PEP Match

Endpoint Overview

POST /api/v1/pep/match

Description

The PEP Match API allows you to verify if an individual is a Politically Exposed Person (PEP) by matching their personal details against a comprehensive database of political figures. This endpoint returns detailed information about potential matches including confidence scores, variations of names, positions held, and other biographical data to help with identity verification and compliance requirements.

Key Benefits

Comprehensive PEP screening with confidence scoring to assess match accuracy

Multiple match results with detailed biographical information for thorough verification

Support for international PEP identification across different countries and jurisdictions

Helps organizations meet regulatory compliance requirements for KYC and AML procedures

Use Cases

Financial Services

Corporate Compliance

Government & Public Sector

Enhanced due diligence during customer onboarding processes

Periodic rescreening of existing customers for ongoing compliance

Risk assessment for high-value transactions with politically connected individuals

Technical Implementation

Authentication

All API requests require authentication using a JWT Bearer token. Authentication follows these steps:

Obtain API Credentials: Register with Surepass to receive your API key.

Generate JWT Token: Use your API key to generate a JWT token.

Include in Requests: Add the token to the Authorization header as Bearer TOKEN.

Different authentication tokens are used for sandbox and production environments:

Sandbox: https://sandbox.surepass.io

Production: https://kyc-api.surepass.io

Request Parameters

Request Headers

Header	Required	Description
Authorization	Yes	Bearer token authentication using JWT format
Content-Type	Yes	application/json

Request Body

Parameter	Type	Required	Description
name	String	Yes	Full name of the politician/individual to check
dob	String	Yes	Date of birth in "YYYY-MM-DD" format
nationality	String	Yes	Nationality of the individual
address	String	Yes	Address of the individual

Example Request

{
    "name": "narendra modi",
    "dob": "1950-09-17",
    "nationality": "indian",
    "address": "gujrat"
}

Process Response

Response Parameters

Parameter	Type	Description
data	Object	Contains the response data
data.client_id	String	Unique identifier for the PEP match request
data.name	String	The name provided in the request
data.results	Array	List of potential PEP matches
data.results[].score	Number	Confidence score of the match (0-1, where 1 is highest confidence)
data.results[].name	Array	Different variations of the individual's name
data.results[].first_name	Array	Different variations of the individual's first name
data.results[].last_name	Array	Different variations of the individual's last name
data.results[].nationality	Array	Nationality codes of the individual
data.results[].position	Array	Various positions held by the individual
data.results[].date_of_birth	Array	Birth dates in "YYYY-MM-DD" format
data.results[].country	Array	Country codes where the individual is politically active
data.results[].gender	Array	Gender of the individual
data.results[].email	Array	Email addresses associated with the individual
data.results[].notes	Array	Additional information about the individual
data.results[].birth_place	Array	Places of birth
data.results[].education	Array	Educational background details
status_code	Integer	HTTP status code of the response
success	Boolean	Indicates if the request was successful
message	String	Human-readable status message
message_code	String	Machine-readable status code

Example Successful Response

{
    "data": {
        "client_id": "pep_match_aLiCyupMfwfSKtRpjeyx",
        "name": "narendra modi",
        "results": [
            {
                "score": 0.98,
                "name": [
                    "Modi, Shri Narendra",
                    "Narendra Modi",
                    "Narendra MODI"
                ],
                "first_name": [
                    "Narendra",
                    "Damodar"
                ],
                "last_name": [
                    "Modi"
                ],
                "nationality": [
                    "in"
                ],
                "position": [
                    "Member of the 17th Lok Sabha (2019-)",
                    "Lok Sabha (member, 2014-)",
                    "Member of the Gujarat Legislative Assembly (2002-2014)",
                    "Member of the 16th Lok Sabha (2014-)",
                    "Chief Minister of Gujarat (2001-2014)",
                    "Head, Dept. of Atomic Energy",
                    "Head, Dept. of Space",
                    "Prime Minister",
                    "Minister of Personnel, Public Grievances and Pensions (2014-)",
                    "Prime minister of India (2014-)",
                    "Leader of the House in Lok Sabha (2019-)",
                    "Minister of Personnel, Public Grievances, & Pensions"
                ],
                "date_of_birth": [
                    "1950-09-17"
                ],
                "country": [
                    "in"
                ],
                "gender": [
                    "male"
                ],
                "email": [
                    "appt.pmo@gov.in"
                ],
                "notes": [
                    "14th Prime Minister of India"
                ],
                "birth_place": [
                    "Vadnagar"
                ],
                "education": [
                    "Gujarat University (-1983)",
                    "University of Delhi (-1978)"
                ]
            },
            {
                "score": 0.98,
                "name": [
                    "Narendra Modi",
                    "Modi, Shri Narendra"
                ],
                "first_name": [
                    "Narendra"
                ],
                "last_name": [
                    "Modi"
                ],
                "nationality": [
                    "in"
                ],
                "position": [
                    "Lok Sabha (member, 2014-)"
                ],
                "date_of_birth": [
                    "1950-09-17"
                ],
                "country": [
                    "in"
                ],
                "gender": [
                    "male"
                ],
                "email": [
                    "appt.pmo@gov.in"
                ],
                "notes": null,
                "birth_place": null,
                "education": null
            }
        ]
    },
    "status_code": 200,
    "success": true,
    "message": "Success",
    "message_code": "success"
}

Possible Error Responses

Authentication Error

Validation Error

{
    "status_code": 401,
    "success": false,
    "message": "Invalid or expired token",
    "message_code": "unauthorized"
}

This error occurs when the JWT token is missing, invalid, or expired.

