in GenAI TRiSM*
Gartner, October 7, 2024 - GenAI deployment and adoption are accelerating and introducing new security and privacy risks that GenAI trust, risk and security management startups are addressing. This research examines solutions product leaders can use to act on early trends and capitalize on emerging risks and opportunities.
You must have effective AI governance in place to make sure there is compliant and responsible use of AI systems within your organization.
Join leading companies like CAPE Analytics, Nayya, and their S&P 500 insurance customers who trust Monitaur technology and solutions for their AI governance.
Get an AI risk assessment today >>