Insurance disputes often come down to a simple question: "The evidence you provide, why should I believe it?"

A heavy rain, a delayed flight, a hospital diagnosis—facts that seem clear-cut can easily become distorted once they enter the insurance company's system. Why does a sensor show 95 millimeters of rain when the farmer reports 100 millimeters? Why does the flight delay certificate provided by the passenger differ by a few minutes from the airline's records? Which set of medical test data is the authoritative standard?

The issue is never the insurance policy itself; the key is: how to prove that a fact is true, verifiable, and impossible for one party to tamper with.

In recent years, more and more financial and insurance agreements are integrating data verification networks. Their role is not simply to "transport data," but to act as neutral data certifiers.

Take crop insurance as an example. The traditional approach is: farmers submit rainfall data → insurance companies question the accuracy of measurement tools → endless disputes. What if we change the approach? Multiple independent meteorological sources simultaneously record data on-chain, with each record carrying a timestamp, source label, and complete verification path, all transparent. On the day of claims, whether to pay or not is clear—using a reproducible chain of evidence, not just the loudest voice.

The same logic applies to flight delay insurance. If your delay proof conflicts with airport announcements, the verification network will simultaneously call real-time airport notices, air traffic control data, and third-party flight information sources, ultimately generating a consensus fact without single points of failure. Want to tamper? You’d need to manipulate all data sources, which becomes exponentially more difficult.

The financial lending sector is even more complex. Clearing triggers, RWA asset valuation, stablecoin collateral ratios—every risk control decision relies on data. If the data sources are opaque, even the strongest risk management system is like building on quicksand. When problems arise, it’s discovered that the original data sources were flawed.

What data verification networks do is truly disruptive: they turn a piece of data into a living, auditable record—clearly showing where it came from, who verified it, who referenced it, and when it was uploaded on-chain. Once this system is operational, most of the disputes in insurance claims will disappear.