Make Case

Performing a report search with AML Watcher is both intuitive and highly adaptable. It all starts with the core filter: the Name. From there, you have the flexibility to enrich your search by layering on additional filters, including Countries, Categories, Birth/Incorporation Date, Unique Identifier, and Match Score. These filters offer extensive customization, allowing you to fine-tune your search criteria precisely to your needs. What's more, these filters are fully combinable, giving you the power to refine your search with pinpoint accuracy. By default, no filters are applied, ensuring that you have the freedom to tailor your AML search process exactly as you require.

Endpoint: https://api.amlwatcher.com/api/search

Method: POST

HTTP

Sample Request

POST /api/search HTTP/1.1
Host: api.amlwatcher.com
Authorization: Bearer Token
Content-Type: application/json
Content-Length: 573

{
    "name": "Kim Campbell",
    "birth_incorporation_date": "",
    "categories": [],
    "unique_identifier": "",
    "countries": [],
    "entity_type": [],
    "fuzziness": 100,
    "exact_search": true,
    "match_score": 100,
    "alias_search": "false",
    "rca_search": "false",
    "ongoing_monitoring": "false",
    "biometric_search_image": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAACOoAAAL4CAYAAADP1oqyAAAMP2...",
    "api_key": "Your Generated API Key",
    "client_reference": "Jh88XGyN58X7EQ6BSquzeTfs",
    "risk_score_engine_id": "65c3885cce288c0363bcfd4f",
    "per_page": 15,
    "webhook": "Provide webhook for Adverse Media"
}

Javascript

Sample Request

var myHeaders = new Headers();
myHeaders.append("Authorization", "Bearer Token");
myHeaders.append("Content-Type", "application/json");

var raw = JSON.stringify({
  name: "",
  categories: [],
  countries: [],
  birth_incorporation_date: "",
  unique_identifier: "",
  alias_search: true,
  rca_search: true,
  ongoing_monitoring: false,
  biometric_search_image: "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAACOoAAAL4CAYAAADP1oqyAAAMP2...",
  entity_type: ["Person"],
  api_key: "Your Generated API Key", 
  client_reference: "Jh88XGyN58X7EQ6BSquzeTfs",
  risk_score_engine_id: "65c3885cce288c0363bcfd4f",
  per_page: 15,
  match_score: 75,
  webhook: "Provide webhook for Adverse Media"
});

var requestOptions = {
  method: "POST",
  headers: myHeaders,
  body: raw,
  redirect: "follow",
};

fetch("https://api.amlwatcher.com/api/search", requestOptions)
  .then((response) => response.text())
  .then((result) => console.log(result))
  .catch((error) => console.log("error", error));

PHP

Sample Request

<?php

$curl = curl_init();

curl_setopt_array($curl, array(
  CURLOPT_URL => 'https://api.amlwatcher.com/api/search',
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => '',
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 0,
  CURLOPT_FOLLOWLOCATION => true,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => 'POST',
  CURLOPT_POSTFIELDS =>'{
    "name": "",
    "categories": [],
    "countries": [],
    "birth_incorporation_date": "",
    "unique_identifier":"",
    "alias_search": true,
    "rca_search": true,
    "ongoing_monitoring": false,
    "biometric_search_image": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAACOoAAAL4CAYAAADP1oqyAAAMP2...",
    "entity_type": ["Person"],
    "api_key": "Your Generated API Key",
    "client_reference": "Jh88XGyN58X7EQ6BSquzeTfs",
    "risk_score_engine_id": "65c3885cce288c0363bcfd4f",
    "per_page":15,
    "match_score":75,
    "webhook": "Provide webhook for Adverse Media"
}',
  CURLOPT_HTTPHEADER => array(
    'Content-Type: application/json'
  ),
));

$response = curl_exec($curl);

curl_close($curl);
echo $response;

