Reporting

Decline code reporting

Gain clarity on why transactions fail with Cardflo's decline code reporting. Understand the specific reasons for payment rejections across your entire payment ecosystem.

This detailed insight enables targeted adjustments to improve your payment success rates and customer experience.

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Reporting
Capabilities
10
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All plans
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The overview

Decline code reporting represents the systematic categorisation and analysis of response codes returned by issuers and acquirers during the authorisation lifecycle. When a transaction is refused, the card scheme transmits a specific alphanumeric code indicating the reason for the failure.

These ranges typically distinguish between hard declines, which require no further attempt, and soft declines, which suggest a temporary issue such as insufficient funds.

Effective reporting into these codes sits at the intersection of the gateway and merchant data stack, providing a granular view of why revenue was not captured.

By isolating specific Merchant Category Code (MCC) performance or card-level response patterns, a merchant can identify whether failures stem from technical errors, suspected fraud, or genuine credit constraints.

This structural visibility allows for a more analytical approach to payment routing and retry logic, moving beyond simple binary success or failure indicators to a detailed map of scheme-level feedback.

How it works

  1. Data capture and mapping

    The system monitors the authorisation response field within the ISO 8583 message standard. As issuers return response codes, the platform captures the raw value and maps it to a standardised internal categorisation.

    This ensures that different codes from Visa, Mastercard, and various acquirers are grouped logically for consistent cross-provider analysis.

  2. Categorisation by decline type

    Responses are segmented into hard declines, such as stolen cards or invalid accounts, and soft declines, like insufficient funds or systemic timeouts.

    This distinction is critical for downstream activities, as it informs the merchant which transactions can be safely retried without violating card scheme rules regarding excessive authorisation attempts.

  3. Aggregated reporting and filtering

    The reporting interface organises data by multiple dimensions including acquirer, geographic region, and card brand.

    Merchants can filter by specific response codes, such as '05 Do Not Honour' or '51 Insufficient Funds', to visualise which failure types are disproportionately affecting specific segments of their transaction volume.

  4. Pattern recognition and alerts

    The analysis engine identifies shifts in decline distributions that may indicate technical issues or changes in issuer behaviour.

    If a specific Bank Identification Number (BIN) shows a sudden increase in refusal rates, the reporting surface highlights this anomaly, allowing for immediate investigation into potential blockages or routing misconfigurations.

Why it matters

Optimisation of retry strategies

Understanding the precise reason for a decline allows merchants to refine their dunning and retry logic.

By only retrying transactions associated with soft decline codes, such as temporary technical errors or temporary limit hits, businesses avoid the penalties and fees associated with attempting to process transactions that are destined to fail, such as those involving expired or restricted cards.

Enhanced fraud and risk visibility

Decline reporting provides an secondary layer of defence against fraud. High volumes of specific codes, such as CVV or AVS failures, across a consolidated period can indicate a card testing attack.

Monitoring these patterns allows a merchant to adjust their risk thresholds and pre-authorisation filters, reducing the operational burden on the acquirer and protecting the merchant's reputation with card schemes.

Informed payment orchestration decisions

For businesses using multiple acquirers, decline code reporting reveals which partners perform best for certain markets or transaction types.

If one acquirer consistently returns higher rates of generic declines for cross-border cards compared to others, the merchant can use this data to adjust their smart routing rules and increase the probability of initial authorisation.

Use cases

Subscription and recurring billing

Subscription firms use decline reporting to distinguish between insufficient funds and expired credentials. This allows for automated account updater triggers or scheduled retries that align with common payroll cycles, reducing involuntary churn.

Cross-border e-commerce expansion

Merchants entering new territories analyse regional decline codes to detect issuer-specific preferences. This data helps decide if local acquiring is necessary to bypass overly cautious risk filters applied to international transactions.

Platform and marketplace monitoring

Large platforms monitor decline trends across their sub-merchant base. A spike in specific response codes can indicate a technical integration error on a merchant's checkout page or a wider issue with a specific PSP gateway.

