Error analysis

Error analysis in Reveal Transactions explains why payments fail—not only that they failed. Every declined transaction carries a reason from the issuer and Gateway Account path. Reveal normalizes those signals into standard error codes and charts so you can see which failures are most common and which cost the most.

To open these views, select Transactions, open Performance in the left navigation, then select the Error Distribution tab.

For how Reveal defines authorization and the difference between transactions and orders, see Understand payment performance.

What Error Distribution shows

The Error Distribution tab gives a multi-dimensional view of declines, including charts such as:

• Transaction Error Distribution — Share of failures by error reason across transactions (including retries, depending on the chart variant)
• Breakdowns you can segment with the same performance filters used on Auth Rate and Decline Rate

Instead of treating every decline as a generic failure, you can see which standard reasons dominate—for example INSUFFICIENT_FUNDS, DO_NOT_HONOR, or 3DS-related authentication failures.

Example: insufficient funds in context

A high share of Insufficient Funds errors looks simple until you ask:

1. Is the rate higher for specific Funding Types (for example prepaid)?
2. Does it spike at certain times of the month?
3. Are particular Customer Countries or segments more affected?
4. Are average amounts for that error higher or lower than other decline reasons?

Answering those questions turns a generic decline spike into a concrete checkout or messaging change.

Break down errors by context

Segment error charts the same way you drill into auth rates. Useful dimensions include:

• Funding Type
• Customer Country / geography
• Time patterns within the selected date range
• Transaction amount ranges
• 3DS Flow
• Gateway Account, Card Type, and other Performance filters

Use Drill down into auth and decline rates for the shared segmentation workflow, then return here to see which error reasons drive the weak segment.

Quantify the cost of each error

Frequency alone can mislead. A rare 3DS failure on high-value orders can cost more than a frequent low-value soft decline. Reveal's revenue-impact views on this area of Performance include:

• Average / occurrence-based impact — Typical financial value tied to each error type
• Last occurrence impact — Revenue associated with the final error before order abandonment

Those metrics are documented in Revenue impact analysis. In the UI they appear under Error Impact on Revenue, with options such as averaged impact and by: Last Occurrence.

Standard error codes in Reveal

Reveal maps processor and issuer responses to a consistent set of codes and reason strings so you can compare failure types across Gateway Accounts. Browse the full list in Standard error codes.

How to act on error insights

1. Identify the top error reasons by count on Error Distribution.
2. Switch to Revenue impact analysis to prioritize by dollars, not only frequency.
3. Segment the costly reasons (Funding Type, country, 3DS, Gateway Account).
4. Feed findings into retry strategy (Retry analysis and order recovery), routing rules, or customer messaging at the point of decline.
5. Monitor whether authorization rates improve after the change.