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Overview

Get started (API v3.1)

Welcome to our new API v3.1 documentation. If you're migrating and are currently using api.onfido.com, please make sure you use api.eu.onfido.com with API v3.1.

You'll find migration guides in the API section.

The Onfido API is based on REST principles. It uses standard HTTP response codes and verbs, and token-based authentication.

If you're just getting started with our API, read our quick-start guides.

Request, response format

You should use a Content-Type: application/json header with all PUT and POST requests except when uploading documents or live photos. For these requests, use a Content-Type: multipart/form-data header.

Responses return JSON with a consistent structure, except downloads.

You must make all your requests to the API over HTTPS and TLS 1.2+, with Server Name Indication enabled. Any requests made over HTTP will fail.

Text fields support UTF-8, but do not allow certain special characters.

Token authentication

The Onfido API uses token-based authentication. API tokens must be included in the header of all requests made to the API.

You can generate new tokens and find your existing ones in your Onfido Dashboard.

You can make requests using sandbox tokens to test our API before you go live.

Token Authentication
1Authorization: Token token=<YOUR_API_TOKEN>

API tokens

You can use API tokens to authenticate any API action described in this documentation.

You can create and revoke API tokens, and see when they were last used, in your Onfido Dashboard.

You must never use API tokens in the frontend of your application or malicious users could discover them in your source code. You should only use them on your server.

If you do need to collect applicant data in the frontend of your application, we recommend that you use one of the Onfido Smart Capture SDKs.

You should limit live API token access to only the minimum number of people necessary, but you can use sandbox tokens to freely experiment with the sandbox Onfido API.

Note that there are some differences between the sandbox and live APIs.

You should not embed API tokens in your backend code—even if it’s not public—because this increases the risk that they will be discovered. Instead, you should store them in configuration files or environment variables. Please consider enabling GitHub's Secret Scanning and Push Protection feature when hosting your code on GitHub. This will help detect and safeguard Onfido API Tokens that could inadvertently be exposed in your repositories.

You should also periodically rotate your live API tokens (see next section).

API token rotation

We highly recommend that you rotate live API tokens when staff members with access to those tokens leave your organisation. Consider creating a leaver's process which covers this.

  1. In your Onfido Dashboard, create a new API token

  2. Wherever you use your old API token, replace it with the new one

  3. Confirm your old token isn't in use

  4. Revoke your old token

Your old API tokens will continue to work until you revoke them, so you can rotate your tokens without users experiencing any downtime.

SDK tokens

If you're using the Android SDK at lower than version 4.11.0 or the iOS SDK lower than 12.2.0, please update your integration to use a Mobile SDK version which supports SDK tokens.

All of the latest Onfido Smart Capture SDKs authenticate using SDK tokens. You cannot use an API token to authenticate the SDKs.

SDK tokens are restricted to an individual applicant and expire after 90 minutes.

You can generate SDK tokens using an API endpoint.

Mobile tokens

Mobile tokens will no longer be supported from October 24th 2022. You will not be able to use Mobile tokens with any version of the Onfido SDKs from this date. Please upgrade your integration to use SDK tokens. We recommend you do this as soon as possible to also allow time to update your application.

If you are on version 4.11.0 or below for Android, or 12.2.0 or below for iOS, you must upgrade to the latest SDK version in order to use SDK tokens.

If you need to generate Mobile tokens please contact Onfido's Customer Support.

Sandbox testing

You should never upload confidential information, including personal data, to the sandbox.

The type of token you use will determine whether you use the sandbox or live environment.

You can make all the same API requests in the sandbox API as in the live one. Sandbox results have the same result response structures as live requests. You will also be notified of check and report status changes via your registered webhooks.

You can use the sandbox API to simulate API requests and to check:

  • your system's network connectivity with the Onfido API
  • your webhooks are working correctly
  • you're posting all required data in the correct format to the Onfido API
  • you're handling Onfido API responses correctly

To use the sandbox, you'll need to generate a sandbox API token in your Onfido Dashboard.

By default, sandbox API tokens start with api_sandbox. and live API tokens start with api_live.. This might vary if you're using a different region environment.

For sandbox requests, the rate limit is 30 requests per minute.