Python

Sample Request

import requests
import json

url = "https://api.amlwatcher.com/api/search"

payload = json.dumps({
  "name": "",
  "categories": [],
  "countries": [],
  "birth_incorporation_date": "",
  "unique_identifier": "",
  "alias_search": True,
  "rca_search": True,
  "ongoing_monitoring": False,
  "biometric_search_image": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAACOoAAAL4CAYAAADP1oqyAAAMP2...",
  "entity_type": ["Person"],
  "api_key": "Your Generated API Key",
  "client_reference": "Jh88XGyN58X7EQ6BSquzeTfs",
  "risk_score_engine_id": "65c3885cce288c0363bcfd4f",
  "per_page": 15,
  "match_score": 75,
  "webhook": "Provide webhook for Adverse Media"
})
headers = {
  'Authorization': 'Bearer Token',
  'Content-Type': 'application/json'
}

response = requests.request("POST", url, headers=headers, data=payload)

print(response.text)

Ruby

Sample Request

require "uri"
require "json"
require "net/http"

url = URI("https://api.amlwatcher.com/api/search")

https = Net::HTTP.new(url.host, url.port)
https.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Content-Type"] = "application/json"
request.body = JSON.dump({
  "name": "",
  "categories": [],
  "countries": [],
  "birth_incorporation_date": "",
  "unique_identifier": "",
  "alias_search": true,
  "rca_search": true,
  "ongoing_monitoring": false,
  "biometric_search_image": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAACOoAAAL4CAYAAADP1oqyAAAMP2...",
  "entity_type": ["Person"],
  "api_key": "Your Generated API Key",
  "client_reference": "Jh88XGyN58X7EQ6BSquzeTfs",
  "risk_score_engine_id": "65c3885cce288c0363bcfd4f",
  "per_page": 15,
  "match_score": 75,
  "webhook": "Provide webhook for Adverse Media"
})

response = https.request(request)
puts response.read_body

Java

Sample Request

import java.io.DataOutputStream;
import java.io.BufferedReader;
import java.io.InputStreamReader;
import java.net.HttpURLConnection;
import java.net.URL;

public class Main {
    public static void main(String[] args) {
        HttpURLConnection connection = null;
        DataOutputStream outputStream = null;

        try {
            // Define the URL
            URL url = new URL("https://api.amlwatcher.com/api/search");

            // Open a connection to the URL
            connection = (HttpURLConnection) url.openConnection();

            // Set the request method to POST
            connection.setRequestMethod("POST");

            // Set the request headers
            connection.setRequestProperty("Content-Type", "application/json");
            connection.setRequestProperty("Authorization", "Bearer Token");

            // Enable input/output streams
            connection.setDoOutput(true);

            // Define the JSON request body
            String jsonPayload = "{\n" +
                "    \"name\": \"\",\n" +
                "    \"categories\": [],\n" +
                "    \"countries\": [],\n" +
                "    \"birth_incorporation_date\": \"\",\n" +
                "    \"unique_identifier\":\"\",\n" +
                "    \"alias_search\": true,\n" +
                "    \"rca_search\": true,\n" +
                "    \"ongoing_monitoring\": false,\n" +
                "    \"biometric_search_image\": \"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAACOoAAAL4CAYAAADP1oqyAAAMP2...\",\n" +
                "    \"entity_type\": [\"Person\"],\n" +
                "    \"api_key\": \"Your Generated API Key\",\n" +
                "    \"client_reference\": \"Jh88XGyN58X7EQ6BSquzeTfs\",\n" +
                "    \"risk_score_engine_id\": \"65c3885cce288c0363bcfd4f\",\n" +
                "    \"per_page\": 15,\n" +
                "    \"match_score\": 75,\n" +
                "    \"webhook\": \"Provide webhook for Adverse Media\"\n" +
                "}";

            // Write the JSON request body
            outputStream = new DataOutputStream(connection.getOutputStream());
            outputStream.writeBytes(jsonPayload);
            outputStream.flush();

            // Get the response code
            int responseCode = connection.getResponseCode();
            System.out.println("Response Code: " + responseCode);

            BufferedReader in;
                if (responseCode >= 200 && responseCode < 300) {
                    in = new BufferedReader(new InputStreamReader(connection.getInputStream()));
                } else {
                    in = new BufferedReader(new InputStreamReader(connection.getErrorStream()));
                }

