The foundation models we see today won’t look like the ones we will see within the next few years. How are you planning to evolve your governance as the landscape of more advanced models continues to grow? AI governance is becoming an essential part of modern business strategy. Monitaur can keep you ahead of the curve and align continuously with regulations, ethical standards, and societal values.
It’s natural to struggle with an overarching approach to the very diverse world of AI and models. The explosion of frameworks and opinions makes it even more challenging to traverse from principles to action. You need a comprehensive yet comprehensible approach, one that works from the board-level down to your model builders and users.
Let Monitaur’s experienced team of governance experts speed up your conversation about AI so you can move into governance execution.
Regarding generative AI or AI agents, don’t be fooled. Generative AI apps, LLMs, AI agents, and their native foundation models need to be governed just like the other models used in your business. Without clear objectives, an understanding of risk, and an effective approach for measuring success, adoption will fail.
Rely on Monitaur to ensure that your approach to AI apps and tools fits within your whole model governance and risk management strategy.
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Monitaur provides deep technical tools for modeling teams that need to understand their impact on the business and its customers. With easy-to-use libraries and clear guidance, we elevate monitoring from experiments into an active step in governance visible to all stakeholders.
Model monitoring can provide a lot of insight for data scientists, but dashboards alone don’t lead to better models. You need to stress-test your models to know they are ready for production. And once they’re live, you need monitoring with purpose – continuous proof that your models are operating as designed.
Monitaur’s validations work across the model lifecycle to guarantee that every stakeholder – technical and non-technical alike – can see problems, root causes, and their resolutions.
Your models have to be fair. “Fairness through unawareness” doesn’t work in a court of law or the court of public opinion. Proving that your models are fair can get complicated by evolving expectations, unclear regulatory guidelines, and potential proxy discrimination.
Monitaur moves fairness within your company’s reach thanks to our expertise and powerful tools for measurement and demonstration.
Don’t be in the dark about the value of your investment in AI and models. Good governance goes beyond risk mitigation to weigh the opportunity and economic impact that models have on your business. To maximize that value, you also need to ensure that your models can handle unpredictable, real world events before they’re put into the wild.
With Monitaur, you can connect the technical performance and robustness of your models directly to key business metrics.
Monitaur provides the bridge between first-line modeling teams and second-line teams in risk and compliance functions. We enable risk to give the business confidence that AI is used safely and responsibly and compliance to ensure that new regulatory requirements are fulfilled.
Across the globe, AI regulation is coming fast and furious. Keeping track of the changes and updates is a difficult enough task. Upskilling compliance teams to understand models and work with technical teams allows your team to avoid non-compliance and the fines that come with it.
Monitaur can provide your team with the training and collaboration tools to ensure all your models are ready for every regulation.
AI is everywhere. Enterprises are buying more GenAI products while your current vendors are scrambling to embed more AI into every corner of their products. How do you contain the risk and still provide access to the best tools for your employees?
Monitaur allows third-party risk teams to triage vendors by risk and perform thorough technical validations for high risk use cases.
It’s challenging to stretch your limited model risk resources to tackle even your highest risk models. And that’s assuming you even have an MRM team to perform independent reviews. You need a way to reduce risk across your entire model portfolio, not just the lowest hanging fruit.
Monitaur’s Controls Library and technical validations ensure that first-line teams provide everything needed to perform rigorous model risk management in a consistent and scalable way.
Enhance your automated decisioning with smart AI that’s streamlined and compliance-ready
Improve profitability and customer retention with well-governed data that stays compliant throughout its AI/ML lifecycle
Responsible AI enhances your ability to maximize your AI/ML potential for predictive modeling, risk assessment, and enterprise risk modeling
Incorporation of data from new sources using clean, responsible AI speeds up claims processing and improves loss forecasting
New data sources and advanced modeling techniques, when governed, help curb the potential impact of fraud
Identify best fit customers and drive market share with ML-optimized offerings
Widen your prospective field and stay more competitive with AI that’s flexible, responsible, and secure
Perform robust stress-testing to ensure fair and unbiased AI continuously
Identify bad actors with well-governed AI that enables more transparency and risk reduction
Govern advanced modeling architectures to reduce high cost false positives
Collaborate across go-to-market and technical teams throughout the model lifecycle
Stay compliant with emerging regulation of AI for prior authorization
Create repeatable AI governance program for your most innovative products
Use AI responsibly to deliver life-changing patient experiences
Expand financing options for customers in protected classes
Expand your candidate portfolio safely with robust, context-aware AI
Narrow the target pool and optimize acquisition of study participants
Fulfill the requirements of current and emerging regulation of HR Tech
Guarantee fairness and compliance throughout the employee journey
Scan screening algorithms for bias that impacts your diversity initiatives
Manage compensation and performance review with responsible AI use
Enhance your workforce with safe, early training interventions
Ensure fair distribution of benefits resources to your employees