Sandbox and live differences

The key differences between sandbox and live checks are:

  • sandbox check data is not processed by Onfido services or third parties—this means that sandbox responses are faster than live responses
  • sandbox check results are pre-determined
  • sandbox applicants are isolated from the live environment*
  • you won't be charged for checks in sandbox

* applicant notification emails still get sent out to sandbox applicants

Sample document, photo

You can use the upload document endpoint with the following files as part of running test checks:

The sandbox API will always return pre-determined responses, regardless of what files are uploaded.

These files also work for testing the Onfido Smart Capture SDKs.

Pre-determined responses

To help you test your integration in the sandbox API, you can trigger pre-determined report responses.

Pre-determined responses work for the following report types:

Pre-determined 'consider' results

To test only 'consider' report responses:

  1. Create an applicant which has the last name "Consider"
  2. Create a check with this applicant

All reports specified in check creation will return a consider report result. If you use any other applicant last name, the result will be clear.

Different reports have different minimum requirements for applicant data (even in the sandbox).

Create an applicant with last name of Consider
1POST /v3.1/applicants/ HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>
4Content-Type: application/json
5
6{
7 "first_name": "Jane",
8 "last_name": "Consider"
9}

Pre-determined 'consider' and 'clear' results

To test multiple different sandbox report responses simultaneously, you can pass specific report types to the consider parameter (in an array).

Only the reports specified in the consider array will return a consider report result. All other reports in the check will return a clear result.

Trigger multiple report results simultaneously
1POST /v3.1/checks/ HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>
4Content-Type: application/json
5
6{
7 "applicant_id": "<APPLICANT_ID>",
8 "report_names": [
9 "watchlist_standard",
10 "identity_enhanced"
11 ],
12 "consider": [
13 "watchlist_standard"
14 ]
15}

Pre-determined responses for Document reports

The sandbox API supports additional functionality for testing Document reports. You can trigger pre-determined Document report responses for specific:

For Document reports, first_name and last_name must be provided when creating an applicant (even in the Sandbox).

Breakdowns and sub-breakdowns

You can trigger responses for particular breakdowns and sub-breakdowns for sandbox Document reports. These responses show possible breakdown and sub-breakdown combinations that can be flagged for a consider report result.

To test breakdown - sub-breakdown combinations:

  1. Create an applicant which has the first_name as the "breakdown - sub-breakdown" combination you intend to trigger.

Sandbox supports the following options:

  • "Image Integrity - Supported Document"
  • "Image Integrity - Image Quality"
  • "Visual Authenticity - Fonts"
  • "Visual Authenticity - Security Features"
  • "Visual Authenticity - Face Detection"
  • "Data Validation - Document Numbers"
  • "Data Consistency - Document Type"

You can also include a document type by specifying last_name as a supported sandbox document type during applicant creation.

  1. Create a check with this applicant.

Passing a first_name option to generate a Document report pre-determined response will override any conflicting option passed to the applicant's last_name.

Trigger an Image Integrity - Supported Document breakdown combination for a Document report
1POST /v3.1/applicants/ HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>
4Content-Type: application/json
5
6{
7 "first_name": "Image Integrity - Supported Document",
8 "last_name": "Smith"
9}

Document types

You can trigger responses for particular document types for sandbox Document reports. These responses show a Document report response including the specific properties for the associated document type.

To test different document types:

  1. Create an applicant which has the last_name as the document type you intend to test.

Sandbox supports the following options:

Sandbox optionSandbox option *Document type **
"CA DL 2018""CA DL 2018 front only"US drivers license for California state
"NY DL 2017""NY DL 2017 front only"US drivers license for New York state
"Ontario ID 2010"-Canadian national identity card for Ontario
"FRA ID 1994""FRA ID 1994 front only"French identity card

* Specifying "front only" means only data contained on the front side of the document will be returned in the properties.

** The document type properties returned are specific to the document version supported in Sandbox.

You can also trigger a flagged "breakdown - sub-breakdown" combination by specifying first_name as a supported combination during applicant creation.

  1. Create a check with this applicant.
Trigger a Document report with US drivers license for California state
1POST /v3.1/applicants/ HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>
4Content-Type: application/json
5
6{
7 "first_name": "Jane",
8 "last_name": "CA DL 2018"
9}

Sub-results

You can trigger responses for particular sub-results for sandbox Document reports. These responses show possible individual breakdown results which can lead to different sub-results.

