Anthony Habayeb is the CEO and Co-Founder of Monitaur, helping carriers and insurance related companies define, manage, and automate responsible and ethical model governance. Anthony was interviewed by Michael Fiedel, Co-Founder at InsurTech Ohio and Co-Founder at PolicyFly, Inc.
Anthony, how would you describe the insurance market's current familiarity and acceptance of artificial intelligence?
“There's been a lot of talk about AI. It's used very loosely, and it has been for some time. Artificial intelligence is not a new idea to insurance, but the frequency and casualness of AI have become prevalent. We're at a place where anyone running a department or even an employee inside the company is curious about AI, largely because of tools like ChatGPT and foundational models. Artificial Intelligence is no longer seen as an unapproachable technology but as a tool anyone within the business might derive value from. This shift requires corporations to develop broader strategies to define what AI is and isn't, enabling them to embrace the technology thoughtfully.”
What are the key differences between new customers who understand AI and those being introduced to it for the first time?
“Within the industry, people have been building models and using machine learning for a long time - this is an actuarial industry after all. As a result, the industry has so much institutional knowledge regarding best practices to build, test and evaluate complex models. We find that bigger carriers, with a wider spectrum of internally developed models and systems, are more comfortable with how AI works and how they want to bring it into the business.
On the other hand, some carriers have historically relied more on vendor models and haven't built as much themselves. Now, with tools like ChatGPT, they have the opportunity to use AI but lack the institutional knowledge to manage its risks.”
Given all of the buzz, it feels like a safe assumption that AI-driven tools are growing. What are the driving factors expanding AI usage?
“The growth of experimentation is accelerating. Many people are testing the art of the possible, exploring secure instances of GPT, summarization tools and other capabilities. However, deploying and productionizing these ideas is a different story. Companies often see exciting possibilities but don’t know if these ideas save time, how much they cost to operationalize or how to manage associated risks. As a result, many ideas don’t make it to production.
As a result, we’re seeing more companies starting to think upfront about what’s required to move from experimentation to production. Organizations are focusing on defining KPI’s and success criteria early to avoid wasting time on ideas that won’t succeed.”
How is the general market growth around AI-driven tools leading to growth for Monitaur?
“The excitement around AI means more people within insurance companies are engaging with the technology and seeking to do it responsibly. Historically, our customers came from risk or analytics departments. Now, we’re seeing interest from product managers, claims executives and other stakeholders. These individuals recognize the potential of AI within their domains and want to ensure they implement it correctly.
This broader engagement expands our reach and creates opportunities for meaningful conversations across departments. Our governance solutions help align these diverse teams, ensuring AI is adopted responsibly and efficiently. Governance isn’t just about risk or compliance—it’s about enabling better processes that increase the likelihood of success for AI initiatives.”
What’s the vision for Monitaur over the next 12 to 24 months?
“Monitaur’s strength lies in our comprehensive solution that spans the lifecycle of AI governance. We define our maturity model as ‘define, manage, automate.’
First, we help companies establish programs with policies, controls, roles and responsibilities. Next, we enable collaboration among data scientists, engineers, IT and risk teams on AI projects. Finally, we streamline or automate these processes.
Some customers are more advanced, actively governing hundreds of models, and rely on our automation features for model testing, monitoring and validation. Others are just starting to establish their governance frameworks. Over the next 12 to 24 months, we’ll continue investing in tools that simplify onboarding, scale governance programs and automate critical validation processes.
Since 2019, we’ve been a leader in this space, and there’s still a long runway for our vision. With feedback from our growing customer base, we’ll continue evolving our solutions, ensuring we remain the leader in AI governance for the insurance industry.”