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How to Handle Cold-Start Wallets Without Blocking Everyone

Most first lookups on Base are still thin. That does not automatically mean the wallet is bad. It usually means you do not have enough history yet to be confident.

This is the cold-start problem in one sentence: a new or lightly used wallet can look weak for the same reason a sketchy wallet looks weak. The difference is that one is early and one is risky.

If you run wallet screening in production, the goal is not to pretend that problem disappears. The goal is to handle it honestly.

Thin Data Is Not The Same As Bad Behavior

Builders get into trouble when they treat every low-information result as a hard no. On Base, many wallets are still early. If you block every thin wallet, you do not just stop bad traffic. You also stop legitimate new users and agents before they can build any history.

The practical distinction: low confidence means "we do not know much yet." High-risk means "we have enough signal to worry." Those are different states and should produce different actions.

The Three Safer Defaults

That is why the first safe policy for most teams looks like this:

unknown / unscored -> allow + log score under 25 -> block score 25-45 -> review score 46+ -> allow if confidence is solid

Why Confidence Matters

A wallet at score 40 with confidence 15 is not the same as a wallet at score 40 with confidence 85. The first one is mostly uncertainty. The second one is a much stronger negative read.

That is why production policy should not be built on score alone. Confidence is what keeps you from mistaking missing history for malicious behavior.

What To Expect In Week One

If you are integrating now, expect a lot of early results to be thin. That is normal. The product becomes more useful as you screen more real traffic, seed more active wallets, and let the route build a memory of who it is seeing.

The Wrong Move

The wrong move is to hard-block every cold-start wallet because the model is not omniscient on day one. That turns screening into a growth tax.

The better move is to start with a conservative policy, review borderline cases, and let real workflow data teach you where the threshold should sit.

Use the docs and start with the conservative pilot defaults.

Open Docs