BIN Details Delivered 3X Faster

If an orchestra is out of tune, a beautiful symphony becomes a social media moment for the wrong reasons.

The same goes for merchants using data to approve or deny a transaction. If any data pieces are out of tune, it’s a chargeback, fraud attempt, and a disappointed audience.

Bank Identification Number (BIN) data is a critical piece of data that payment teams rely on. If your team is still working from monthly BIN snapshots, your orchestra could be out of tune. BIN data that the card networks remove or re-add without any continuity can create gaps that disrupt a transaction in-flight. Complete BIN data is the difference between a sweet symphony, or a sour note.

Expanded Coverage, Faster Performance 

Basis Theory’s updated BIN service now aggregates BIN data from the last 18 months. If a BIN has been seen in that time, the details come back.

The previous model pulled BIN details from a monthly network snapshot. When a card network removed a BIN between those snapshots, even temporarily, the data was gone until the next update. That gap has been closed, and the dataset will only grow from here since new data is continuously merged.

For merchants, this means dramatically fewer “no BIN details returned” responses, and a service that runs three times faster than before.

Better data, delivered faster, with no action required on your end.

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Technically Speaking 

This behind-the-scenes infrastructure update was rolled out broadly, and we are now able to deliver BIN details in real time, including at the moment of vaulting, without having to download files or refresh stale data.

The speed improvement comes from a fundamental change in how we retrieve this data. Previously, the service depended on an intermediate file to determine what data to pull, and from which database. This extra step added latency.

We now query the database directly, and the result is response times around 2ms, compared to 10ms before. That difference isn’t noticeable to the user, but it reflects a more resilient architecture that supports everything being built on top of it.

Teams that are making real-time decisions based on BIN data will find this update impactful. Specifically:

• Merchants evaluating whether to accept a payment based on card properties like prepaid status, segment, or issuer country. Now, you have a far more complete picture at the moment of decision. Accepting a non-reloadable prepaid card for a subscription is a chargeback waiting to happen. With more complete BIN data, the call for routing is easier to make upfront.
• Teams optimizing payment routing decisions. Knowing the issuer and card type at the moment of vaulting enables a merchant to route transactions to the processor offering the best authorization rate or most favorable processing fee.

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What This Unlocks 

This architecture is a stepping stone, not a bug fix. We have set the foundation for regional BIN intelligence, meaning specific issuer-level data can be merged into a global BIN details table.

Today's BIN data comes primarily from card networks and is global by nature. The next step brings in issuer-specific records that reflect regional nuances, giving merchants a more precise picture of every card in their vault.

That work is next on our roadmap, and the infrastructure to support it is already in place. In the meantime, the improvements are live and ready to explore.

The best way to experience the improvement is to test it directly. Create a card token and look for the card property returned in the response. You'll notice more data coming back and a much higher likelihood of receiving complete BIN details for the cards you're vaulting.

Get started using our documentation.

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