Swedish startup Insa has launched a consumer AI product that collects and analyzes a person's entire insurance portfolio in one place, built on Insurely's financial data infrastructure. The product uses BankID authentication to pull structured data from all insurance providers, then feeds it into an AI assistant that identifies coverage gaps and duplicate policies.
Insa's early user data shows how fragmented personal insurance actually is. Users hold an average of 5.5 policies across up to 34 providers, paying roughly 12,000 SEK per year. More than half of users - 57% - discover at least one potential duplicate, such as coverage already included through a credit card or employer. For those affected, the average potential savings comes to about 2,100 SEK per year.
Why Insurely's infrastructure
Insa chose Insurely for two specific reasons, according to founder William Dahlgren: the breadth of data coverage and the credibility of the pre-built consent experience. "The breadth of the data - being able to collect across all providers regardless of insurer - and the credibility that comes with your pre-built UI were the two key reasons we chose Insurely," Dahlgren said. "It gives us credibility with our users, and it gives us the data foundation we need to successfully build something that actually works."
Insurely has aggregated and standardized insurance data across European providers since 2018, originally to help financial institutions manage customer information. That same infrastructure now supports consumer-facing products like Insa. The company's work is directly relevant to professionals exploring AI for Insurance applications, where access to consistent data is often the main barrier to building useful tools.
"Insurance is one of the most opaque parts of people's financial lives," Dahlgren said. "The data tells a clear story - too many policies, too many gaps, too much money spent on coverage people already have elsewhere. Our job is to surface that story. Insurely makes it possible."
AI's dependence on structured data
Insurance data in Europe is typically scattered across providers and formats, which makes AI applications difficult to build. Insurely's platform solves that by standardizing the data before it reaches the AI layer. For companies working on similar products in financial services, the same principle applies: the quality of the AI output depends on the quality of the underlying data infrastructure.
"Insa is a great example of what becomes possible when AI meets structured, reliable financial data," said Martin J. Gylfe, chief executive officer and co-founder of Insurely. "The consumer case for insurance intelligence is significant, and Insa is operating exactly the kind of product this infrastructure was assembled to enable."
The launch also signals a shift in how insurance technology companies position themselves. Insurely's infrastructure now serves both institutional clients and consumer product builders, suggesting that the data layer itself has become a viable business model. For those tracking AI for Finance developments, the Insa launch demonstrates how standardized data pipelines enable consumer-facing AI products in regulated industries.
Why this matters for insurance professionals
For insurance professionals, the practical takeaway is that consumer expectations are shifting. When an AI tool can show a customer they're overpaying for duplicate coverage, that creates pressure on agents and brokers to offer the same level of transparency. The data Insa has collected - 5.5 policies per user, 34 providers, 57% finding duplicates - gives a concrete picture of the scale of the problem. Professionals who can proactively identify gaps and duplicates in their clients' portfolios will be better positioned than those who wait for customers to discover the information themselves through tools like Insa.
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