                String inputLine;
                StringBuilder response = new StringBuilder();
                while ((inputLine = in.readLine()) != null) {
                    response.append(inputLine);
                }
                in.close();

                System.out.println("Response: " + response.toString());

                connection.disconnect();

            } catch (Exception e) {
                e.printStackTrace();
            }
        }
    }

cURL

Sample Request

curl --location --request POST 'https://api.amlwatcher.com/api/search' 
--header 'Content-Type: application/json' 
--data '{
    "name": "",
    "categories": [],
    "countries": [],
    "birth_incorporation_date": "",
    "unique_identifier":"",
    "alias_search": true,
    "rca_search": true,
    "ongoing_monitoring": false,
    "biometric_search_image": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAACOoAAAL4CAYAAADP1oqyAAAMP2...",
    "entity_type": ["Person"],
    "api_key": "Your Generated API Key",
    "client_reference": "Jh88XGyN58X7EQ6BSquzeTfs",
    "risk_score_engine_id": "65c3885cce288c0363bcfd4f",
    "per_page":15,
    "match_score":75,
    "webhook": "Provide webhook for adverse media"
}'

C#

Sample Request

using RestSharp; 
using System;
using System.Threading.Tasks;

class Program
{
    static async Task Main(string[] args)
    {
        var options = new RestClientOptions("https://api.amlwatcher.com")
        {
            ThrowOnAnyError = true,
            Timeout = TimeSpan.FromMilliseconds(-1),
        };
        var client = new RestClient(options);

        var request = new RestRequest("/api/search", Method.Post);
        request.AddHeader("Content-Type", "application/json");

        var body = new
        {
            name = "",
            categories = new string[] { },
            countries = new string[] { },
            birth_incorporation_date = "",
            unique_identifier = "",
            alias_search = true,
            rca_search = true,
            ongoing_monitoring = false,
            biometric_search_image = "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAACOoAAAL4CAYAAADP1oqyAAAMP2...",
            entity_type = new string[] { "Person" },
            api_key = "Your Generated API Key",
            client_reference = "Jh88XGyN58X7EQ6BSquzeTfs",
            risk_score_engine_id = "65c3885cce288c0363bcfd4f",
            per_page = 15,
            match_score = 75,
            webhook = "Provide webhook for Adverse Media"
        };

        request.AddJsonBody(body);

        RestResponse response = await client.ExecuteAsync(request);
        Console.WriteLine(response.Content);
    }
}

Go

Sample Request

package main

import (
  "fmt"
  "strings"
  "net/http"
  "io/ioutil"
)

func main() {

  url := "https://api.amlwatcher.com/api/search"
  method := "POST"

  payload := strings.NewReader(`{
    "name": "",
    "categories": [],
    "countries": [],
    "birth_incorporation_date": "",
    "unique_identifier":"",
    "alias_search": true,
    "rca_search": true,
    "ongoing_monitoring": false,
    "biometric_search_image": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAACOoAAAL4CAYAAADP1oqyAAAMP2...",
    "entity_type": ["Person"],
    "api_key": "Your Generated API Key",
    "client_reference": "Jh88XGyN58X7EQ6BSquzeTfs",
    "risk_score_engine_id": "65c3885cce288c0363bcfd4f",
    "per_page":15,
    "match_score":75,
    "webhook": "Provide webhook for Adverse Media"
}`)

  client := &http.Client {
  }
  req, err := http.NewRequest(method, url, payload)

  if err != nil {
    fmt.Println(err)
    return
  }
  req.Header.Add("Content-Type", "application/json")

  res, err := client.Do(req)
  if err != nil {
    fmt.Println(err)
    return
  }
  defer res.Body.Close()

  body, err := ioutil.ReadAll(res.Body)
  if err != nil {
    fmt.Println(err)
    return
  }
  fmt.Println(string(body))
}

