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At first glance, auto insurance and mobile device protection appear to be very different industries. One protects vehicles. The other protects smartphones. But fundamentally, both industries face the same core problem: How do you fairly price protection when customer risk varies dramatically from person to person? The auto insurance industry solved this problem through telematics and behavioral pricing. Now, mobile protection is beginning to follow the same path. Auto Insuran

Mobile protection has been around for decades. But one thing hasn’t changed much over time — how we think about the customer. Most programs still assume a relatively uniform user base. One price. One product. One experience. But when you look closer, that assumption starts to break down. Not All Customers Behave the Same In reality, mobile protection customers fall into very different behavioral categories. Some users: Rarely engage Almost never claim Stay on programs for lon

Enterprise insurers competing in device protection and adjacent short-tail products face a familiar constraint. Actuaries are asked to price increasingly competitive programs using largely similar historical data, comparable assumptions, and limited visibility into real-world customer behavior. As a result, differentiation becomes difficult — and competition compresses toward price rather than structure, fairness, or long-term performance. Over the past several years, we’ve b

And why the industry is heading down this path whether it realizes it or not For decades, mobile protection and extended warranty programs have been built on a simple premise: price everyone the same. A careful user and a chronic phone-dropper both pay identical premiums. That made sense in a world with limited data and basic devices. But that world is gone. Smartphones now generate incredibly rich sensor data. AI has matured. Consumers expect personalization. And behind the

How behavioural intelligence turns everyday data into predictive power.

Artificial Intelligence is everywhere today. Every industry conference has AI panels, every vendor touts an AI-powered solution, and every corporate strategy deck has AI in bold letters. But back in 2019, before the hype cycle, before Generative AI dominated headlines, our team at AmplifyIQ was already building with it. And not because it was trendy. We did it because it was the right way to solve a problem no one else was addressing. Why We Started Early Traditional mobile

When we came up with the concept of risk based variable pricing for phone protection it all made sense, after all, it was what we felt customers wanted, but we faced a paradox from the beginning. To build a variable pricing model, you need real-world behavioural data. But to collect that data, you first need a live variable-pricing program. That circular dependency has kept the industry in place for years. Everyone knew personalization and fairness were the future — but nobo

The numbers look strong — but customers don’t feel the same. In the late 90s, mobile insurance was an innovation. It quickly became a...

When our team began R&D, we were chasing a problem no one else in the industry had solved. The market was dominated by flat pricing...