To do this:

  1. Create an applicant which has the last_name as one of the following strings:
  • "clear"
  • "rejected"
  • "suspected"
  • "caution"
  1. Create a check with this applicant.

You can't also specify a document type when testing sub-results.

Trigger a rejected sub-result for a Document report
1POST /v3.1/applicants/ HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>
4Content-Type: application/json
5
6{
7 "first_name": "Jane",
8 "last_name": "rejected"
9}

Pre-determined responses for Facial Similarity reports

The sandbox API supports additional functionality for testing breakdowns and sub-breakdowns for Facial Similarity Photo, Photo Fully Auto, Video and Motion reports.

For Facial Similarity reports, first_name and last_name must be provided when creating an applicant (even in the Sandbox).

Breakdowns and sub-breakdowns

You can trigger responses for particular breakdowns and sub-breakdowns for sandbox Facial Similarity reports. These responses show possible breakdown and sub-breakdown combinations that can be flagged for a consider report result.

To test breakdown - sub-breakdown combinations:

  1. Create an applicant which has the first_name as the "breakdown - sub-breakdown" combination you intend to trigger.

Sandbox supports the following options:

  • "Visual Authenticity - Spoofing Detection"
  • "Face Comparison - Face Match"
  • "Image Integrity - Source Integrity"
  • "Image Integrity - Face Detected"
  1. Create a check with this applicant.
Trigger an Visual Authenticity - Spoofing Detection breakdown combination for a Facial Similarity report
1POST /v3.1/applicants/ HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>
4Content-Type: application/json
5
6{
7 "first_name": "Visual Authenticity - Spoofing Detection",
8 "last_name": "Smith"
9}

Applicant IDs returned in the response don't map to actual sandbox applicants, they are example uuids to represent the applicant ID field. As a result, there is no associated applicant data.

Pre-determined responses for Repeat Attempts

The sandbox API supports additional functionality for testing breakdowns and sub-breakdowns for Repeat Attempts.

To help you integrate with this service, you can generate pre-defined Repeat Attempts responses. Depending on the scenario you are trying to test, you can use one of four possible keywords as the report_uuid in the request URL:

  • match
  • mismatch
  • error
  • empty
Trigger a Repeat Attempts match
1$ curl -X POST https://api.eu.onfido.com/v3.1/repeat_attempts/match \
2 -H 'Authorization: Token token=<YOUR_API_TOKEN>' \

Below is a pre-determined response example for a Repeat Attempts match:

json
1{
2 "report_id": "00000000-0000-0000-0000-000000000000",
3 "repeat_attempts": [
4 {
5 "report_id": "00000000-0000-0000-0000-000000000001",
6 "applicant_id": "00000000-0000-0000-0000-000000000003",
7 "date_of_birth": "match",
8 "names": "match",
9 "result": "clear",
10 "created_at": "2022-01-06T14:46:43Z",
11 "completed_at": "2022-01-06T15:46:43Z"
12 },
13 {
14 "report_id": "00000000-0000-0000-0000-000000000002",
15 "applicant_id": "00000000-0000-0000-0000-000000000003",
16 "date_of_birth": "match",
17 "names": "match",
18 "result": "clear",
19 "created_at": "2022-02-18T03:09:34Z",
20 "completed_at": "2022-02-18T03:10:34Z"
21 }
22 ],
23 "attempts_count": 3,
24 "attempts_clear_rate": 1,
25 "unique_mismatches_count": 0
26}

Go live

Before you go live, you may find the introductory guides in our Getting Started section useful.

API client libraries

You can use our officially supported client libraries to integrate with the Onfido API.

LanguageLibraryNotes
Rubyonfido-ruby
Javaonfido-java
Node.jsonfido-nodeAlso supports TypeScript.
Pythononfido-python
PHPapi-php-clientMade with OpenAPI generator.

Refer to our API versioning guide for details on client library versioning.

Please email Onfido's Customer Support if you write your own library and want us to link to it.

OpenAPI specification

We use an OpenAPI specification to generate our PHP library, which we also host publicly.

For any custom libraries you generate yourself with this specification, we can only provide support on a best-effort basis.