Request

Parameters	Required	Type	Description
name	Yes	String	The name of entity/business you want to search. Min: 2 character Max: 100 characters Constraint: Name should not consist entirely of special characters or numbers.
countries	No	Array	Array of countries based on which you want to filters reports. See Countries. Note: ISO 3166-1 alpha-2 country codes are supported. Example: ["CA", "IN"]
categories	Yes	Array	Array of categories based on which you want to filters reports. See Categories. Example: ["Adverse Media", "SIP"]
birth_incorporation_date	No	String	Date(DD-MM-YYYY) based on which you want to filters reports. Note: To perform year search you can use the format 00-00-1947 and vice versa for date, month or combination of the three. Example: 10-03-1947 | 10-03-0000 | 00-03-1947 | 00-00-1947
unique_identifier	No	String	Unique identifier can be used to filter the search records. Min: 2 character Max: 50 characters Constraint: Unique identifier should not consist entirely of special characters. Note: It can be any key within the data object like Passport No, National ID number. Example: TR12345677.
alias_search	No	Boolean	Alias search is used to specify whether user want to perform search within aliases or not. Note: The default value of alias_search is True. Example: True.
rca_search	No	Boolean	RCA search is used to specify whether user want to perform search within rca or not. Description: RCA (Relatives and Close Associates) - Immediate family members or close social or professional contacts of a government or political official, or senior executive – meaning spouses, parents, siblings, children, and spouses’ parents and siblings. Note: The default value of rca_search is True. Example: True.
ongoing_monitoring	No	Boolean	Ongoing monitoring is used to monitor the cases for Ongoing AML. Note: The default value of ongoing_monitoring is False. Example: True. Disclaimer: Please note that any adverse media retrieved through our API is provided as-is at the time of request, and we do not offer continuous updates or ongoing monitoring of adverse media screening.
biometric_search_image	No	Base64 encoded	Biometric AML Screening: AML Watcher's innovative screening matrix features Name + Image + DOB + Unique Identifier which facilitates precise matching. Biometric AML serves the purpose of reducing the manual effort of MLROs and compliance officers by minimizing false positives as well as false negatives with image based search filtration. Note: Image size should not be grater than 5MBs. Only JPG and PNG image types are accepted.
entity_type	No	Array	Entity Type: AML screening serves the purpose of identifying individuals or entities listed in various AML databases. AML Watcher provides screening services of five types of entities i.e. Person, Company, Organization, Crypto_Wallet, Vessel and Aircraft. Example: ["Person"].
match_score	No	String	Match score indicates the extent to which a search should accommodate variances between the search term and the terms being matched. A value of 0 signifies a loose match, while 100 indicates an exact match. Note: It ranges from 0-100. By default value is 80 Example: 65
api_key	Optional	String	An API key is required to perform search, only if access token is not passed in authorization header as a bearer token.
per_page	Optional	Integer/String	The option to specify the number of results per page is not mandatory; it is up to the user to decide how many they want to retrieve in a single request.
client_reference	No	String	A unique client reference can be assigned to each search.
risk_score_engine_id	No	String	A risk score engine id should be used while making case.
webhook	Required	String	A webhook is required to perform search when Adverse Media category is selected, All adverse media response will be sent on the provided webhook after processing.

Response

Parameters	Description
error	Whenever there is an error in your request, this param will have details of that error; otherwise it’ll remain empty.
status	The status field is set to either “SUCCESS” or “FAIL”, indicating that the API request resulted in a successful or failure/error condition respectively.
data	An array containing the actual response elements.

