What Aggregate Claims Data Reveals About Carrier Settlement Patterns

Two homeowners file claims with the same insurer. Similar damage, similar policies, same state. One claim settles in 90 days. The other drags into a lawsuit, then an appeal. Looking at either file alone, there is no obvious reason why. Look at thousands of claims with that insurer at once, and the pattern shows up.

How insurers handle claims is not random. Each carrier — the industry word for an insurance company — behaves in patterns, and those patterns become visible in bulk. Insurers have always been able to see their own patterns. The lawyers who sue them usually cannot. DAIS was built to close that gap.

What this data is, and what it is not

Aggregate claims data is not a lookup tool. It does not pull up any individual claim file or identify any policyholder. It shows patterns across thousands of claims, sorted by carrier, claim type, state, and outcome.

Three patterns matter most. How fast a carrier typically closes a given type of claim. How often similar claims escalate from a demand letter into a lawsuit. And whether a carrier tends to settle before a suit is filed or only after. All of it comes from aggregate, anonymized records.

One line matters more than any other: this data describes what a carrier has done across many past claims. It does not predict what the carrier will do in yours. It is a historical read on where a case sits, not a prediction.

How attorneys use it

Not as evidence. The data does not go into a court filing or prove that a carrier "always does X." It informs the work that happens before anything is filed.

An attorney framing a demand can set expectations against the carrier's typical resolution window instead of a generic timeline. When the carrier sends a guarded response, its track record in similar situations helps the attorney read whether that signals a coming denial or a routine step.

The data also flags claims that are running off track. If most comparable claims resolve within 120 days and a client's claim sits at 200 with no real response, that gap is useful context — not proof of anything, just a marker of what the carrier's own history says is normal.

The limits

Every case turns on its own facts, its own policy language, and its own state's law. A claim that runs off the carrier's usual track may have an innocent explanation. A claim that tracks the pattern exactly may still involve misconduct. The data adds context; it does not decide anything.

It is also historical. Carriers change how they behave — after new regulations, new management, or big verdicts. A documented past pattern is not a guarantee about the future. Used that way, as one input into a careful case evaluation rather than a substitute for one, the data earns its place.