As AI takes centre stage at industry conferences and across the broader financial sector, Definity’s commercial insurance chief says the Canadian P&C market is at a turning point.
For years, the industry quietly used AI behind the scenes – powering pricing models, segmentation tools and predictive analytics. But according to Obaid Rahman (pictured), senior vice-president and chief underwriting officer for commercial insurance, the next phase is fundamentally different.
“The insurance industry has always been a very data-driven industry,” Rahman said. “We’ve been using AI for over a decade in our pricing, in our segmentation… we’ve had machine learning models embedded in many components of our analytics.”
What is changing, he said, is where AI is now being deployed – moving out of the back office and into customer-facing interactions, underwriting workflows, and broader operational processes. Large language models (LLMs) in particular are enabling a shift that goes far beyond rating and predictive loss modelling.
Rahman said Definity has already integrated LLM-driven tools into parts of its business, with the early focus on improving the customer experience and reducing friction in its direct channel.
“We’ve deployed some large language models on our chatbots,” he said. “Those are interacting directly in our direct channel with our customers.”
The company is now preparing to bring similar tools into commercial underwriting. The first wave involves underwriting assistants designed to accelerate intake, reduce information leakage and support frontline underwriters in understanding risk faster and more consistently.
“What this will do is accelerate how quickly you can understand the risk, how quickly you import a risk,” he said. “So the service a broker will get – they’ll get it much faster.”
Rahman sees these capabilities as the gateway to a longer-term transformation. As the technology matures, the question is not whether underwriting automation will happen, but how far carriers can go while still maintaining disciplined oversight.
“That really becomes the first step,” he said. “Eventually, you’re going towards: how much underwriting can you actually automate through AI?”
For all the attention AI has received, Rahman said technology is only part of the equation. The more difficult (and more important) step is changing the processes that surround it.
“Just having the technology on its own doesn’t immediately make you efficient or give you a great customer experience,” he said. “The biggest component is you have to change your process, your workflows, how you operate as a business, and incorporate the technology.”
That level of operational adaptation takes time, especially for large carriers with established systems, functions and dependencies.
“These are large companies,” he said. “You bring in a new technology – you still need to function the company, and then you’ve got to incorporate it into your way of working. That’s why it’s going to take a little bit of time as this rolls in.”
Still, Rahman expects the cumulative effect to be significant. Within the next five to seven years, he anticipates a commercial insurance environment where AI is deeply embedded across underwriting, claims, adjustment processes and customer interactions.
While Definity is building out internal capabilities, Rahman said the second major focus is the broker ecosystem. Brokers remain the company’s primary customer, and many are now developing or considering their own AI tools – something carriers will need to support if the market is going to evolve cohesively.
“The second area of what we’re trying to explore is: how do we help brokers?” he said. “They have to deploy their own AI solutions for the customers they’re servicing. For us, it’s how do we best support them? How do we build one seamless experience between the carrier and the broker? Because that’s really what affects the customer.”
At a time when brokers face rising expectations around speed, accuracy and digital access, Rahman said alignment between broker systems and carrier systems will become increasingly critical.
Rahman noted that Definity has spent years preparing its architecture for this next phase of AI adoption. Those investments – in cloud infrastructure, data modernization and system upgrades – are now enabling the company to move faster on emerging use cases.
“We really are, I would say, on the forefront of this,” he said. “We made big investments in our infrastructure to be prepared for this. We moved all of our data into a cloud infrastructure, which puts us in a very strong position to deploy many of these tools.”
