In the high-speed world of digital transactions, every transaction is supported by identifiers and protocols, underpinning transaction processing. These identifiers help in payment routing, verifying authenticity, and in pulling up transaction details. One of the most significant identifiers is the BIN (Bank Identification Number), which is the first six to eight digits of the payment card number.

Let’s say your payment gateway flags a high-risk transaction, prompting you to gather more information, like verifying the origin of the card used. Was it issued within the country or overseas? Is it a credit or debit card? Which bank issued it? This information is embedded directly on the card within the BIN.

For businesses that accept card payments, whether through an ecommerce store, in-person point-of-sale, or a subscription-based billing model, BINs often surface during scenarios involving payment routing issues, chargebacks, or fraud investigations. For merchants and payment professionals, understanding BINs offers strategic insights into how card-based transactions flow through the system.

BINs: The number behind every payment

What is a BIN?

A BIN, or bank identification number, is the first six to eight digits of a payment card number. These digits serve as an identifier for the issuing institution, enabling the processing network to route a transaction to the correct bank and facilitate the BIN lookup process.

BINs are used across the global payments ecosystem. Card networks, merchant acquirers, payment processors, fraud detection platforms, and financial institutions use BINs. They are a foundational component of the infrastructure that makes real-time, borderless digital payments possible.

With BIN data, systems can determine:

• Card type (debit/credit/prepaid)

• Card brand (Visa, Mastercard, etc.)

• Issuing bank

• Country of issuance

• Whether the card is corporate or personal

For businesses, this information is useful when building rules for risk assessment, geolocation verification, credit card surcharges, and checkout flows.

Structure of a BIN

A typical BIN includes a Major Industry Identifier (MII), Issuer Identifier Number (IIN), account number, and check digit.

• Digit 1: This is the Major Industry Identifier (MII). It indicates the industry of the card issuer, like airlines, travel, BFSI, and others. For example, the number 4 usually denotes banking and financial services.

• Digits 2–6 (or 2–8): These digits represent the IIN, and identify the issuing institution, enabling the network to route transactions appropriately.

• Account number: These digits typically identify the individual account.

• Last digit (the check digit): This is used to verify the card number's authenticity via the Luhn algorithm, a checksum formula that helps detect errors in card entry or card number fabrication.

BINs are issued by payment networks such as Visa, Mastercard, Discover, American Express, and regional networks like RuPay (India) or JCB (Japan). These networks assign BIN ranges to licensed issuing banks or financial institutions. To learn more about card networks and how they function, check out our article here.

Role of BINs in payment processing

BINs come into play early in the transaction lifecycle. A typical card-based payment involves steps like payment initiation, payment authentication, and then authorization by the issuing bank. The transaction is then cleared and proceeds to settlement. To learn more about card payment processing, feel free to check out our article here. Here is how BINs are involved within the cycle.

• Customer initiates a transaction via card, and the merchant’s system sends data to the acquiring bank or payment gateway.

• The acquirer forwards the transaction to the card network (e.g., Visa).

• The card network uses the BIN to identify the issuing bank.

• The issuer authenticates the transaction (e.g., by checking balance, fraud parameters).

• The result (approved/declined) is routed back along the same chain.

The BIN is central to this workflow. Without accurate BIN recognition, transactions could be misrouted, fail, or expose merchants to higher fraud risk.

BIN usage in fraud prevention

Fraud detection systems heavily rely on BIN intelligence to identify risky transactions. Examples include:

• Geolocation mismatch - If the card’s issuing country (based on BIN) differs from the device or IP location, it could flag the transaction as suspicious.

• Velocity rules - Monitor transaction frequency for a particular BIN or card. An unusually high frequency can signal card testing or bot activity.

• BIN blacklisting - Fraud systems may block or flag transactions from BINs associated with chargebacks or fraudulent activity.

• Card testing detection - Fraudsters often use low-value transactions to test stolen card details. BIN filtering allows systems to detect and cut off the pattern early.

BIN-level data aids merchants to preemptively block high-risk transactions and dynamically adjust fraud thresholds. To learn more about different methods to manage credit card risk, check out our article here.

BINs in disputes and chargebacks

A chargeback is a reversal of a transaction initiated by the cardholder, often due to fraud, product issues, or service disputes.

Understanding the chargeback process:

• The customer disputes a charge with their bank.

• The issuing bank reviews the complaint and may reach out to the merchant for further information, raising a request.

• The merchant is asked to provide evidence to counter the claim.

• If evidence fails, the dispute formally escalates to a chargeback, and the merchant is debited.

BINs come into play during the initial verification. By cross-checking the issuer details, transaction metadata, and customer claims, processors can:

• Detect potential first-party fraud (friendly fraud).

• Confirm mismatches between claimed card origin and merchant data.

• Assess risk levels based on known issuer behaviors.

The BIN supports early warning systems and strengthens dispute management workflows.

BINs in merchant operations

For merchants, BINs offer utility in back-end payment operations. BIN data can optimize cost routing, as some processors offer lower rates depending on the issuer and card type. They also support fraud prevention measures by flagging risky or mismatched inputs, such as discrepancies between a card’s issuing region and customer location, and also preempt fraud through BIN-level blocking. During disputes, BIN insights aid in verifying issuer-level details and can help businesses respond more effectively and refine risk controls.

Conclusion

BINs are foundational to how payments are initiated, routed, approved, and safeguarded. For payment professionals and merchants alike, a working knowledge of BIN structures and signals can enable smarter fraud management, checkout flows, and better resolution strategies. They act as a first line of contextual insight, allowing merchants to interpret payment behavior before deeper analytics kick in. A strong understanding of BINs can help businesses improve routing, manage risk, and provide insights into transaction data.