Insurance Edge met up with Noga Aloni, Director of Product at Earnix Excelerate 2025 in London, to learn more about the Earnix offer to insurance carriers, market trends, partnerships and more.
IE: There are lots of insurance partnerships now in the embedded sector, where brands are tailoring products for an impulse buy, say in travel insurance, where data really makes a difference. Is Earnix seeing more of that trend recently?
NA: Yes, we are seeing more of that trend. In embedded insurance, data sharing and feedback loops between the brand, agent, and customer are crucial. With our recent acquisition of Zelros, Earnix is focused on turning the vast amount of available data into actionable insights.
Historically, insurers often had data locked away in lakes or systems like Snowflake, making it hard to access or apply effectively. Earnix bridges that gap by acting as a layer that helps insurers unlock and use their data more efficiently – enabling partnerships, smoother product launches, and ultimately more tailored embedded offerings.
IE: Listening to one of the speakers earlier, they said that as an insurance brand they wanted to create premium products, add value, otherwise it’s just a race to the bottom on price. Are there roadblocks within the data systems some insurers or brokers have that prevent them from unlocking some of that premium value?
NA: At Earnix we look at the whole flow; you’re bringing in the data, the planning, to decide your final strategy. We are looking at making it easier for them to develop the best decision-making – it’s all about getting the best data into their application. This goes a long way to creating a premium product.
IE: I guess for brands that are in a real niche area of insurance, say TV or movie production, specialty lines, it can be high risk, and the data is very specific to that niche area.
NA: Yes, but in niche and high-risk areas like specialty lines, the key challenge is ensuring the data supports effective decision-making. We always ask clients how they’re using their data today and how it aligns with their goals. What we’ve found is that by identifying the fastest transformation and integration points, we can help clients unlock the value of their highly specific data and get them to their desired outcomes more quickly.
IE: Across most of Europe now it’s a very multicultural market, with many different accents and regional dialects too. Do you see LLM (Large Language Model) software evolving and learning all these different languages and slang words etc to meet compliance regs in future?
NA: If I look at our product just a few years ago translating different languages was quite difficult, but things are changing fast thanks to AI. Being bi-lingual myself, I see all kinds of AI tools doing a better job now on translation.
IE: If people use their phones to buy insurance using voice ID, not typing, in the future, then understanding all the nuances within one language will be essential. For insurers that can deploy that LLM tech the opportunity is there perhaps?
NA: I can see a huge opportunity there for sure. I speak with lots of global teams and now we have synchronised voice translation during the meeting. We can think about the way people access insurance products, learn all dialects and make sure that say Chatbots can understand those conversations in the future.
When I look a little wider into, say Underwriting, then I see that Earnix tools can help them get more done; be compliant, use language tools to service customers speaking different languages and so on. It is really all about assisting insurance brands and their staff, so people aren’t replaced, they have AI agents or co-pilots at every stage, so that makes them be the best they can be. All that is a big step up from where we were just a few years back.
IE: Are there different directions now for AI deployment across the insurance chain; Agentic, GenAI, Data Analytics etc?
NA: Well AI is not new. It’s moved beyond say Predictive AI, asking the software will someone buy or not? It’s being applied everywhere in insurance. Now we have a chance to talk to an AI system using natural language, ask it to do specific tasks, or you can create an AI Agent and let the customer work with that dedicated Agent. It’s evolving fast and we are building what people can use, what suits their needs.
IE: Do you see more regulation of AI in the future?
NA: Earnix has been working in financial services for a long time, and so we are used to supporting our customers with being compliant across territories. That’s an advantage for us, a good starting point. We also train our staff so they know they product and how it can be personalised for each client, because different companies have their own goals.
This is the way that AI will develop in the future, and it won’t just be a toolkit that only helps a certain demographic like younger people already used to the internet. AI can be empowering for every brand, every customer too. Insurance is a cautious industry; regulators have that same cautious approach too. Everyone knows it’s necessary to have all the correct data for decision making. It’s really the same way of doing things historically as regards insurance but using AI to get deeper insights and make it happen that bit faster.
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