Watchlists, Politically Exposed Persons, Adverse Media Screening

Introduction

This API can be used for 3 different screenings based on the input provided by client as mentioned below :-

a) Global Watchlists & Sanction Sceening :- Signzy's Global Watchlists & Sanction offers data from more than 6000 global source daily to alert you about potential sanction risks when screening candidates, vendors, or other business partners.

Global watchlists are compiled by governments and international organizations to identify entities linked to crime, corruption, terrorism, laundering, and various other forms of unethical behavior. Entities include individuals, corporations, or even countries. Even if they aren’t actively committing a crime, listed entities may be connected to suspicious activity. Engaging in risky business relationships with suspicious parties can result in severe regulatory penalties, financial loss, and reputational damage.

b) Politically Exposed Persons (PEP) Screening :- Signzy's Politically Exposed Persons Screening uses data from Government databases, a lot of other datasources & analyze media sources daily to uncover PEP associations not listed by governments or other common sources, looking at family members and close associates as well as the individual in question.

Politically Exposed Persons are individuals connected to high-level roles in a government, either directly, through family members, or through close personal and business relationships. PEPs are considered higher risk customers because their proximity to power offers more opportunities to engage in unethical or unlawful behavior, such as nepotism, money laundering, and embezzlement.

International AML/KYC regulations for financial services, banking, and other sectors often require ongoing monitoring of PEPs. While PEP status is not an automatic dealbreaker, it may be a sign you need to implement extra AML/CFT protocols and conduct specialized due diligence. Signzy offers an easier, more affordable solution for reducing reputational and financial risk while supporting smarter compliance decisions.

c) Adverse/Negative Media Screening :- Signzy's Adverse Media Screening uses data from public sources by crawling the web for relevant information on a daily basis, leveraging sentiment analysis and negative keywords to reduce false positives.

Adverse media detection serves as an important early predictor for potential watchlist or sanctions listings, as media outlets can often identify risk with more agility than government or international watchdogs. Red flag behavior linked to money laundering, financial fraud, drug trafficking, human trafficking, risky finances, terrorism — and more — can be better identified and predicted with adverse media screening.

Adverse Media Source Examples :- BBC, The New York Times, Al Jazeera, Washington Post, Gulf News, CNN, The Telegraph, Fox News, The World Bank, Wallstreet Journal, Mumbai Mirror, The Asian Age, The Seattle Times, Caribbean New Now, China Daily, The Indian Express, Bangkok Post, Sydney Morning Herald, Chicago Tribune, Newsroom Panama, Winnipeg Sun, and thousands more....

API Details

You must first login before sending the request. The authorization header in the request must include the access token obtained from the login API call.

Sample cURL

Production

Pre-Production

curl --location --request POST 'https://api.signzy.app/api/v3/global/pep_nm_wls' \
--header 'Authorization: <----Auth Token---->' \
--header 'Content-Type: application/json' \
--data-raw '{
    "subject": "Donald Trump",
    "subjectId": "GA94924-83",
    "categories": "ALLPP",
    "needsTranslation": false,
    "dateOfBirthFilter": false,
    "aliases": [
        "POTUS"
    ],
    "parameters": {
        "age": "56",
        "dateOfBirth": "7/3/1962",
        "free text": "keyword1; keyword2",
        "identifier": "some identifier",
        "address line 1": "123 Peachtree St",
        "city/district": "Atlanta",
        "state/province/region/locality": "GA",
        "country": "USA",
        "countryCodes": "USA,CAN",
        "postal code": "30303",
        "source country": "USA"
    },
    "options": {
        "pep": {
            "excludeFields": [
                "social",
                "business relations"
            ],
            "profileLevels": [
                1,
                2,
                3
            ]
        }
    },
    "monitoring": {
        "monitor": false
    }
}'

