Payment Fraud Detection - Greip API Documentation

Want to skip the docs? Use the MCP Server

Endpoint availability: Premium and aboveLearn more

{
  "data": {
    "score": 82,
    "rules": [
      {
        "id": "PF10003",
        "description": "Customer IP Address is probably VPN/Proxy/Bot/Hosting/Cloud."
      },
      {
        "id": "PF10004",
        "description": "Customer Email Address is probably invalid or spam."
      },
      {
        "id": "PF10001",
        "description": "High purchase rate, according to `customer_ip`."
      },
      {
        "id": "PF10002",
        "description": "High purchase rate, according to `customer_id`."
      },
      {
        "id": "PF10013",
        "description": "Customer device might not be a real device (according to `customer_useragent`)."
      },
      {
        "id": "PF10014",
        "description": "Customer device is registered as a high-risk device (according to `customer_useragent`)."
      }
    ],
    "rulesChecked": 21,
    "rulesDetected": 6,
    "custom_rules_applied": {
      "total": 0,
      "rules": []
    }
  },
  "status": "success",
  "executionTime": 5
}

Payment Fraud Detection

curl --request POST \
  --url https://greipapi.com/scoring/payment \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "data": {},
  "format": "<string>",
  "mode": "<string>",
  "userID": "<string>"
}
'

{
  "data": {
    "score": 82,
    "rules": [
      {
        "id": "PF10003",
        "description": "Customer IP Address is probably VPN/Proxy/Bot/Hosting/Cloud."
      },
      {
        "id": "PF10004",
        "description": "Customer Email Address is probably invalid or spam."
      },
      {
        "id": "PF10001",
        "description": "High purchase rate, according to `customer_ip`."
      },
      {
        "id": "PF10002",
        "description": "High purchase rate, according to `customer_id`."
      },
      {
        "id": "PF10013",
        "description": "Customer device might not be a real device (according to `customer_useragent`)."
      },
      {
        "id": "PF10014",
        "description": "Customer device is registered as a high-risk device (according to `customer_useragent`)."
      }
    ],
    "rulesChecked": 21,
    "rulesDetected": 6,
    "custom_rules_applied": {
      "total": 0,
      "rules": []
    }
  },
  "status": "success",
  "executionTime": 5
}

Want to skip the docs? Use the MCP Server

Endpoint availability: Premium and aboveLearn more

{
  "data": {
    "score": 82,
    "rules": [
      {
        "id": "PF10003",
        "description": "Customer IP Address is probably VPN/Proxy/Bot/Hosting/Cloud."
      },
      {
        "id": "PF10004",
        "description": "Customer Email Address is probably invalid or spam."
      },
      {
        "id": "PF10001",
        "description": "High purchase rate, according to `customer_ip`."
      },
      {
        "id": "PF10002",
        "description": "High purchase rate, according to `customer_id`."
      },
      {
        "id": "PF10013",
        "description": "Customer device might not be a real device (according to `customer_useragent`)."
      },
      {
        "id": "PF10014",
        "description": "Customer device is registered as a high-risk device (according to `customer_useragent`)."
      }
    ],
    "rulesChecked": 21,
    "rulesDetected": 6,
    "custom_rules_applied": {
      "total": 0,
      "rules": []
    }
  },
  "status": "success",
  "executionTime": 5
}

POST

scoring

payment

Payment Fraud Detection

curl --request POST \
  --url https://greipapi.com/scoring/payment \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "data": {},
  "format": "<string>",
  "mode": "<string>",
  "userID": "<string>"
}
'

{
  "data": {
    "score": 82,
    "rules": [
      {
        "id": "PF10003",
        "description": "Customer IP Address is probably VPN/Proxy/Bot/Hosting/Cloud."
      },
      {
        "id": "PF10004",
        "description": "Customer Email Address is probably invalid or spam."
      },
      {
        "id": "PF10001",
        "description": "High purchase rate, according to `customer_ip`."
      },
      {
        "id": "PF10002",
        "description": "High purchase rate, according to `customer_id`."
      },
      {
        "id": "PF10013",
        "description": "Customer device might not be a real device (according to `customer_useragent`)."
      },
      {
        "id": "PF10014",
        "description": "Customer device is registered as a high-risk device (according to `customer_useragent`)."
      }
    ],
    "rulesChecked": 21,
    "rulesDetected": 6,
    "custom_rules_applied": {
      "total": 0,
      "rules": []
    }
  },
  "status": "success",
  "executionTime": 5
}