Rate limits

Onfido's API enforces a maximum volume of requests per second for all clients. Unless contractually agreed otherwise, the maximum rate is 400 requests per minute (up to 7 requests per second with a burst of 14 requests).

For sandbox requests, the rate limit is 120 requests per minute (up to 2 requests per second with a burst of 4 requests).

Onfido uses the token bucket algorithm to handle usage.

Any request over the limit will return a 429 Too Many Requests error.

Rate limit reached error object
1HTTP/1.1 429 Too Many Requests
2Content-Type: application/json
3
4{
5 "error": {
6 "type": "rate_limit",
7 "message": "Rate limit exceeded. Please try again later."
8 }
9}

Regions

There is no default region in API v3.1. If you were previously using api.onfido.com, you should use api.eu.onfido.com with v3.1.

Initialization with region EU
1onfido = Onfido::API.new(
2 api_key: ENV['ONFIDO_API_KEY'],
3 region: :eu
4)

Onfido offers region-specific environments: EU, US, and Canada. You can use these to store the data in your Onfido account at rest within a specific geographic region.

Initialization with region US
1onfido = Onfido::API.new(
2 api_key: ENV['ONFIDO_API_KEY'],
3 region: :us
4)

Regions have unique base URLs and API token formats for both live and sandbox environments.

Initialization with region CA
1onfido = Onfido::API.new(
2 api_key: ENV['ONFIDO_API_KEY'],
3 region: :ca
4)
RegionNotesAPI base URLAPI token format
EUReplaces api.onfido.com for EU region in v3.1https://api.eu.onfido.com/Tokens are prepended with api_live. and api_sandbox.
UShttps://api.us.onfido.com/Tokens are prepended with api_live_us. and api_sandbox_us.
CAhttps://api.ca.onfido.com/Tokens are prepended with api_live_ca. and api_sandbox_ca.

Unless specified, all examples in the documentation refer to the https://api.eu.onfido.com/ base URL and token format.

For the EU region, data is physically stored in the Republic of Ireland, with backup storage in Germany.

If you're using one of the officially supported API client libraries, follow that library's GitHub documentation to change the region.

Versioning policy

Refer to our API versioning guide for details on Onfido's versioning policy.

Changelog

DateDescription
2022-01-12Added documentation for Watchlist AML report.
2021-11-15Added documentation for Trusted Faces.
2021-08-19Added documentation for Face Authenticate.
2021-08-03Added documentation on the Driver's License Data Verification report.
2021-07-21Added documentation for new Sandbox functionality.
2021-05-11Added share code content to Right to Work report (product now deprecated and no longer available).
2021-04-08General release of API version 3.1. Please see our release notes
2021-04-08privacy_notices_read_consent_given added to check object in v3.1

Upcoming maintenance

There's currently no scheduled maintenance.

Errors

All errors are returned with the same structure:

json
1{
2 "error": {
3 "type": <TYPE>,
4 "message": <MESSAGE>,
5 "fields": <FIELDS - NOT ALWAYS PRESENT>
6 }
7}

Example error object

AttributeDescription
typestring
The type of error returned.
messagestring
A human-readable message giving more details about the error.
fieldsobject
The invalid fields and their associated errors. Only applies to validation errors.
Example validation error object
1HTTP/1.1 422 Unprocessable Entity
2Content-Type: application/json
3
4{
5 "error": {
6 "type": "validation_error",
7 "message": "",
8 "fields": {
9 "email": [
10 "invalid format"
11 ]
12 "name": [
13 "can't be blank"
14 ]
15 }
16 }
17}