curl --location --request POST 'https://api-preproduction.signzy.app/api/v3/global/pep_nm_wls' \
--header 'Authorization: <----Auth Token---->' \
--header 'Content-Type: application/json' \
--data-raw '{
    "subject": "Donald Trump",
    "subjectId": "GA94924-83",
    "categories": "ALLPP",
    "needsTranslation": false,
    "dateOfBirthFilter": false,
    "aliases": [
        "POTUS"
    ],
    "parameters": {
        "age": "56",
        "dateOfBirth": "7/3/1962",
        "free text": "keyword1; keyword2",
        "identifier": "some identifier",
        "address line 1": "123 Peachtree St",
        "city/district": "Atlanta",
        "state/province/region/locality": "GA",
        "country": "USA",
        "countryCodes": "USA,CAN",
        "postal code": "30303",
        "source country": "USA"
    },
    "options": {
        "pep": {
            "excludeFields": [
                "social",
                "business relations"
            ],
            "profileLevels": [
                1,
                2,
                3
            ]
        }
    },
    "monitoring": {
        "monitor": false
    }
}'

Request Body Parameters

Parameter	Data Type	Required	Description
Content-Type		Yes	application/json
Authorization		Yes	Authorization token
subject	string	Yes	Name of individual or business.
subjectID	string	Sometimes When using with Monitoring.	This is the ID the client has assigned to the Subject used to match the response to the record in the client’s database.
needsTranslation	boolean	Optional	Whether the subject and/or aliases needs to be translated. This only translates the subject name from non-Latin characters (e.g. Chinese, Japanese, Greek, Russian) to Latin characters. Please only pass True for entries that need to be translated from nonLatin characters into Latin characters. Please do not pass True for all API calls by default, this feature will slow down your response time.
dateOfBirthFilter	boolean	Optional	When set to true, only results that match the searched DOB will be returned. Set to false, all results with namematch scores at or above the relevancy score setting will be returned. Default is false. Please note that if the result does not contain a DOB value, it will be returned regardless of the setting being true or false.
categories	string	Yes	Product category(-ies) to search. When using more than one product category separate each value with a comma or semicolon.There should be no space after each catogery while entering multiple catogeries at once. Ex: If there are two or more entries at the same then the entries should be like - ALLWL,ALLNM See Categories Section Below
aliases[]	list		List of any aliases to search.
parameters	object	Optional	Optional search criteria.
parameters.age	string	Optional	Number value entered as a text.
parameters.dateOfBirth	string	Optional	Individual's age entered as text.
parameters.free text	string	Optional	Input any keyword text you would like added to the search. Several search words or phrases should be separated by a comma or a semicolon.
parameters.identifier	string	Optional	Any values associated to the Individual or Business. For example: Passport number or Business License.
parameters.address line 1	string	Optional	In the US this value would be the Number and Street Name.
parameters.address line 2	string	Optional	In the US this value would be the Suite or PO Box.
parameters.city/district	string	Optional	City or District
parameters.state/province/region/locality	string	Optional	State, Province, Region, or Locality
parameters.country	string	Optional	Country of the searched subject.
parameters.countryCodes	string	Optional	Comma separated list of country codes expressed in ISO 3166- 1 alpha 3 format. Currently only used to filter level 1 and level 2 PEP profiles. Please note that any of the following codes will be accepted for Yugoslavia: (BIH, HRV, MKD, MNE, SRB, and RSK) – BIH will always be the displayed code in the PEP profile.
parameters.postal code	string	Optional	Postal Code
parameters.source country	string	Optional	Identifies the country where the data was captured expressed in ISO 3166-1 alpha-3 format.
options	object	Optional	Additional search options
options.pep	object	Optional	Additional search options for PEP searches
options.pep.excludeFields	list	Optional	String enumeration of fields to not return from a Pep profile. Possible values include "Professional History", "Member Of", Employer", "Education", "Awards Received", "Notable Work", "Convicted", "SourceInfoURL" "Affiliation", "Family Members", "Social", "Business Relations", "Business Partnerships", "Lobbying", "Stakeholder", and "Contributions". Please note an error will not occur for any provided value not in our list of acceptable values
options.pep.profileLevels	list	Optional	Numeric value indicating what pep profile levels to search. Possible values are 1,2,3. 1 – Profile Name 2 – Profile Alias 3 – Profile Relations
monitoring	object	Optional	Monitoring options.
monitoring.monitor	boolean	Optional	Whether this search should be monitored.
monitoring.schedule	object		Schedule options.
monitoring.schedule.scheduleType	string	Optional	String enumeration for monitor frequency. Default value is Monthly. Possible values are DAILY, WEEKLY, MONTHLY, QUARTERLY, OR ANNUALLY.
monitoring.schedule.endAt	datetime	Optional	Specifies when the monitoring should stop, expressed in ISO 8601.