Sample Response

{
    "data": {
        "adverse_media_status": "PENDING",
        "client_reference": "",
        "match_status": "Potential Match",
        "pagination": {
            "current_page": 1,
            "records_per_page": 160,
            "total_pages": 1,
            "total_records": 20
        },
        "results": [
            {
                "birth_incorporation_date": [
                    "1947-03-10"
                ],
                "categories": [
                    "Businessperson",
                    "SIP",
                    "PEP"
                ],
                "countries": [
                    "International",
                    "Canada"
                ],
                "data": {
                    "additional_information": {
                        "twitter_handle": [
                            "akimcampbell"
                        ]
                    },
                    "identification_documents": [],
                    "legal_notice": [
                        "The information contained in this report is derived from public sources such as Official Government Websites, Global Watchlists, Compliance Reports, Published Research Articles and News Sources. AML Watcher® is not the source of the data and is not responsible for the content of third party sources. AML Watcher® does not determine any positive or negative risks associated with the profiled entity. These decisions are solely determined by our clients as mandated by their applicable regulatory obligations."
                    ],
                    "linked_entities": [
                        {
                            "description": [
                                "spouse"
                            ],
                            "details": [
                                "Canadian actor, playwright, and pianist"
                            ],
                            "entity_name": [
                                "Hershey Felder"
                            ]
                        },
                        {
                            "description": [
                                "spouse"
                            ],
                            "details": [
                                "Canadian mathematician, chess master, chess writer, chess official (1925-2012)"
                            ],
                            "entity_name": [
                                "Nathan Divinsky"
                            ]
                        }
                    ],
                    "sanction_details": [],
                    "summary": {
                        "address": [],
                        "alias": [
                            "Kim Campbellová",
                            "Avril Phaedra Douglas Campbell",
                            "Кэмпбелл, Ким",
                            "Avril Phædra Douglas Campbell",
                            "کیم کمپبل",
                            "კიმ კემპბელი",
                            "キム・キャンベル",
                            "金·坎贝尔",
                            "Кім Кэмпбел",
                            "킴 캠벨",
                            "Ким Кембъл",
                            "Κιμ Κάμπελ",
                            "کم کیمبل",
                            "किम क्याम्पबेल",
                            "كيم كامبل",
                            "Kim Campbell",
                            "קים קמפבל",
                            "Քիմ Քեմփբել",
                            "Ким Кэмпбелл",
                            "Кім Кемпбелл",
                            "Ким Кэмбелл",
                            "Ким Кембел",
                            "Kim Kempbel"
                        ],
                        "category": [
                            "PEP"
                        ],
                        "country": [
                            "Canada"
                        ],
                        "date_of_birth": [
                            "1947-03-10"
                        ],
                        "date_of_death": [],
                        "description": [],
                        "designation": [],
                        "education": [
                            "Prince of Wales Secondary School",
                            "Peter A. Allard School of Law",
                            "University of British Columbia",
                            "The Royal Conservatory of Music",
                            "London School of Economics and Political Science"
                        ],
                        "email": [],
                        "entity_type": [
                            "Person"
                        ],
                        "first_name": [
                            "Avril"
                        ],
                        "gender": [
                            "female"
                        ],
                        "keywords": [
                            "National government"
                        ],
                        "last_name": [
                            "Campbell"
                        ],
                        "name": [
                            "Kim Campbell"
                        ],
                        "nationality": [
                            "Canada"
                        ],
                        "net_worth": [],
                        "notes": [
                            "19th Prime Minister of Canada in 1993"
                        ],
                        "occupation": [
                            "Politician"
                        ],
                        "phone": [],
                        "place_of_birth": [
                            "Port Alberni Canada",
                            "Port Alberni"
                        ],
                        "place_of_death": [],
                        "political_party": [],
                        "position": [
                            "Prime Minister of Canada (1993-1993)",
                            "member of the House of Commons of Canada"
                        ],
                        "position_occupancies": [
                            "member of the House of Commons of Canada"
                        ],
                        "religion": [
                            "Anglican Church of Canada"
                        ],
                        "suffix": [],
                        "title": [],
                        "website": [
                            "http://www.kimcampbell.com/"
                        ]
                    }
                },
                "entity_types": [
                    "Entity",
                    "Person"
                ],
                "id": "TZVsTJNDuSkerVtLPzxyDK",
                "matched_alias": "",
                "matched_names": [
                    {
                        "matched_name": "Kim Campbell",
                        "matching_fields": {},
                        "record_id": "TZVsTJNDuSkerVtLPzxyDK",
                        "score": "100",
                        "source_ids": [
                            "431699"
                        ]
                    },
                    {
                        "matched_name": "Kim Campbell",
                        "matching_fields": {
                            "alias": false,
                            "birth_incorporation_date": true,
                            "image": false,
                            "profile_name": true
                        },
                        "record_id": "L8ayNgJBRH4FtzLfGstxLN",
                        "score": "100",
                        "source_ids": [
                            "17109391",
                            "431871"
                        ]
                    }
                ],
                "matched_rca": "",
                "name": "Kim Campbell",
                "relevance_status": {
                    "alias": false,
                    "birth_incorporation_date": false,
                    "category": true,