Error codes and what to do

StatusAction
400 bad_requestMake sure your request is formatted correctly.
400 incorrect_base_urlPlease use api.eu.onfido.com for API v3.1 onwards if you were previously using api.onfido.com.
401 authorization_errorMake sure you've entered your API token correctly.
The Onfido Smart Capture SDKs use SDK tokens for authentication, not API tokens. If you're receiving a 401 error on one of our SDKs, check you've entered a valid application ID when generating the SDK token.
401 user_authorization_errorContact an administrator about user permissions.
401 bad_referrerCheck the referrer used to generate the SDK token.
401 expired_tokenRequest a new SDK token.
403 account_disabledPlease contact client-support@onfido.com.
403 trial_limits_reachedPlease contact client-support@onfido.com.
404 resource_not_foundMake sure you've formatted the URI correctly.
410 goneThe resource has been deleted or is scheduled for deletion.
422 validation_errorCheck the fields property for a specific error message.
422 missing_billing_infoMake sure you've provided your billing information before starting a check.
422 missing_documentsMake sure you've uploaded the required documents before starting a check.
422 invalid_reports_namesMake sure you've entered the report name(s) in the correct format (string).
422 missing_id_numbersMake sure you've supplied all required ID numbers.
422 report_names_blankMake sure you've specified report_names in your request.
422 report_names_formatreport_names must be an array of strings, not an array of objects.
422 deprecated_reportsThe requested reports have been deprecated.
422 check_type_deprecatedtype is not used in this version of the API. Please read about the applicant_provides_data feature.
422 document_ids_without_document_reportYou should only specify the optional document_ids argument when creating a check containing a Document report or a Facial Similarity report, or both.
422 facial_similarity_photo_without_documentFor applicant_provides_data checks, Facial Similarity reports must be paired with a Document report.
422 facial_similarity_video_not_supportedThe Facial Similarity Video report is not supported for checks where applicant_provides_data is true.
422 failed_check_requirementsCheck that all required information has been provided and correctly specified.
422 incomplete_checksThere are other ongoing checks associated with this applicant.
422 disabled_reportsThere are reports disabled in your account. Please contact client-support@onfido.com.
422 too_many_checksYou have exceeded the limit of 1000 checks for the given applicant.
429 rate_limitThe rate limit has been reached. Please try again later.
500 internal_server_errorThe server encountered an error. If this persists, please contact client-support@onfido.com.

Core Resources

Applicants

An applicant represents an individual who will be the subject of a check. An applicant must exist before a check can be initiated.

Different report types have different minimum requirements for applicant data, and different recommended data. For each report, this information is noted in under the relevant section of this documentation. For example, for Document reports.

If you're requesting multiple checks for the same individual, you should reuse the id returned in the initial applicant response object in the applicant_id field when creating a check.

Applicants with Sanctioned Documents

If an applicant uploads a document which is issued by a country subject to comprehensive US sanctions (list of countries here), any reports run with that applicant will return a withdrawn status unless otherwise specified in the report documentation. Current exceptions to this are the Document and Facial Similarity reports, which will still run but return a result indicating the presence of a sanctioned document.

Applicant object

AttributeDescription
idstring
The unique identifier for the applicant.
created_atdatetime
The date and time when this applicant was created.
delete_atdatetime
The date and time when this applicant is scheduled to be deleted, or null if the applicant is not scheduled to be deleted.
hrefstring
The URI of this resource.
first_namestring
The applicant's first name.
last_namestring
The applicant's surname.
emailstring
The applicant's email address.
dobdate
The applicant's date of birth in YYYY-MM-DD format.
id_numbersarray of id number objects
A collection of identification numbers belonging to this applicant.
addressaddress object
The address of the applicant.
sandboxBoolean
Indicates whether the object was created in the sandbox or not.

ID number object

The ID number array of objects is nested inside the applicant object.

AttributeDescription
typestring
Type of ID number. Valid values are ssn, social_insurance (e.g. UK National Insurance), tax_id, identity_card and driving_licence.
valuestring
Value of ID number. ssn supports both the full SSN or the last 4 digits. If the full SSN is provided then it must be in the format xxx-xx-xxxx.
state_codestring
Two letter code of issuing state (state-issued driving licences only).

Address object

The applicant address object is nested inside the applicant object.

AttributeDescription
flat_numberstring
The flat number.
building_numberstring
The building number.
building_namestring
The building name.
streetstring
The street of the applicant's address. There is a 32-character limit on this field for UK addresses.
sub_streetstring
The sub-street.
townstring
The town.
statestring
The address state. US states must use the USPS abbreviation (see also ISO 3166-2:US), for example AK, CA, or TX.
postcodestring
The postcode (ZIP code) of the applicant's address. For UK postcodes, specify the value in the following format: SW4 6EH.
countrystring
The 3 character ISO country code of this address. For example, GBR is the country code for the United Kingdom.
line1string
Line 1 of the address.
line2string
Line 2 of the address.
line3string
Line 3 of the address.

postcode and country are required fields if an address is provided for an applicant. For US addresses, state is also a required field.