By the numbers

10-25%
Soft decline recovery range

This represents the typical industry range of revenue that can be recovered through data-driven retry strategies after an initial soft decline, depending on the merchant's sector.

40-60%
Generic response prevalence

Standard industry data shows that a significant portion of declines are often returned as generic 'Do Not Honour' codes, necessitating deeper BIN-level analysis to uncover the actual cause.

2-5%
Authorisation lift via routing

Merchants using detailed decline reporting to optimise their acquirer routing often observe an uplift in this range by avoiding providers with poor issuer reputations in certain markets.

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What you get with Decline code reporting

  • Standardise response codes across multiple acquirers and card schemes for unified reporting.
  • Distinguish between hard and soft declines to inform intelligent retry logic strategies.
  • Monitor 'Do Not Honour' response rates to identify generic refusal patterns by issuers.
  • Filter decline data by Bank Identification Number (BIN) to detect issuer-specific performance issues.
  • Track CVV and AVS failure rates to identify potential card testing or fraud.
  • Analyse the impact of 3DS authentication results on final authorisation decline codes.
  • Identify geographic regions where specific decline reasons are disproportionately high compared to peers.
  • Evaluate acquirer performance by comparing decline distributions for identical merchant category codes.
  • Export detailed decline logs to support dunning and customer service recovery efforts.
  • Visualise trends in decline codes over time to measure the effectiveness of optimisation.
See Decline code reporting on your acquiring stack.

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Questions about Decline code reporting

How does decline code reporting distinguish between a technical error and a lack of funds?

The reporting system relies on the specific response codes provided by the issuer during the authorisation process. For example, a code such as '05 Do Not Honour' is a general refusal, whereas '19' or '51' specifically indicate insufficient funds.

Technical errors, such as a timeout or a communication failure between the gateway and the scheme, are mapped to different categories.

By analysing these specific values, merchants can separate issues related to the customer's financial status from those caused by infrastructure instability or incorrect payment data.

Why should I care about the 'Do Not Honour' decline code specifically?

The '05 Do Not Honour' code is one of the most common yet least descriptive responses provided by issuers.

While it often masks insufficient funds or suspected fraud, a high volume of these declines can also suggest that the transaction appears suspicious to the issuer's risk engine. Monitoring this code allows merchants to experiment with different routing or 3DS triggers.

If a specific acquirer triggers more '05' responses than another for the same traffic, it may indicate a lack of trust between that acquirer and the issuer.

Can decline reporting help reduce the risk of merchant account termination?

Yes, indirectly. Card schemes like Visa and Mastercard monitor a merchant's decline ratio as part of their health metrics.

High rates of declines, particularly those related to fraud or invalid cards, can lead to increased monitoring or fines.

By using reporting to identify and stop attempts on cards that consistently return hard declines, or by detecting card testing attacks through CVV failure patterns, a merchant can keep their total decline ratio within the thresholds allowed by their acquirer and the card schemes.

What is the difference between a raw response code and a mapped code?

Raw response codes are the original values returned by the various financial institutions involved in a transaction. Because different banks and schemes may use different codes for the same failure reason, mapping involves translating these varied signals into a single, standardised internal nomenclature.

This allows a merchant to see a unified view of 'Expired Card' failures regardless of whether the transaction was processed via an acquirer in Europe or North America, or through different payment networks.

How frequently is decline data updated in the reporting interface?

In most modern payment environments, decline data is captured in real-time as the authorisation message returns from the network. While some advanced analytical visualisations may have a slight processing lag, the core data for any individual transaction is usually available immediately after the refusal occurs.

This allows merchants to perform near real-time troubleshooting if they notice a sudden drop in authorisation rates following a new software deployment or marketing campaign launch.

Does decline reporting include failures that happen before the authorisation request reaches the bank?

Yes, comprehensive reporting should include 'pre-authorisation' declines. These occur when the gateway or a merchant's internal risk engine blocks a transaction before it is sent to the card scheme.

Reasons might include failed CVV validation at the gateway level, blacklist hits, or geographic blocks. Distinguishing these from issuer-side declines is vital for understanding whether revenue loss is happening due to internal risk settings or external banking decisions.

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