                    "country": false,
                    "entity_type": false,
                    "image_match": false,
                    "potential_match": false,
                    "profile_name": true,
                    "rca_name": false,
                    "unique_identifier": false
                },
                "risk_audit": {
                    "category_rules": {
                        "business": {
                            "absolute_score": 10,
                            "selected": false,
                            "weightage": 50,
                            "weighted_score": 0
                        },
                        "businessperson": {
                            "absolute_score": 10,
                            "weightage": 50,
                            "weighted_score": 5.0
                        },
                        "fitness and probity": {
                            "absolute_score": 80,
                            "selected": false,
                            "weightage": 50,
                            "weighted_score": 0
                        },
                        "insolvency": {
                            "absolute_score": 80,
                            "selected": false,
                            "weightage": 50,
                            "weighted_score": 0
                        },
                        "pep": {
                            "absolute_score": 70,
                            "weightage": 50,
                            "weighted_score": 35.0
                        },
                        "pep level 1": {
                            "absolute_score": 70,
                            "selected": false,
                            "weightage": 50,
                            "weighted_score": 0
                        },
                        "pep level 2": {
                            "absolute_score": 49,
                            "selected": false,
                            "weightage": 50,
                            "weighted_score": 0
                        },
                        "pep level 3": {
                            "absolute_score": 40,
                            "selected": false,
                            "weightage": 50,
                            "weighted_score": 0
                        },
                        "pep level 4": {
                            "absolute_score": 25,
                            "selected": false,
                            "weightage": 50,
                            "weighted_score": 0
                        },
                        "rca": {
                            "absolute_score": 49,
                            "selected": false,
                            "weightage": 50,
                            "weighted_score": 0
                        },
                        "sanctions": {
                            "absolute_score": 100,
                            "selected": false,
                            "weightage": 50,
                            "weighted_score": 0
                        },
                        "sie": {
                            "absolute_score": 90,
                            "selected": false,
                            "weightage": 50,
                            "weighted_score": 0
                        },
                        "sip": {
                            "absolute_score": 90,
                            "selected": true,
                            "weightage": 50,
                            "weighted_score": 45.0
                        },
                        "warnings and regulatory enforcement": {
                            "absolute_score": 90,
                            "selected": false,
                            "weightage": 50,
                            "weighted_score": 0
                        }
                    },
                    "country_rules": {
                        "afghanistan": {
                            "absolute_score": 75.71,
                            "selected": false,
                            "weightage": 50,
                            "weighted_score": 0
                        },
                        "albania": {
                            "absolute_score": 38.63,
                            "selected": false,
                            "weightage": 50,
                            "weighted_score": 0
                        },
                        ....
                    }
                },
                "risk_decision": "Failed",
                "risk_level": "High",
                "risk_score": 95,
                "risk_score_engine_id": "65ce1f26a74c6232ed9ce828",
                "risk_title": "AML Default Risk",
                "risk_view": {
                    "categories": {
                        "risk_level": "Medium",
                        "risk_scores": {
                            "Businessperson": 10,
                            "PEP": 70,
                            "SIP": 90
                        },
                        "score": 45.0,
                        "weightage": 50
                    },
                    "countries": {
                        "risk_level": "Medium",
                        "risk_scores": {
                            "Canada": 25.41,
                            "International": 100
                        },
                        "score": 50.0,
                        "weightage": 50
                    },
                    "crimes": {
                        "risk_level": "Low",
                        "risk_scores": {},
                        "score": 0,
                        "weightage": 0
                    },
                    "custom_list": {
                        "risk_level": "Low",
                        "risk_scores": {},
                        "score": 0,
                        "weightage": 0
                    }
                },
                "source_details": [
                    {
                        "categories": [
                            "PEP",
                            "Businessperson",
                            "SIP"
                        ],
                        "countries": [
                            "International"
                        ],
                        "description": "Pantheon is project that uses biographical data to expose patterns of human collective memory. Pantheon contains data on more than 70k biographies, which Pantheon distributes through a powerful data visualization engine centered on locations, occupations, and biographies. Pantheon’s biographical data contains information on the age, occupation, place of birth, and place of death, of historical characters with a presence in more than 15 language editions of Wikipedia. Pantheon also uses real-time data from the Wikipedia API to show the dynamics of attention received by historical characters in different Wikipedia language editions.",
                        "publisher": "Pantheon World",
                        "url": "https://pantheon.world/"
                    },
                    {
                        "categories": [
                            "PEP"
                        ],
                        "countries": [
                            "Canada"
                        ],
                        "description": "Wikidata serves as the source of much of the data related to politically exposed persons (PEPs). The Wikidata importer will also traverse family and personal relationships that are documented in the database and import relatives and close associates whereever these are stated.",
                        "publisher": "Wikidata",
                        "url": "https://www.wikidata.org/wiki/Wikidata:Main_Page"
                    }
                ]
            },
        ],
        "search_reference": "643211e2daaeadac04832eb5",
        "searched_name": "Kim Campbell",
        "total_records": 20
    },
    "error": false,
    "status": "SUCCESS"
}