Most addresses will contain information such as flat_number. Make sure they are supplied as separate fields, and do not try and fit them all into the street field. Doing so is likely to affect check performance.

Alternatively, you can provide addresses in the form line1, line2 and line3 if you're creating a check with an Identity Enhanced report. If you provide address data in this form, Onfido uses a third-party subprocessor for address cleansing.

Forbidden characters

For addresses the following characters are forbidden:

!$%^*=<>

For names the following characters are forbidden:

^!#$%*=<>;{}"

Example applicant object
1HTTP/1.1 201 Created
2Content-Type: application/json
3
4{
5 "id": "<APPLICANT_ID>",
6 "created_at": "2019-10-09T16:52:42Z",
7 "sandbox": true,
8 "first_name": "Jane",
9 "last_name": "Doe",
10 "email": null,
11 "dob": "1990-01-01",
12 "delete_at": null,
13 "href": "/v3.1/applicants/<APPLICANT_ID>",
14 "id_numbers": [],
15 "address": {
16 "flat_number": null,
17 "building_number": null,
18 "building_name": null,
19 "street": "Second Street",
20 "sub_street": null,
21 "town": "London",
22 "state": null,
23 "postcode": "S2 2DF",
24 "country": "GBR",
25 "line1": null,
26 "line2": null,
27 "line3": null
28 }
29}

Create applicant

POST
/v3.1/applicants/

Using this endpoint in a live context will cause you to send personal data to Onfido. Always make sure you inform your users about this and obtain any necessary permissions. For more information on how Onfido uses personal data, view our Privacy Policy.

Creates a single applicant. Returns an applicant object.

When you create an applicant, some characters are forbidden. You should remove any duplicate whitespaces before creating an applicant, otherwise this may result in a data comparison failure.

The minimum required (and recommended) applicant data depends on the type of report requested. For example, for Document reports.

Request body parameters

ParameterDescription
first_namerequired
The applicant's forename.
last_namerequired
The applicant's surname.
emailrequired only if creating a check where applicant_provides_data is true
The applicant's email address.
doboptional
The applicant's date of birth in YYYY-MM-DD format.
id_numbersoptional
A collection of identification numbers belonging to this applicant.
addressoptional
The address of the applicant.
Create an applicant
1POST /v3.1/applicants/ HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>
4Content-Type: application/json
5
6{
7 "first_name": "Jane",
8 "last_name": "Doe",
9 "dob": "1990-01-31",
10 "address": {
11 "building_number": "100",
12 "street": "Main Street",
13 "town": "London",
14 "postcode": "SW4 6EH",
15 "country": "GBR"
16 }
17}

Retrieve applicant

GET
/v3.1/applicants/{applicant_id}

Retrieves a single applicant. Returns an applicant object.

Retrieve an applicant
1GET /v3.1/applicants/<APPLICANT_ID> HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>

Update applicant

PUT
/v3.1/applicants/{applicant_id}

Using this endpoint in a live context will cause you to send personal data to Onfido. Always make sure you inform your users about this and obtain any necessary permissions. For more information on how Onfido uses personal data, view our Privacy Policy.

Updates an applicant's information. Returns the updated applicant object.

  • Partial updates are valid
  • Addresses and ID numbers present will replace existing ones
  • Takes the same request body parameters as creating an applicant
  • Applicant details can be updated between check creations
Update an applicant
1PUT /v3.1/applicants/<APPLICANT_ID> HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>
4Content-Type: application/json
5
6{
7 "first_name": "New",
8 "last_name": "Name"
9}

Delete applicant

DELETE
/v3.1/applicants/{applicant_id}

Deletes a single applicant. If successful, returns a 204 No Content response.

Sending a deletion request adds the applicant object and all associated documents, photos, videos, checks, reports and analytics data to our deletion queue. The objects will be permanently deleted from Onfido's production object storage and relational database system after a deletion delay which can be configured by emailing our client support team. After deletion, applicant details cannot be recovered or queried, and Onfido will not be able to troubleshoot. Within the delay period, the applicant can be restored. For more information about Onfido's deletion service, see our Data Deletion FAQ.

Once deleted, Onfido will not be able to carry out any troubleshooting or investigate any queries raised by the client. It is for this reason we recommend a longer deletion period, for example, a minimum of thirty days.

