Raunak Mehta
Igloo’s rise as an AI-native insurtech did not come from a sudden pivot or an epiphany in the boardroom. Rather, as Co-Founder and CEO Raunak Mehta puts it, the company’s transformation was a natural consequence of decisions made years earlier, long before AI became the defining theme of global business strategy.
“I think it’s more of a natural evolution, not so much of a certain inflection point,” Mehta explains. “Ever since the inception, we have been deeply invested into frontier technology. Before the AI moment in 2022, we were already deploying machine learning and neural networks for insurance use cases.”
In a region where digital maturity is highly uneven, Igloo’s early bet on data and engineering discipline positioned it to move faster than traditional insurers. While global enterprises struggled with failed proofs of concept—echoing what Mehta describes as the “classic MIT study which said 95 percent of POCs are failing”—Igloo had already built the structural foundations required to scale AI across the value chain.
This foundation was fueled by data. With more than 80 million policies facilitated monthly, over 40 million customers served, and roughly 400 product-plan combinations in circulation, Igloo holds one of Southeast Asia’s richest and most diverse insurance datasets. “AI ultimately comes down to what kind of data is fed to the AI and in what structure it is fed,” Mehta says, noting that the company’s knowledge graph, built over seven years, enables its agents to understand relationships among policies, behaviors, and risks with unusually high precision.
This dataset is what powers Igloo’s AI-native workflows today. From underwriting to product recommendation, claims adjudication to fraud detection, nearly every part of Igloo’s operations now carries what Mehta calls “some flavor of AI.” The company’s recommendation systems illustrate this clearly. In Indonesia, auto insurance customers receive real-time suggestions based on where they live, their exposure to natural disasters, or potential theft risks.
“We have seen conversions jump by 30 to 40 percent because of this,” he notes. “We are making insurance a lot more contextual to the consumer base.”
The impact is particularly relevant in markets with entrenched underinsurance, such as the Philippines, where penetration remains below two percent. “People are not getting access to insurance products,” Mehta says. “They are not having products that are contextual to them and not at a price point they can purchase.” AI, he argues, will dramatically expand access by simplifying discovery and reducing cognitive barriers for first-time buyers.
A conversational buying interface is already in development, designed to guide users through insurance decisions in natural language instead of menus and comparison tables. “Insurance is not an area where you know what you want,” he says. “It comes down to how you are guided. AI is playing that role.”
Claims processing, long one of the slowest pain points of the industry, has been reengineered using Igloo’s agentic AI model. “Claim timelines have fallen from two to three days to a span of minutes,” Mehta says. Through document parsing, real-time validation, and automated adjudication—already deployed in Indonesia—customers receive near-instant feedback. The company reports a 70 percent reduction in operational expenditure linked to claims management.
Looking ahead, Mehta sees the biggest breakthroughs in underwriting and advanced claims decisioning. “These two areas are probably the most complex in the insurance industry,” he notes. “We should be able to bring them onto one platform. You will start seeing this rolling out in 2026.”
He also believes AI will reshape product innovation itself. By training models on decades of regional product structures, Igloo is beginning to generate entirely new insurance categories tailored to the needs of underserved populations. “If you ask AI to come up with a product, it will come up with a product,” he says. “But if you provide the right grounding, it can give you a list of products that can really solve penetration problems.”
Operational efficiency, improved conversions, and AI-powered engineering productivity will contribute to Igloo’s goal of breaking even in 2026, even as capital expenditures increase. “AI will help us increase margins and avoid linear expansion of our operations team,” he adds.
For Mehta, the endgame is clear: an insurance ecosystem that is scalable, contextual, and personalized. “Almost everything is going to have some flavor of AI,” he says. “This is the journey of becoming AI native.”