Monitaur is an AI governance software platform that helps organizations manage and govern the entire lifecycle of their AI systems. It provides a complete risk management solution to record, monitor, govern, and audit AI, ensuring machine learning assurance.
1. Sign up for an account on the Monitaur platform 2. Create a project and define your AI system 3. Use the platform to document the lifecycle of your AI journey 4. Leverage user-friendly workflows to ensure responsible AI practices 5. Monitor for bias, drift, and anomalies 6. Govern and comply with AI governance frameworks 7. Record, inspect, and verify AI models 8. Audit your AI systems to maintain transparency and trust
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Social Listening
Do you have any advice for others considering AI governance?
Watch the full discussion in our webinar: https://info.monitaur.ai/cape-webinar-download-registration "Put your controls on a piece of paper, see if they're covering every aspect of risk that you see in your modeling organization just start there. And then after you build the controls, then you start saying, well, how am I gonna prove that? I actually complied with that control? Who needs to be involved with that in the organization? What does that document need to look like? What are some of the affirmations that need to be in that internal document that says, OK, the project engineer on that model actually thought about that issue and wrote the answer in this document? So it's a building thing but it really does start, I think with those core risk controls and once you get those on paper, it does start to flow."
What validation have you had that AI governance is worth the investment?
Watch the full discussion in our webinar: https://info.monitaur.ai/cape-webinar-download-registration "We now have a consistent approach to every model that is going to be put into development. It starts with a product document that contains a lot of the goals of the project. It includes a legal review, which a subset of that is review to make sure that we're complying with the actuarial standards, the AAPS. So that is part of the process that we go into. So definitely having standardization has been an absolutely huge benefit. I think another huge benefit to the organization is a high level of visibility to everybody who needs to know information about a particular model because we have a standardized set of documents, those need to be reviewed and signed off on by participants in the modeling process including myself. So that I think has been extremely beneficial to us in terms of having one source of truth, so to speak. And in terms of business benefit for us, we are seeing our clients are more attuned to the regulatory environment and what's happening. And AI and making sure that they have other ducks in a row again, even though there is not a specific regulation other than I think the Colorado one that is applicable. We're seeing increased interest on that end. So it's, it's very comforting to know that we are in a position to be able to satisfy that need. The client need for those insure tax out. There is significant, I think confidence in our models, but by our clients will be a byproduct that it is helping us to quite frankly be able to respond more quickly to client needs and requests around the pricing rate use case because we are now everything is, it's organized. It's not like we have to search for data, we know where to look and get it. So that's created some efficiencies for us in there. I can't overstate that. It's really a business driver at the end of the day."
29. Machine Learning Assurance with Andrew Clark - CTO of Monitaur
Note: This is a guest interview. Andrew talks to us about machine learning (ML) and what auditors should consider regarding ML assurance. You can reach out to Andrew via the Monitaur (https://monitaur.ai/?utm_source=assurshow&utm_medium=pod) website. About this podcast The podcast for performance auditors and internal auditors that use (or want to use) data. Hosted by Conor McGarrity (https://www.linkedin.com/in/conorfmcgarrity) and Yusuf Moolla (https://www.linkedin.com/in/yusufmoolla/) . Produced by Risk Insights (https://www.riskinsights.com.au/) (riskinsights.com.au).
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