Integration Best Practices

Security Recommendations

Store API credentials securely and never expose them in client-side code

Implement proper error handling to avoid exposing sensitive information

Use HTTPS for all API communications to ensure data encryption in transit

Implement rate limiting on your side to prevent API abuse

User Experience Guidelines

Consider implementing a confidence score threshold (e.g., 0.7+) for automatic approvals

Display multiple potential matches to users when manual review is needed

Highlight key identifying information (positions, DOB, nationality) to aid verification

Implement a clear workflow for handling potential PEP matches in your application

Code Samples

cURL

Python

Node.js

Related APIs

KYC Verification API - Verify identity documents and perform KYC checks

AML Screening API - Screen individuals against global sanctions and watchlists

Document Verification API - Verify authenticity of identity documents

Address Verification API - Verify residential and business addresses

Compliance and Legal Considerations

PEP screening is a critical component of Anti-Money Laundering (AML) and Know Your Customer (KYC) compliance programs. Many jurisdictions require enhanced due diligence for individuals identified as PEPs. This API helps organizations meet regulatory requirements under frameworks such as FATF Recommendations, EU AML Directives, and local AML regulations. Always consult with compliance and legal teams to ensure proper implementation of PEP screening in your jurisdiction.

curl --location --request POST 'https://kyc-api.surepass.app/api/v1/pep/match' \ --header 'Content-Type: application/json' \ --data-raw '{ "name": "narendra modi", "dob": "1950-09-17", "nationality": "indian", "address": "gujrat" }'

{ "data": { "client_id": "pep_match_aLiCyupMfwfSKtRpjeyx", "name": "narendra modi", "results": [ { "score": 0.98, "name": [ "Modi, Shri Narendra", "Narendra Modi", "Narendra MODI" ], "first_name": [ "Narendra", "Damodar" ], "last_name": [ "Modi" ], "nationality": [ "in" ], "position": [ "Member of the 17th Lok Sabha (2019-)", "Lok Sabha (member, 2014-)", "Member of the Gujarat Legislative Assembly (2002-2014)", "Member of the 16th Lok Sabha (2014-)", "Chief Minister of Gujarat (2001-2014)", "Head, Dept. of Atomic Energy", "Head, Dept. of Space", "Prime Minister", "Minister of Personnel, Public Grievances and Pensions (2014-)", "Prime minister of India (2014-)", "Leader of the House in Lok Sabha (2019-)", "Minister of Personnel, Public Grievances, & Pensions" ], "date_of_birth": [ "1950-09-17" ], "country": [ "in" ], "gender": [ "male" ], "email": [ "appt.pmo@gov.in" ], "notes": [ "14th Prime Minister of India" ], "birth_place": [ "Vadnagar" ], "education": [ "Gujarat University (-1983)", "University of Delhi (-1978)" ] }, { "score": 0.98, "name": [ "Narendra Modi", "Modi, Shri Narendra" ], "first_name": [ "Narendra" ], "last_name": [ "Modi" ], "nationality": [ "in" ], "position": [ "Lok Sabha (member, 2014-)" ], "date_of_birth": [ "1950-09-17" ], "country": [ "in" ], "gender": [ "male" ], "email": [ "appt.pmo@gov.in" ], "notes": null, "birth_place": null, "education": null }, { "score": 0.88, "name": [ "Narendra MODI" ], "first_name": null, "last_name": null, "nationality": null, "position": [ "Prime Min.", "Head, Dept. of Atomic Energy", "Head, Dept. of Space", "Min. of Personnel, Public Grievances, & Pensions" ], "date_of_birth": null, "country": [ "in" ], "gender": null, "email": null, "notes": null, "birth_place": null, "education": null }, { "score": 0.77, "name": [ "Jashodaben Narendrabhai Modi" ], "first_name": null, "last_name": [ "Modi" ], "nationality": [ "in" ], "position": null, "date_of_birth": [ "1952" ], "country": null, "gender": [ "female" ], "email": null, "notes": [ "Spouse of Prime Minister of India Narendra Modi" ], "birth_place": [ "Rajpur" ], "education": null }, { "score": 0.51, "name": [ "Narendra Jadhav" ], "first_name": [ "Narendra" ], "last_name": null, "nationality": [ "in" ], "position": [ "Member of Rajya Sabha (2016-2022)" ], "date_of_birth": [ "1953" ], "country": [ "in" ], "gender": [ "male" ], "email": null, "notes": [ "Indian economist, educationist, and politician" ], "birth_place": [ "Nashik" ], "education": [ "University of Mumbai", "Indiana University" ] } ] }, "status_code": 200, "success": true, "message": "Success", "message_code": "success" }

Provide your bearer token in the

Authorization

header when making requests to protected resources.

Example:

Authorization: Bearer ********************

PEP Match

PEP Match#

Description#

Use Cases#

Technical Implementation#

Request Headers#

Request Body#

Example Request#

Response Parameters#

Example Successful Response#

Possible Error Responses#

Integration Best Practices#

Code Samples#

Request

Responses

PEP Match

Description

Use Cases

Technical Implementation

Request Headers

Request Body

Example Request

Response Parameters

Example Successful Response

Possible Error Responses

Integration Best Practices

Code Samples