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Centsless analyzes rounding ratios, override patterns, and void rates across every transaction to generate fraud scores in real time. A merchant that consistently rounds up, applies overrides at unusual rates, or voids transactions on a suspicious schedule accumulates a higher risk score over time. These endpoints let you inspect aggregate risk for individual merchants or across your entire platform.

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Authentication

All requests require an x-api-key header with admin scope.

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GET /merchant//risk-profile — Merchant risk profile

Retrieve a comprehensive fraud risk profile for a single merchant. 
GET https://api.centsless.org/api/v1/merchant/{merchant_id}/risk-profile

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Path parameters

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merchant_id
string
required
The unique identifier of the merchant. Example: MERCHANT-001

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Code example

curl https://api.centsless.org/api/v1/merchant/MERCHANT-001/risk-profile \
  -H "x-api-key: YOUR_API_KEY"

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Response

The response includes:
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fraud_score
integer
Aggregate fraud score for the merchant. Higher values indicate greater risk.
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risk_level
string
Summary risk classification. One of: NONE, LOW, MEDIUM, HIGH, CRITICAL
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rounding_analysis
object
Breakdown of rounding behavior including round-up vs. round-down ratios and penny-ending distribution across transactions.
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override_patterns
object
Override frequency, reason code distribution, and average delta between calculated and overridden amounts.
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void_rates
object
Void rate, void count, and normalization failure rate for this merchant’s transaction history.

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GET /admin/fraud-overview — All merchants fraud overview

Returns a ranked list of all merchants by fraud risk score, with summary statistics for each. Use this to identify merchants that require investigation without needing to pull individual profiles. 
GET https://api.centsless.org/api/v1/admin/fraud-overview

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Code example

curl https://api.centsless.org/api/v1/admin/fraud-overview \
  -H "x-api-key: YOUR_API_KEY"
The response ranks all merchants from highest to lowest risk score and highlights those with suspicious rounding patterns, elevated override rates, or high void frequencies. Merchants with a risk_level of HIGH or CRITICAL are surfaced at the top of the list.