Overview

Detecting and preventing fraudulent payments is a critical task for any business that accepts online payments. This AI-based module is designed to help you do that by analysing a range of data points related to each transaction. Using sophisticated machine learning algorithms, this method can detect and flag potentially fraudulent transactions by analysing user data, user behaviour, user device, and other factors. For example, if a transaction appears to be coming from an unusual location or device, or if the user’s behaviour is inconsistent with their past transactions, this method can flag the transaction for further review or rejection. One of the key advantages of this AI-based module is its ability to adapt and learn over time. As it analyses more data and detects more fraud, it can improve its accuracy and efficiency, making it a highly effective tool for preventing financial losses due to fraud. By implementing this method in your payment processing system, you can help protect your business and your customers from fraudulent activity, while providing a seamless and secure payment experience.

“ECOMMERCE LOSSES TO ONLINE PAYMENT FRAUD TO EXCEED $48 BILLION GLOBALLY IN 2023, AS FRAUD INCURSIONS EVOLVE”, according to a recent report by Juniper Research.

Integration Workflow

Body Parameters

data

object

required

Hide properties

action

string

The action your customer try to implement.Accepts: purchase, deposit, or withdrawal.

website_domain

string

The domain name of the website the customer trying to purchase from.Sample value: domain.com

website_name

string

The name of the website the customer trying to purchase from.Sample value: Nike Store, California

merchant_id

string|integer

If your a service provider with “sub-websites” (like Shopify), then provide a unique identification code indicating the website the customer trying to purchase from.Sample values: 12330098, 01as-aowq-029jd, or abcdefg.

shipment_id

string|integer|number

The identification code of the shipment.

transaction_id

string|integer|number

The identification code of the transaction in your system.

transaction_amount

string|number|float

The total amount of the transaction.

transaction_currency

string

The currency in which the customer pay with.Sample value: GBP

cart_items

string|integer|number

Show properties

item_id

string|number|integer

item_name

string

item_quantity

string|integer

item_quantity

integer

item_price

string|float|integer

item_category_id

string|number|integer

isDigitalProducts

boolean

Set this to true if the customer is purchasing a digital product.

coupon

string

The promo code used by the customer to complete the checkout.

customer_id

string|integer

The identification number of the customer in your system.

customer_firstname

string

The first name of the customer.

customer_lastname

string

The last name of the customer (Family Name).

customer_pob

string

The Place of Birth of the customer.

customer_ip

string

The IP address of the customer.

customer_country

string

The ISO 3166-1 alpha-2 code format of the country where the customer live. Learn more

customer_region

string

The name of the region where the customer live.

customer_city

string

The name of the city where the customer live.

customer_zip

string|integer|number

The name of the zip code of customer location.

customer_street

string

The “address line 1” of the customer.

customer_street2

string

The “address line 2” of the customer.

customer_latitude

integer|float

The customer latitude on the map (GPS Coordinates).

customer_longitude

integer|float

The customer longitude on the map (GPS Coordinates).

customer_device_id

string|integer|number

The device identification code of the customer.

customer_phone

string|integer|number

The phone number of the customer (international format).

customer_registration_date

integer

The registration date of the customer (UNIX Timestamp).

customer_balance

string|integer|float

If you offer a Wallet feature in your website, then pass the user balance to this pararmeter.

customer_dob

string

The customer’s date of birth.Sample value: ‘1985-12-27`

customer_email

string

The email address of the customer.

customer_2fa

boolean

Set this to true if the customer has 2FA enabled in his/her account.

customer_useragent

string

Pass the User Agent of the customer to this parameter.

shipping_country

string

The shipping country code of the customer (in ISO 3166-1 alpha-2 format).

shipping_region

string

The shipping region name of the customer.

shipping_city

string

The shipping city name of the customer.

shipping_zip

string|number|integer

The zip code of the customer’s shipping address.

shipping_street

string

The shipping “address 1” of the customer.

shipping_street2

string

The shipping “address 2” of the customer.

shipping_latitude

integer|number|float

The latitude of the customer’s shipping address (GPS Coordinates).

shipping_longitude

integer|number|float

The longitude of the customer’s shipping address (GPS Coordinates).

billing_country

string

The billing country code of the customer (in ISO 3166-1 alpha-2 format).

