Ruting

BIN-rapportering

BIN-rapportering tilbyder omfattende analyser af transaktionsydelse segmenteret efter Bank Identification Number. Cardflo leverer detaljerede rapporter om autorisationsrater, afvisningsårsager og omkostninger forbundet med specifikke BIN'er.

Disse data gør det muligt for forretningsdrivende at identificere tendenser, optimere routingkonfigurationer og forhandle bedre vilkår med indløsere.

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Overblikket

Bank Identification Number (BIN) reporting involves the systematic analysis of the first six to eight digits of a primary account number. This segment of the card data identifies the issuing bank, the card scheme, the card type, and the country of origin.

In the payments stack, BIN reporting sits within the analytics and orchestration layer, providing granular visibility into how specific subsets of payment traffic behave across different acquirers. By segmenting transaction data by BIN, merchants can distinguish between debit, credit, prepaid, and corporate cards.

This level of detail is necessary for calculating precise interchange costs and identifying patterns in authorisation success rates. The reporting typically integrates with a merchant's gateway or payment service provider to surface data points such as decline codes and settlement times.

Understanding these variables allows for the adjustment of routing logic or the implementation of retry strategies tailored to the issuer's historical behaviour, which may reduce unnecessary friction during the checkout process.

Sådan fungerer det

  1. Data ingestion and extraction

    The system captures the BIN from the initial authorisation request. The reporting engine extracts this digit string before the card data is tokenised or encrypted for storage.

    This ensures the metadata remains available for longitudinal analysis without compromising the security requirements central to maintaining PCI-DSS compliance across the processing environment.

  2. Enrichment via BIN tables

    Raw BINs are cross-referenced against global databases to determine attributes such as issuing bank name, card product level, and geographic territory.

    This enrichment adds context to the raw transaction data, allowing for deeper segmentation beyond simple pass or fail results communicated by the acquirer during the authorisation phase.

  3. Performance metrics aggregation

    The platform aggregates performance indicators including authorisation rates, decline codes, and average transaction values for each specific BIN.

    This allows merchants to observe if certain issuers are frequently returning specific refusal reasons, such as suspected fraud or insufficient funds, which may differ from the broader portfolio average.

  4. Economic impact analysis

    Cost data is mapped to the BIN level to isolate the impact of interchange and scheme fees.

    Since corporate or premium cards often carry higher interchange rates, this step allows for an accurate assessment of the net margin associated with different customer segments and card products in real-time.

Hvorfor det betyder noget

Authorisation rate optimisation

Merchants can identify specific issuers that frequently decline transactions due to overly sensitive fraud filters or technical incompatibility with 3DS implementations.

By analysing these patterns, businesses can adjust their smart routing configurations to send traffic from these BINs through acquirers that maintain better technical relationships or higher historical success rates with those specific issuing institutions, potentially recovering revenue that would otherwise be lost to false positives.

Interchange cost management

Precise BIN reporting allows for a transparent breakdown of the interchange-plus or blended pricing models. Since different card types attract varying scheme fees and interchange rates, identifying a high volume of premium or commercial cards enables merchants to better predict their processing overheads.

This data provides the necessary evidence to negotiate more favourable merchant service charges or to adjust pricing strategies for specific international regions.

Strategic routing logic

Effective BIN analysis informs the development of routing rules that prioritise specific payment paths for high-value or high-risk cards.

For example, if transactions from a particular BIN range consistently experience delays or soft declines during peak hours, the merchant can automate a failover mechanism to a secondary gateway to maintain service levels and minimise the impact on the customer experience.

Anvendelser

Subscription and recurring billing

Identify which BINs are linked to prepaid cards that frequently fail on second-attempt dunning. Merchants can use this data to restrict certain card types from being used for recurring subscriptions to reduce involuntary churn.

Cross-border expansion analysis

Evaluate the performance of international BINs before establishing a local legal entity. This helps in determining whether current cross-border authorisation rates justify the investment in local acquiring and domestic domestic processing.

Fraud and risk mitigation

Detect clusters of fraudulent activity originating from specific BIN ranges. This allows risk teams to apply stricter 3DS requirements or manual review triggers to those specific segments while maintaining a frictionless path for trusted BINs.

