AI in Business Insurance
Uh great, my name is Lisa Dolan. I’m a managing director with Link Ventures. You probably have heard Dave Blendon speak. We are a fund that’s very much focused on AI. We look at foundational models, horizontal models, and also verticalized applications. So today, we’re going to be talking about the application of insurance. The PNC Market in the U.S. alone is just under a trillion dollars, so this is in the camp of very high-value users. Within verticalized applications, I really focus on founders that truly understand their user and are building proprietary data. So today, we’re talking to enterprises and startups alike, some of which we have invested in, some of which I wish I had invested in. So to start, I’d like everybody to introduce themselves, and then we can go into it.
Panelist Introductions
Starting with you, Marson.
Yeah, so I’m Marson, the group chief data scientist of AXA, which is not that well known in the U.S. but is one of the biggest insurers in the world. I run a research team, and moreover, I started my PhD thesis during the winter of AI, so I’ve been around AI for a lot of years.
AI in Insurance: Concrete Use Cases
So now, let’s dive into some concrete AI use cases. Starting with you, Marson, how are you at AXA using AI?
We deploy AI in two main ways. First, we provide secure access to OpenAI’s backend models for all our employees. These AI co-pilots handle smaller tasks that add significant value. We also use AI for more transformative functions like translating contracts into computable formats, helping us streamline processes and reduce costs.
The Future of AI in Insurance: Transformation of Pricing and Underwriting
Christopher, how do you see AI transforming pricing and underwriting in the next year and beyond?
In the next year, AI will assist in faster claims processing by improving data collection, analyzing accident severity, and identifying key details like bodily injury. Over the next five years, dynamic pricing based on real-time data, including telematics, will revolutionize pricing models.
Risk and Talent Shifts in the Industry
How do you see the balance of risk shifting, and where do you think talent will move in the insurance industry?
As AI democratizes, we’ll see more data scientists transition into roles that merge data science with traditional insurance knowledge. The talent pool will shift towards a deeper integration of technology in insurance, focusing on improving risk assessment, reducing human error, and offering more personalized solutions.
Innovative Approaches: Startups and Enterprise Collaboration
For startups, integrating with large carriers like Allstate or AXA is often challenging. How do you approach working with startups?
For startups, having a clear value-based use case and dedicated internal teams for implementation are crucial. Partnerships must focus on solving one problem really well, with executive sponsorship ensuring the integration of AI in existing systems.
Future of Risk and Insurance
As AI evolves, the nature of risk will change, especially with autonomous vehicles and systemic risks emerging from widespread model use. AI’s role in insurance will shift, and insurers will need to understand and adapt to these new types of risks.
Conclusion
The future of AI in the insurance industry is promising, with rapid advancements in data usage, claims processing, and dynamic pricing. Startups and enterprises alike need to collaborate closely to foster innovation, with an emphasis on integrating AI into all aspects of the insurance lifecycle.
