Data Harmonization

Your

Processor

Speak

Different

Languages

Pagos Translates

Pagos Translates

All of Them

Payments data harmonization converts fragmented transaction records across every processor into one standardized, aggregated data stream.

  • approved

  • decline

  • do_not_honor

  • chase_bank

THE SOLUTION

Same Thing,

Same Thing,

Different Name

Every processor records transactions in its own schema, using different field names, decline code taxonomies, fee labels, and metric calculations. This breaks cross-processor analysis and makes side-by-side comparisons impossible.

Decline Code

Stripe →

"do_not_honor"

Adyen →

"Refused (05)"

Same response, different labels

Issuing Bank Name

PSP A →

"JPMORGAN CHASE BK NA"

PSP B →

"Chase Bank"

Same bank, different formatting

Approval Rate Definition

Braintree →

approvals / attempts

Adyen →

approvals/(attempts − retries)

Same metric, different calculations

MECHANICS

How Pagos

How Pagos

Harmonization Works

Harmonization Works

Three steps, each building on the previous, so you can always trust your downstream analysis.

  1. Consolidate

  1. Consolidate

Pull raw transaction data from every processor, gateway, and acquirer into one centralized ingestion layer via API, SFTP, webhook, or direct connection. No processor left out, no settlement file uploaded manually.

Pull raw transaction data from every processor, gateway, and acquirer into one centralized ingestion layer via API, SFTP, webhook, or direct connection. No processor left out, no settlement file uploaded manually.

Data Connections

Add Data Connection

Processor

Chase Integration

Chase

Connection Type

Batch

Created date

17 May, 2025

Adyen US Market

Adyen

Connection Type

Batch

Created date

17 May, 2025

Charts / Transaction Count By Processor and Transaction Status Across Time

Transaction Count

Processor

Accros Time

Add Filter

Declined

47,158

Authorized

47,158

Generic

63 845

17 May

63 845

Transaction Count by Processor and Transaction Status Across Time

The total number of attempted Transactions across time when split by Processor and Transaction Status

324,848

80,000

60,000

40,000

  1. Normalize

  1. Normalize

Map every processor-specific field name, value, and schema to a single canonical data model. Transaction status, decline codes, fee types, issuer names, and timestamps all resolved to one consistent definition across every source.

Map every processor-specific field name, value, and schema to a single canonical data model. Transaction status, decline codes, fee types, issuer names, and timestamps all resolved to one consistent definition across every source.

  1. Enrich

  1. Enrich

Augment each normalized record with BIN-level intelligence, including card type, product tier, issuing bank (standardized), country of issue, network, and tokenization status, plus benchmarking signals from the Pagos merchant network.

Augment each normalized record with BIN-level intelligence, including card type, product tier, issuing bank (standardized), country of issue, network, and tokenization status, plus benchmarking signals from the Pagos merchant network.

{
"number": {

"length": 16

},

"bin_length": 6,

"bin_min": "4147200000000000000",

"bin_max": "4147209999999999999",

"pan_or_token": "pan",

"virtual_card": null,

"level2": false,

"level3": false,

"alm": true,

"account_updater": true,

"domestic_only": false,

"gambling_blocked": false,

"issuer_currency": "USD",


see more…

ACTION

Taking Action

with Harmonized Data

with Harmonized Data

Harmonized data is the foundation of payments optimization.

Approval Rate by Processor and Card Type Across Time

The percentage of transactions that are successful across time when split by Processor and Card Type

75.41

%

0%25%50%75%100%18 May19 May20 May21 May22 May23 May
19 May78.31%
Generic
78.31%
Credit
83.34%
Debit
82.73%
Prepaid
82.34%
Non-card
80.35%
Unknown
69.16%

Cross-Processor Benchmarking

Compare approval rates across all processors using identical definitions to identify which one performs best by card type, region, or corridor.

Fees Category Costs

The categories that compose your total fees.

Total Fees

$

138,395.99

USD

62.56% / $86,580.53 Interchange
33.50% / $46,362.66 Processor
3.79% / $5,245.21 Assessments
0.15% / $207.59 Unknown
$0$35k$70k$105k$140kAprMayJun
Apr
Processor
$46,362.66
Unknown
$207.59
Interchange
$86,580.53
Assessments
$5,245.21

Interchange Cost Reduction

Interchange is 70–90% of processing costs. Route transactions to the processor with the most favorable interchange rates.

