(Image credit: NoName_13/Pixabay.)
After two decades building insurance programs, products and risk models across carriers, MGAs and international markets, Rajiv Matta says Lilypad Insurance (New York) offers something he has rarely encountered: a platform largely free of the legacy constraints that have slowed insurance innovation for years.
Lilypad Insurance, an admitted property/casualty insurance group focused on coastal property risk, appointed Matta Chief Innovation Officer in May. The company says Matta will lead its use of artificial intelligence and emerging technology across underwriting, distribution and product development. Matta says that description is accurate, but that his role extends to business innovation.
Rajiv Matta, Chief Innovation Officer, Lilypad Insurance. (Click to enlarge.)
“It includes new program development and new verticals that I’ll be launching as well,” Matta elaborates. “Accelerating all of these initiatives with AI—and also accelerating our AI strategy—are all part of my job.”
For Matta, the opportunity rests on the fact that Lilypad is part of Arbol, whose data and analytics infrastructure can support more granular risk selection in difficult coastal markets. Lilypad serves homeowners and commercial insureds in coastally exposed geographies, with a particular focus on Florida and the Gulf states, as well as Hawaii. The company is licensed in Florida, Texas, Louisiana, Massachusetts, Oklahoma, Mississippi, Alabama, South Carolina, North Carolina and Hawaii.
Matta describes Lilypad’s proposition simply: provide the right coverage for the right premium by using more precise risk analytics than the market has traditionally applied.
“By getting more granular, you are differentiating risk between properties that are essentially in the same ZIP code and might be next to each other as well, but the characteristics are different,” he says.
That observation goes to the heart of Lilypad’s market argument. Coastal property insurance is often discussed in terms of availability and affordability, but Matta frames the problem as one of precision. Traditional risk analysis has too often relied on coarse territorial measures, out-of-the-box catastrophe models or averaged assumptions that may obscure meaningful differences from one property to the next. Lilypad’s approach, he says, is to bring more data points into the underwriting process and use AI to make that information operational.
Examples include more detailed data about crime, wind gust behavior, the effect of building shadows and the way topography interacts with wind. Matta says much of the data has been available, but AI now makes it possible to analyze and apply it more effectively.
“All that data has been available,” he says. “It’s just now with AI, we can analyze that a lot better.”
A Career Built Around Risk and Programs
Matta’s arrival at Lilypad brings together several threads of his career. He began in hazard analytics after earning a master’s degree in environmental engineering from Clemson University, working as a consultant to the National Flood Insurance Program during its flood-map digitization effort. He later became a project manager on maps for several states and worked on broader hazard mitigation, including flood, hurricane, dam failure, precipitation and earthquake exposures.
That foundation led to a role with the technology and R&D division of Tokio Marine, where Matta worked on new ways of analyzing risk and building models. He developed a flood model for Mexico and a hail model for Europe, and attempted to build a flood model for China before data constraints limited the effort.
Siddhartha Jha, Founder and CEO, Arbol.
At Assurant, Matta built new products and programs and later led the company’s international property and casualty business, overseeing a diverse portfolio that included mobile phone warranties, dwelling and homeowners insurance, reinsurance business in Mexico and the Caribbean, and an auto insurance MGA in New Zealand. He then joined Millennial Specialty Insurance, where he led emerging markets, created new commercial and specialty verticals, participated in M&A activity and was part of a platform that grew from roughly $100 million in premium to more than $1 billion.
Matta also holds two machine learning patents, filed years before the current AI boom. He emphasizes that they were not theoretical exercises but solutions to specific business problems deployed at Assurant.
“If you look at my career over the last 20 years, it’s really been mostly focused on analytics, but also focused on new program development,” Matta says.
That combination is central to why Lilypad CEO Sid Jha characterized Matta’s appointment as timely for the coastal insurance market. In the company’s announcement, Jha says Matta’s experience building programs at scale and his conviction that AI must be embedded across the full value chain made him the right leader as Lilypad expands.
Four Paths for Growth
Matta describes his initial agenda at Lilypad in four broad categories. The first is cross-selling. Where Lilypad is already having success with a product, customer segment, state or distribution channel, Matta is asking what else can be offered to that same customer base.
The second category is close adjacencies—new products or programs that sit near Lilypad’s existing underwriting, data, AI and distribution capabilities. He gives examples as possibilities rather than announcements: if the company writes condominium associations, could apartments be a close adjacency? Could hotels and motels be another? Could a property-focused product be expanded with general liability?