Abbreviation	Name
ALLWL	All WLS categories
ACTIV	Activist
AMLKC	AML/KYC Compliance
EXDEB	Exclusion/Debarment
FINAN	Financial
GLCRM	Global Criminal
GLHLC	Global Healthcare
GWLAS	Global Watch Lists and Sanctions
IMEXP	Import/Export
NATCF	National Criminal File
NATHC	National Healthcare
OIGHS	Office of the Inspector General
RLEST	Real Estate
SAMGE	SAM.gov Exclusions
SAMGV	SAM.gov
SXOFF	Sex Offenders
WCORR	Corruption
WOFAC	OFAC
WTERR	Terrorism

Abbreviation	Name	Description
ALLNM	All NM categories	Contains all adverse news types.
ANRTS	Animal Rights	This category contains adverse news geared towards animal rights. Which includes news of animal cruelty, arrests, lawsuits etc.
BUFIN	Business & Financial	Contains adverse news from business and financial articles.
CRCRT	Crime & Courts	contains adverse news involving Crime and Courts. A few examples include: o Investigations o News on trials o News on Arrests o Police Logs o News on Sentencings o News on Legal Cases
GNEWS	General News	contains all adverse news types (with the exception of Sports, Celebrity News, Gossip, Weather). A few examples include; o Regional News o Top Stories o Featured News o World News
MISEC	Military & Security	contains adverse news involving Military and Nation Security. A few examples include; o War and Conflict o Defense News o News on Terrorism/Terrorist o International Criminal Court News o Country Relations o Government Briefs o Sanctions o News from Intelligence Agencies
NMCOR	Corruption	o News of bribery o News of embezzlement 5 o Political corruption o News from Anti-Corruption agencies o Whistle-Blower News o News of investigations/arrests/cases/trials for corruption o Misconduct News
POGOV	Politics & Government	contains adverse news involving Politics or Government. A few examples include; o Brexit News o Parliament News o Political News o Embassies News o Election News o Federal/State/City Politics o Government News

Abbreviation	Name
ALLPP	All PEP categories

Sample Response (WLS, AM, PEP)