Commercial card cost tracking

Monitor the volume of corporate and purchasing cards which often carry higher interchange fees. This helps B2B merchants understand how card mix impacts their bottom line and informs decisions regarding surcharging where permissible.

I tal

2-5%
Authorisation improvement

This reflects the typical uplift observed when merchants use BIN data to reroute transactions away from issuers or acquirers with documented technical incompatibilities.

10-15%
Interchange cost reduction

An industry-standard range for savings achieved by B2B merchants who identify high-cost BINs and negotiate specific domestic acquiring rates for those segments.

8-digit
Reporting granularity

The current ISO standard for BIN length, providing the necessary level of detail to distinguish between different card products within the same financial institution.

Ready to route with BIN-rapportering?

Talk to our team about a live rollout on your acquiring stack.

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Hvad du får med BIN-rapportering

  • Detaljerede autorisationsrater efter BIN
  • Analyse af afvisningsårsager pr. BIN
  • Omkostningsfordeling for BIN-specifikke transaktioner
  • Identifikation af højtydende og problematiske BIN'er
  • Dataeksportmuligheder for yderligere analyse
  • Understøttelse af strategisk håndtering af indløserrelationer
  • Longitudinal tracking of BIN performance to detect shifts in issuer risk appetites.
  • Exportable reports for reconciling acquirer statements against actual transaction card types.
  • Validation of BIN ranges for domestic versus international transaction processing configurations.
  • Detection of high-risk BINs to inform custom routing and fraud prevention rules.
See BIN-rapportering on your acquiring stack.

A short scoping call, then a written plan for your MIDs.

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Spørgsmål om BIN-rapportering

Hvilken form for indsigt kan jeg få fra BIN-rapportering?

BIN-rapportering tilbyder indsigt i, hvilke BIN'er der klarer sig bedst eller værst, almindelige afvisningsårsager for specifikke kortudstedere og omkostningskonsekvenserne ved at behandle kort fra visse regioner eller banker. Disse data informerer strategiske beslutninger.

Hvor ofte opdateres BIN-rapporteringen?

BIN-rapporteringsdata opdateres næsten i realtid, hvilket giver dig aktuel indsigt i din transaktionsydelse. Dette giver mulighed for hurtige justeringer af routingstrategier og hurtig respons på nye tendenser eller problemer, der påvirker specifikke korttyper eller udstedere.

Kan BIN-rapportering hjælpe med at reducere behandlingsgebyrer?

Ja, BIN-rapportering kan hjælpe med at reducere behandlingsgebyrer ved at fremhæve, hvilke BIN'er der medfører højere omkostninger eller har lavere autorisationsrater hos visse indløsere. Denne intelligens giver dig mulighed for at optimere routing til mere omkostningseffektive indløsere eller forhandle bedre vilkår baseret på konkrete data.

How can BIN data be used to improve authorisation rates for cross-border payments?

International transactions often suffer from higher decline rates because issuers may flag foreign acquirers as high-risk. BIN reporting identifies the country of the issuing bank, allowing the merchant to see which regions are performing poorly.

With this information, the merchant can route transactions from specific country-coded BINs to a local acquirer within that same jurisdiction.

This domestic routing frequently leads to higher authorisation rates as the transaction no longer appears as a cross-border risk to the issuing bank's fraud detection systems.

What role does BIN reporting play in managing 3-D Secure (3DS) performance?

Different issuers have varying levels of technical maturity regarding 3DS protocols, such as the transition from 3DS1 to 3DS2. BIN reporting allows merchants to track which issuers are currently failing 3DS challenges or causing high latency during the authentication process.

If a specific BIN range shows a high abandonment rate during the 3DS step, the merchant can investigate if there is a technical mismatch or if they should utilise specific SCA exemptions permitted under PSD2 for that issuer to improve the conversion rate.

Does BIN reporting require the storage of full Primary Account Numbers (PAN)?

No, effective BIN reporting does not require the storage of the full 16-digit card number. Because the BIN only comprises the first six to eight digits, it is considered non-sensitive data under many PCI-DSS interpretations, provided the remaining digits are truncated or tokenised.

This allows merchants to gain all the analytical benefits of BIN-level insights without the increased security burden and compliance risk associated with storing full cardholder data within their internal reporting databases or analytics platforms.

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