Response

Parameter	Description
error	Indicates whether an error occurred during the API request. In this response, "error": false indicates that the request was successful without errors.
status	The status of the API request.
data	The main payload containing detailed information retrieved from the API.
data.adverse_media_status	The status of the adverse media check.
data.client_reference	The client reference ID for search reference.
data.match_status	The status of the match. "Potential Match" indicates that the searched case is a match.
data.pagination	Object containing pagination details.
data.pagination.current_page	The current page number of the results.
data.pagination.records_per_page	The number of records per page.
data.pagination.total_pages	The total number of pages.
data.pagination.total_records	The total number of records.
data.results	An array of result objects, each containing detailed information about the case.
data.results[].birth_incorporation_date	A string value containing the birth or incorporation date.
data.results[].categories	An array of categories associated with the entity.
data.results[].countries	An array of countries associated with the entity.
data.results[].data	An object containing additional data about the entity.
data.results[].data.additional_information	Object containing additional information such as social media handles.
data.results[].data.identification_documents	An array containing identification documents.
data.results[].data.legal_notice	An array containing legal notices related to the data.
data.results[].data.linked_entities	An array of linked entities with descriptions and details.
data.results[].data.sanction_details	An array containing details of any sanctions, which is empty in this response.
data.results[].data.summary	Object containing summary information about the entity.
data.results[].entity_types	An array containing the types of entities.
data.results[].id	The unique identifier for the entity.
data.results[].matched_alias	The matched alias.
data.results[].matched_names	An array containing matched names and their details.
data.results[].matched_rca	An array of matched relatives and close associates (RCA).
data.results[].name	The name of the entity.
data.results[].relevance_status	Object containing the relevance status for various fields.
data.results[].risk_audit	Object containing the risk audit details.
data.results[].risk_audit.category_rules	This object contains category-specific rules and their associated scores as defined in a custom or default risk scoring engine. For instance, if a category is listed with a predefined weightage, the system checks for its presence in the response data. If found, it calculates the weighted score and sets selected key to true according to the configurations established during the setup of the custom or default risk scoring mechanism.
data.results[].risk_audit.country_rules	This object contains country-specific rules and their associated scores as defined in a custom or default risk scoring engine. For instance, if a country is listed with a predefined weightage, the system checks for its presence in the response data. If found, it calculates the weighted score and sets selected key to true according to the configurations established during the setup of the custom or default risk scoring mechanism.
data.results[].risk_decision	The risk decision for the entity.
data.results[].risk_level	The risk level for the entity.
data.results[].risk_score	The risk score for the entity.
data.results[].risk_score_engine_id	The ID of the risk score engine used.
data.results[].risk_title	The title of the risk.
data.results[].risk_view	Object containing the risk view details.
data.results[].risk_view.categories	Object containing risk view details by category.
data.results[].risk_view.countries	Object containing risk view details by country.
data.results[].risk_view.crimes	Object containing risk view details by crimes.
data.results[].risk_view.custom_list	Object containing risk view details by custom list.
data.results[].source_details	An array containing details of the sources used for the data.