{
  "approximateTotalRecords": 1521,
  "subject": "Donald Trump",
  "subjectId": "GA94924-83",
  "results": {
    "subject": "Donald Trump",
    "results": {
      "wlsResults": [
        {
          "score": 0.8825105,
          "category": "NATCF,SXOFF",
          "productId": "WLS",
          "resultId": 1,
          "sourceId": 124,
          "address": "265 E JACKSON ST DOVER, NJ 07801",
          "age": "59 (DOB: 03/30/1959)",
          "aliasList": "DONALD THOMPSON",
          "caution": "2C:24-4A - Endangering the Welfare of a Child",
          "dateOfBirth": null,
          "entityName": null,
          "eyeColor": "Brown",
          "gender": "M",
          "hairColor": "Gray",
          "height": "5'10''",
          "highlights": [],
          "identifier": "231981",
          "individualName": "DONALD T THOMPSON",
          "nationality": null,
          "placeOfBirth": null,
          "program": null,
          "race": "White",
          "remarks": "Scar on L_eye () , Scar on Head () , Scar on Forehead () , Scar on Nose () , Scar on Back ()",
          "sourceAgencyAcronym": "N/A",
          "sourceAgencyName": "New Jersey State Police",
          "sourceListType": "State Sex Offender Registry",
          "sourceParentAgency": "N/A",
          "sourceRegion": "North America",
          "subjectMatched": "DONALD T THOMPSON",
          "text": "Offender Search: Offender Details Details Name: DONALD T...",
          "url": "http://www.icrimewatch.net/...",
          "weight": "176lbs"
        }
      ],
      "nmResults": [
        {
          "score": 1,
          "category": "GNEWS",
          "productId": "NM",
          "resultId": 3,
          "sourceId": 323,
          "highlights": [],
          "subjectMatched": "Donald Trump",
          "text": "Nearly 100 of America's top tech companies like Apple, Google and Facebook ..."
        }
      ],
      "pepResults": [
        {
          "score": 1,
          "productId": "PEP",
          "profileId": 73616,
          "resultId": 4,
          "country": "United States of America",
          "countryCode": "USA",
          "name": "Donald Trump",
          "gender": "male",
          "placeOfBirth": "Jamaica Hospital",
          "dateOfBirth": "1946-06-14",
          "dateOfDeath": null,
          "birthName": "Donald John Trump",
          "nativeName": "Donald Trump",
          "professionalHistory": [
            "President of the United States of America",
            "director",
            "chairperson"
          ],
          "memberOf": [
            "Forbes list of billionaires",
            "Republican Party"
          ],
          "employer": [],
          "education": [...],
          "awardsReceived": [...],
          "notableWork": [...],
          "convicted": [],
          "sourceInfoURL": [],
          "address": [...],
          "aliases": [...],
          "scoreBoosts": [
            "Score Boosted from 1 to 1.02 (Profile ID: 73616) Alias The Don found in The Donald"
          ],
          "pepSearchType": 0,
          "familyMembers": [
            {
              "relationType": "Relative",
              "name": "Elizabeth Trump"
            },
            {
              "relationType": "Spouse",
              "name": "Ivana Trump"
            }
          ],
          "social": [...],
          "businessRelations": [...],
          "businessPartnerships": [...],
          "lobbying": [],
          "stakeholder": [...],
          "contributions": [...]
        }
      ]
    }
  },
  "translatedSubject": null,
  "translatedResults": {
    "wlsResult": null,
    "medResults": null,
    "nmResults": null,
    "pepResults": null
  },
  "alaisResults": [
    {
      "subject": "POTUS",
      "results": {
        "wlsResults": [...],
        "medResults": [...],
        "nmResults": [...],
        "pepResults": [...]
      },
      "translatedSubject": null,
      "translatedResults": {
        "wlsResult": null,
        "medResults": null,
        "nmResults": null,
        "pepResults": null
      }
    }
  ],
  "monitor": {
    "monitorId": "15249ac5-19d8-4bbf-8c2f-50244e5eecc9",
    "duplicate": false,
    "success": true,
    "message": "Monitor successfully created"
  },
  "searchedProducts": {
    "WLS": {
      "categories": [
        "FINAN"
      ],
      "minScore": 0.8
    },
    "NM": {
      "categories": [
        "GNEWS",
        "BUFIN"
      ]
    },
    "PEP": {
      "minScore": 0.875
    }
  }
}

Sample Response (Only Adverse Media)