Pagos AI Analyzing your payment data…

Recommended Routing Rules (Ready to Implement)

Condition

Route to

Expected Lift

Any EU Country

European acquirer

≈+20pp

Scheme:
Visa + Card Type = Debit

Processor with strong Visa Debit

≈+13pp

Issuer Country = Brazil

Local acquirer (Clelo/Rede)

≈ +8pp est.

Once you add everything to your stack, share the data and I can rerun this analysis to compare actual cross-processor performance and validate which rules are delivering lift.

Intelligent Routing

Build routing rules from actual cross-processor data. Route by card type, geography, or issuer to the processor with the best performance profile.

Decline Code

Refer to the Issuer

38,022

CVV Failure

9,421

Account Closed

8,229

Invalid Transaction

2,005

Pick Up Card

4,473

Invalid Account Number

3,945

Fraud Lost Card

3,184

Do Not Honor

1,873

Update Payment Information

1,089

Decline Analysis

Use standardized decline codes to identify systemic patterns. Spot when specific issuers, card types, or segments are declined at rates that warrant action.

Chargebacks

Processor

Chargeback Rate

3.02

%

78.43%

vs previous period

Chargeback Count

22,239

20,919

vs previous period

Chargeback Value

$

421,611.64

$395.34K

vs previous period

0%0.75%1.50%2.25%3.00%AprMayJun
Apr
Chargeback Rate
3.00%

Issuer Behavior Analysis

With standardized bank names and BIN data, analyze authorization rates, chargeback patterns, and fees by issuing bank across all processors at once.

Opportunities

Total Estimated Opportunity

$

32,432.00

USD

17.33% / $5,620.47 Debit Routing
80.64% / $26,153.16 Enhanced Data
2.03% / $658.37 Network Tokenization

Enhanced Data

$

86,633.00

USD

$26,789 Eligible Volume

Network Tokenization

$

2,180.00

USD

$2,684,600.47 Eligible Volume

Debit Routing

$

18,615.00

$10,159,000.22 Eligible Volume

Approval Rate

The percentage of transactions that are successful

Reconciliation Automation

Replace manual multi-file reconciliation with one standardized data feed. Settlement files from all processors arrive in a consistent format.

New Anomaly

-2.4% Change in Approval Rates for EUR transactions with Processor 1 detected over the last 7 days.

Dismiss

New Anomaly

Real-Time Anomaly Detection

Monitor authorization rates, chargeback velocity, and cost metrics across all processors in real time, and detect degradations.

Approvals

Processor

Approval Rate

68

%

2,03%

vs previous period

Approved Transaction

11,528,018

59,542

vs previous period

Approved Value

$

1,383,612.64

$9,91m

vs previous period

Approval Rate

The percentage of transactions that are successful

0%25%50%75%100%21 Aug25 Aug29 Aug2 Sep6 Sep10 Sep14 Sep17 Sep
10 Sep
Approval Rate
72.00%

Industry Benchmarking

Compare your performance against anonymized benchmarks from merchants in the same vertical. Know whether a number is good, not just that it moved.

AI READY DATA

AI READY DATA

Harmonization: The Prerequisite for

Harmonization: The Prerequisite for

AI Analysis

AI models require clean, standardized data to produce accurate answers. Unharmonized payments data produces confidently wrong results. Pagos cleans and harmonizes your data, so our AI delivers analyses you trust.

AI models require clean, standardized data to produce accurate answers. Unharmonized payments data produces confidently wrong results. Pagos cleans and harmonizes your data, so our AI delivers analyses you trust.

Pagos AI

Pagos MCP:

Connect Pagos MCP to Gemini
Connect Pagos MCP to Gemini
Connect Pagos MCP to Claude

What decline codes drove the spike in failures on May 15th?

What are my top dispute reasons this quarter, broken down by processor?

Which issuing bank has the lowest authorization rate for Visa debit in the US?

How do my cross-border fees compare across Stripe and Adyen this month?

Hello, I'm here to help make sense of your payments data…

WHY PAGOS

Built For

AI

AI

Pagos connects to your processors, normalizes every transaction event, and delivers a clean data stream your team—and AI—can use.

$1.2T+

in transaction volume processed across the platform

27B+

transaction events harmonized and optimized for customers

12+

processors connected natively — no custom integration required

5

continents covered with consistent data standards

Companies of all sizes trust Pagos for payments expertise

  • gofundme
  • mintmobile
  • eventbrite
  • crocs
  • Adobe
  • BasisTheory
  • ppro
  • Wix Company
  • Ravelin
  • Sardine

FAQ

See your Payment Data as one

See your Payment
Data as one

Unified Stream

Pagos connects to your processors, harmonizes every transaction event, and delivers a clean data feed your team can act on.