The third category is what Matta calls stretching the core: identifying market gaps where Lilypad’s analytics and AI-native capabilities might allow the company to solve a problem others have not. As an example, he cites liquor liability in Florida as an area where machine vision and AI capabilities might contribute to a new approach, though he stresses that he was not announcing any specific product.
The fourth category is accelerating Lilypad’s AI strategy itself.
“I am a strong believer in the sea change we’re seeing,” Matta says. “It’s real. I am experiencing it myself.”
That experience has been immediate at Lilypad, he says. In prior roles, building a policy form might take three months. At Lilypad, he says, comparable work can take three days because of the AI-native infrastructure already in place.
That speed is not merely a process improvement. For Matta, it changes what an insurance organization can spend its energy on. He argues that for too long, insurance talent has been trapped by operational and technology constraints: endorsements, processing work, disconnected systems, manual workflows and the sheer difficulty of making old systems do new things.
“You need to do an endorsement effectively in a timely fashion, and it doesn’t have to be such a ginormous task,” he says.
Owning More of the Risk Analysis
One of Matta’s sharper critiques is that the industry has outsourced too much of its risk analytics to a small group of external model providers. He is quick to acknowledge the value those firms have provided, but he argues that the industry needs to develop more proprietary risk insight of its own.
That point is especially relevant in coastal property. As climate-related loss patterns become more localized and volatile, the ability to distinguish one risk from another becomes more strategically important. Matta’s argument is not that AI replaces underwriting judgment or catastrophe science, but that it allows carriers to internalize more analytic capability and apply data with more precision.
The shift also has economic implications. If AI can reduce the time and expense associated with routine processing, product configuration and system work, carriers can redirect investment toward risk analytics, mitigation, resiliency and customer value. Matta says insurance has spent too much of its best talent and capital on work that should be table stakes.
“What’s important is the insured getting the right coverage at an affordable price and getting the right service,” he says.
He adds that resources currently devoted to processing work should move into better risk analytics, mitigation research, resiliency research and practical value for customers.
The Advantage of No Legacy Drag
Lilypad’s timing matters because the company is not trying to retrofit an AI strategy onto a heavily burdened legacy environment. Matta says many carriers have spent years and substantial capital digitizing systems that may now face pressure from AI-enabled alternatives. That creates difficult questions: whether to preserve sunk investments, modify them or replace them.
Lilypad, by contrast, starts from a different position.
“We also don’t have this overhang of being this legacy carrier with a lot of different disconnected systems or data sitting everywhere else,” Matta says. “We have a fresh start here.”
That lack of legacy drag is central to Matta’s enthusiasm. He says Lilypad can embed AI into processes from the beginning rather than bolting it onto old workflows. The result, in his view, is not just faster operations but a different kind of insurance company—one able to move from risk insight to product development to distribution with far less friction.
Matta compares the pace of change to moving from a typewriter to a smartphone in a matter of years rather than decades. For carriers with long technology roadmaps, that pace can be disorienting. For Lilypad, he suggests, it is an opening.
“We’re not tied to anything,” he says. “There’s a new efficient way.”
A Transformational Moment
Matta is careful not to announce specific new Lilypad products prematurely. But the outline of the opportunity is clear: a coastal insurance platform with proprietary analytics, AI-native infrastructure and an expanding admitted-carrier footprint, now joined by an executive whose career has combined hazard modeling, product development, specialty insurance program building and machine learning.
That makes the appointment more than a personnel announcement. It signals Lilypad’s intention to use AI not as an add-on capability but as an organizing principle for growth.
Matta says his role is to connect the dots among the tools, talent and momentum already present at Lilypad and Arbol—and to bring the market experience needed to turn those capabilities into programs that work.
“This has worked in the marketplace before,” he says. “How do we navigate this specific cycle? How do we accelerate our AI strategy? How do we get even better from servicing our customers and what new products make sense on a platform like Lilypad?”
For Lilypad, the answer may define its next stage. In a coastal property market under pressure from climate-driven losses, capacity challenges and affordability concerns, Matta’s bet is that AI-native execution can do more than make insurance operations faster. It can help the company select risk more accurately, build products more efficiently and focus scarce industry expertise where it belongs: on coverage, pricing, service and resilience.
Lilypad Insurance Selects BriteCore for Core Platform Expansion