{
    "result": {
        "recordsFound": true,
        "subject": "Riza Aziz",
        "results": {
            "wlsResults": null,
            "nmResults": [
                {
                    "productId": "NM",
                    "score": 1,
                    "sourceId": 9837,
                    "category": "CRCRT",
                    "resultId": 1,
                    "subjectMatched": "Riza Aziz",
                    "text": "KUALA LUMPUR: Former prime minister Datuk Seri Najib Tun Razak’s wife Datin Seri Rosmah Mansor is expected to present herself to the police on Friday for her statement to be recorded in connection with the investigation into alleged misappropriation of funds from 1Malaysia Development Berhad (1MDB).According to a source, Rosmah will be quizzed by the Anti-Money Laundering Crime Investigation Team at Menara KPJ, Jalan Tun Razak here on Friday morning.“She was asked to come tomorrow to give her statement, but has requested to postpone the recording of her statement to Friday,” the source told Bernama.The source added that besides Rosmah, her sons, Riza Aziz and Mohd Norashman Najib would also be present to give their statements regarding the investigation.On Oct 4, Inspector-General of Police Tan Sri Mohamad Fuzi Harun said the police may call Rosmah to record her statement on various cases including 1MDB. --Bernama © New Straits Times Press (M) Bhd",
                    "url": "https://www.nst.com.my/news/crime-courts/2018/10/424466/1mdb-rosmah-expected-give-statement-police-tomorrow",
                    "sentimentConfidenceLevel": "High"
                },
                {
                    "productId": "NM",
                    "score": 1,
                    "sourceId": 9837,
                    "category": "CRCRT",
                    "resultId": 2,
                    "subjectMatched": "Riza Aziz",
                    "text": "KUALA LUMPUR: Former prime minister Datuk Seri Najib Razak did not want a second valuation be done on the assets of 1Malaysia Development Bhd's (1MDB) joint venture partner, PetroSaudi International Ltd (PSI), the High Courtm heard today.Former 1MDB chief executive officer Datuk Shahrol Azral Ibrahim Halmi said a second valuation could have proved that there was \"more downside than upside\" to the deal.Asked by Najib’s lead counsel Tan Sri Muhammad Shafee Abdullah as to why details about PSI’s assets were concealed from the board, Shahrol replied: “It just did not come up”.The ninth prosecution witness said at the time, Edward Morse was the only independent valuer for PSI’s assets and Najib, as the chairman of 1MDB board of advisers, had stated there was no need for a second valuation.Shafee: So what does that mean? There was no second valuation?Shahrol: It means that a second valuation was not preferred. My take from this is that he (Najib) did not prefer this.Shafee: Did he explicitly say he did not want you to make a second valuation?Shahrol: No, he did not say that. The court then heard that fugitive businessman Low Taek Jho or Jho Low was described as \"a fox taking care of chicken\".Shafee said this when the witness testified that he went back and forth between Najib, Low and the 1MDB board of directors.Shahrol said after a meeting with Najib on Oct 16, 2009, he went to see Low to get the minutes of meeting and went back to the 1MDB board of directors.Shafee: Was I wrong to say that Jho Low was (like) a fox taking care of chicken?Shahrol: He was in a way facilitating the misappropriation from 1MDB. I think it may be worth to know that in 2016, Good Star Ltd (a company owned by Low) sent some money to Red Granite Pictures (a company owned by Najib’s stepson, Riza Aziz).Shafee: Why did you go to Red Granite? We will get to that later. Let’s concentrate on what you did. Do not get into anybody else’s problem.Cross-examination before judge Collin Lawrence Sequerah continues tomorrow.Najib, 66, is charged with misappropriating RM2.28 billion of 1MDB funds, money laundering and abuse of power.© New Straits Times Press (M) Bhd",
                    "url": "https://www.nst.com.my/news/crime-courts/2019/10/534177/witness-najib-said-no-need-second-valuation-psi-assets",
                    "sentimentConfidenceLevel": "High"
                }
                 ],
            "pepResults": null
        },
        "translatedSubject": null,
        "translatedResults": {
            "wlsResults": null,
            "nmResults": null,
            "pepResults": null
        }
    }
}

Response Body Parameters

Parameter	Data Type	Description
approximateTotalRecords	integer	Total number of search results.
subject	string	Name of individual or business searched.
subjectId	string	Provided SubjectId
results	object	Results for the subject. Includes subject and translated subject.
aliasResults[]	list	The list of results for all aliases. Includes subject and translated subject results.
monitor	object	Only populated if the search was marked for monitoring.
monitor.monitorId	guid	The ID for the monitor created.
monitor.duplicate	boolean	Whether a monitor already exists for this subjectId.
monitor.success	boolean	Whether a monitor was successfully created. monitor.message string A plain text message in regards to creating a monitor.
searchedProducts	object	Information on the products searched.
searchedProducts.(key)	string	Identifies the product.
searchedProducts.(key).categories[]	list	The categories searched for this product.
searchedProducts.(key). minScore	float	If configured, shows the minimum relevancy score used for this product for this search. Any results below this value have been excluded.