billing_region

string

The billing region name of the customer.

billing_city

string

The billing city name of the customer.

billing_zip

string|number|integer

The zip code of the customer’s billing address.

billing_street

string

The billing “address 1” of the customer.

billing_street2

string

The billing “address 2” of the customer.

billing_latitude

integer|float

The latitude of the customer’s billing address (GPS Coordinates).

billing_longitude

integer|float

The longitude of the customer’s billing address (GPS Coordinates).

payment_type

string

The payment method used to complete this transaction.Accepted values: cards, cards_mada, applepay, stcpay, bank, crypto, wallet, or cod.

card_name

string

The name on the card (Cardholder Name).

card_number

string|number|integer

The card number (min: 6 digits).

card_expiry

string

The expiry date of the customer debit/credit card.Sample value: 29/05

cvv_result

boolean

Set this to true if the customer passed the CVV/CSV verification process.

format

string

default:"JSON"

The format command is used to get a response in a specific format.Expected values: JSON, XML, CSV, or NewlineFor more information please refer to Response Format.

mode

string

default:"live"

The mode command is used to in the development stage to simulate the integration process before releasing it to the production environment.Expected values: live, or test.For more information please refer to Development Environment.

userID

string

The userID command can be used to identify requests sent by specific users to monitor in the Events Page.Expected values: email address, phone number, user id, name, etc.For more information please refer to User Identifier.

Response properties

data

object

required

Hide properties

score

float

A risk-score from 0 to 100 indicating how risky this transaction is (10.5 means it’s 10.5% risky to pass this transaction).

rules

array

required

Hide properties

string

The Id of the detected rule. (10.5 means it’s 10.5% risky to pass this transaction).Sample value: PF10003

description

string

The full description of the detected rule.Sample value: High purchase rate, according to "customer_id".

rulesChecked

integer

required

Total rules checked against the transaction.

rulesDetected

integer

required

Total rules detected in the transaction.

custom_rules_applied

object

The custom rules applied to this request, learn more.

Hide properties

total

integer

required

The total number of custom rules applied to this request.

rules

object

required

The custom rules applied to this request, learn more.

Hide properties

string

required

The rule ID as shown in the dashboard (e.g: CR104).

title

string

required

The rule title you set when creating the rule.

status

string

required

The response status.Expected values: success, or error.

executionTime

integer

required

Time spent in milliseconds to process the data.

Possible Rules

Id	Description
PF1001	High purchase rate, according to `customer_ip`.
PF1002	High purchase rate, according to `customer_id`.
PF1003	Customer IP Address is probably VPN/Proxy/Bot/Hosting/Cloud.
PF1004	Customer Email Address is probably invalid, disposable or spam.
PF1005	Customer Phone Number is probably invalid or spam.
PF1006	Customer Latitude/Longitude is invalid.
PF1007	Customer card number (BIN/IIN) is invalid.
PF1008	Customer debit/credit card issued by a brand different from the one exist in `payment_type` parameter.
PF1009	Customer country is a high-fraud country.
PF1010	Customer debit/credit card issued in a high-risk country.
PF1011	Customer is purchasing multiple times from multiple locations within the past 30 days.
PF1012	Customer debit/credit card is being used multiple times from multiple customer accounts (according to `customer_id` and `card_number`).
PF1013	Customer device might not be a real device (according to `customer_useragent`).
PF1014	Customer device is registered as a high-risk device (according to `customer_useragent`).
PF1015	AI flagged the transaction as potentially fraudulent.
PF1016	AI flagged the transaction as potentially fraudulent due to high transaction amount.
PF1017	Mismatch between billing address and IP geolocation.
PF1018	Customer has multiple fraudulent transactions in the past 30 days.
PF1019	Unusual purchase amount compared to customer’s history.
PF1020	Transaction initiated from a newly created account.
PF10021	Multiple payment cards used by a single account within a short timeframe.
PF10022	Customer IP address were found in one of your blacklists.
PF10023	Customer email address were found in one of your blacklists.
PF10024	Customer phone number were found in one of your blacklists.
PF10025	Customer card number were found in one of your blacklists.
PF10026	Customer Id were found in one of your blacklists.

Profanity Detection User Data Deletion

Documentation Index

​Overview

​Integration Workflow

​Body Parameters

​Response properties

​Possible Rules

Overview

Integration Workflow

Body Parameters

Response properties

Possible Rules