Watchlist Screen Result Parameters

Parameter	Data Type	Description
Score	float	The calculated relevancy match percentage is based on matching the name submitted with the name in the record. The score could also be boosted if any of the more parameters from the record match with what the user submitted.
category	string	Category(-ies) matched. Multiple values are comma separated.
productId	string	Product matched
resultId	integer	Unique id for the search result
sourceId	long	Internal ID assigned for the source.
address	string	Address information for individual or business.
age	string	Individual's age.
aliasList	string	Individual's alias name(s) and/or business DBA(s)
caution	string	Any known alerts/sanctions/issues related to the ad subject.
dateOfBirth	string	Individual's date of birth.
entityName	string	Name of the business.
eyeColor	string	Individual's eye color.
gender	string	Individual's gender.
hairColor	string	Individual's hair color.
height	string	Individual's height.
highlights[]	list	Snippets of text where the name was matched in a text based search.
identifier	string	Any values associated to the Individual or Business. For example: Passport number or Business License.
individualName	string	Name of the individual.
nationality	string	Individual's nationality.
placeOfBirth	string	Hospital and/or City.
program	string	Type of list, group, or association with which the searched subject may be connected to, per the source.
race	string	Individual's race.
remarks	string	Any pertinent remarks about the searched subject which the source chose to highlight.
sourceAgencyAcronym	string	Acronym of the agency which represents the source of the result record.
sourceAgencyName	string	Name of the agency which represents the source of the result record.
sourceListType	string
sourceParentAgency	string	Name of the parent agency which represents the source of the record.
sourceRegion	string	Geographic region of the source which represents the result record.
subjectMatched	string	The name matched for this document
text	string	Any associated unstructured text.
url	string	Web URL for article source.
weight	string	Individual's weight.

Adverse/Negative Media Result Parameters

Parameter	Data Type	Description
score	float	The calculated relevancy match percentage.
category	string	Category(-ies) matched. Multiple values are comma separated.
productId	string	Product matched
resultId	integer	Unique id for the search result
sourceId	long	Internal ID assigned for the source.
highlights[]	list	Snippets of text where the name was matched in a text based search.
subjectMatched	string	The name matched for this document
text	string	Any associated unstructured text.
url	string	Web URL for article source.
sentimentConfidenceLevel	string	Sentiment confidence level for capture. Possible values are Low, Moderate, and High

Politically Exposed Persons (PEP) Result Parameters

Parameter	Data Type	Description
score	float	The calculated relevancy match percentage.
productId	string	Product matched
profileId	long
resultId	integer	Unique id for the search result
country	string	Country of Citizenship
countryCode	string	Country Code for country of citizenship
name	string	Name of PEP Profile
gender	string	Male or Female
placeOfBirth	string	Hospital and/or City
dateOfBirth	string	The date the individual as born
dateOfDeath	string	The date the individual died, if applicable.
birthName	string	Name on Birth Certificate
nativeName	string	Name of PEP Profile
professionalHistory[]	list	List of professional positions held
memberOf[]	list	List of any groups the person belongs to
employer[]	list	List of employers
education[]	list	List of schools the person has attended
awardsReceived[]	list	List of any major award the person has received
notableWork[]	list	List of notable works
convicted[]	list	List of any crimes or legal issues the person has been convicted of.
address[]	list	Any known addresses the PEP holds/has held.
aliases[]	list	Alias hits from the PEP search
scoreBoosts[]	list	Explanation of relevancy score boosts
pepSearchType	integer	PEP, Alias, or Associations
familyMembers[]	list	Business partnerships the PEP is/was engaged in.
social[]	list	Social groups, establishments or friends the PEP is/was engaged with.
businessRelations[]	list	Business relationships the PEP is/was engaged in.
businessPartnerships[]	list	Business partnerships the PEP is/was engaged in.
lobbying[]	list	Lobbying relationships the PEP is/was engaged in.
stakeholder[]	list	Names of any individuals or businesses which are stakeholders in interest of the PEP, or which the PEP holds a stake in.
contributions[]	list	Business partnerships the PEP is/was engaged in.

Sample Error

{
    "error": {
        "name": "error",
        "message": "Invalid Date",
        "status": 400,
        "reason": "VALIDATION_ERROR",
        "type": "Bad Request",
        "statusCode": 200
    }
}

Error Response Parameters

Parameter	Description
error	This parameter contains the error.
error.name	the name of the error
error.message	the error message
error.status	status of the api
error.reason	Reason for error
error.type	Type of the error
error.statusCode	Request Status code from Signzy

Getting help

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