Delete an applicant
1DELETE /v3.1/applicants/<APPLICANT_ID> HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>

Restore applicant

POST
/v3.1/applicants/{applicant_id}/restore

Restores a single applicant scheduled for deletion. If successful, returns a 204 No Content response.

A restore request will also restore all associated documents, photos, videos, checks, reports and analytics data.

Applicants that have been permanently deleted cannot be restored.

Restore an applicant
1POST /v3.1/applicants/<APPLICANT_ID>/restore HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>

List applicants

GET
/v3.1/applicants/

Lists all applicants you've created, sorted by creation date in descending order. Returns data in the form: {"applicants": [<LIST_OF_APPLICANT_OBJECTS>]}.

Requests to this endpoint will be paginated to 20 items by default.

Query string parameters

include_deleted=true (optional): include applicants scheduled for deletion.

per_page (optional): set the number of results per page (500 at maximum). Defaults to 20.

page (optional): return specific pages. Defaults to 1.

The Link header contains pagination information. For example:

Link: [https://api.eu.onfido.com/v3.1/applicants?page=3059](https://api.eu.onfido.com/v3.1/applicants?page=3059); rel="last", [https://api.eu.onfido.com/v3.1/applicants?page=2](https://api.eu.onfido.com/v3.1/applicants?page=2); rel="next"

Possible rel values are:

NameLink relation (description)
nextNext page of results.
lastLast page of results.
firstFirst page of results.
prevPrevious page of results.

The custom X-Total-Count header gives the total resource count.

Return all applicants youve created
1GET /v3.1/applicants?page=1&per_page=5 HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>

Documents

Some reports require uploaded identity documents in order to be processed successfully.

Depending on the type of the document, we may require both sides of the image to be uploaded. See the full list of documents we support.

Documents belong to a single applicant, so they must be uploaded after an applicant has been created.

The API uses the British English spelling driving_licence.

Document object

AttributeDescription
idstring
The unique identifier of the document.
created_atdatetime
The date and time at which the document was uploaded.
hrefstring
The URI of this resource.
download_hrefstring
The URI that can be used to download the document.
file_namestring
The name of the uploaded file.
file_typestring
The file type of the uploaded file.
file_sizeinteger
The size of the file in bytes.
typestring
The type of document.
sidestring
The side of the document, if applicable. The possible values are front and back.
issuing_countrystring
The issuing country of the document, in 3-letter ISO code, specified when uploading it.
applicant_idstring
The id of the applicant to whom the document belongs.
Example document object
1HTTP/1.1 201 Created
2Content-Type: application/json
3
4{
5 "id": "<DOCUMENT_ID>",
6 "created_at": "2019-02-11T13:49:20Z",
7 "file_name": "sample_driving_licence.png",
8 "file_type": "png",
9 "file_size": 490408,
10 "type": "driving_licence",
11 "side": "front",
12 "issuing_country": null,
13 "applicant_id": "<APPLICANT_ID>",
14 "href": "/v3.1/documents/<DOCUMENT_ID>",
15 "download_href": "/v3.1/documents/<DOCUMENT_ID>/download"
16}

Document types

Identity documents

The following is a partial list of document types (i.e. type when uploading a document):

Type
national_identity_card
driving_licence
passport
voter_id
work_permit

This list is not exhaustive.

If you're unsure of the type of document you want to verify, you can submit documents with type unknown. In this case, we will attempt to classify and recognize the document type when processing a Document report.

Upload document

POST
/v3.1/documents/

Using this endpoint in a live context will cause you to send personal data to Onfido. Always make sure you inform your users about this and obtain any necessary permissions. For more information on how Onfido uses personal data, view our Privacy Policy.

Uploads a single document as part of a multipart request. Returns a document object.

We provide a sample document to test this endpoint.

Valid file formats for documents are jpg, png and pdf. The file size must be between 32KB and 10MB. Maximum supported resolution is 64MPx.

Supply side when uploading documents for optimal results.

Request body parameters

ParameterDescription
applicant_idrequired
The ID of the applicant who owns the document.
filerequired
The file to be uploaded.
typerequired
The type of document. For example, passport.
sideoptional (required for documents which have multiple sides)
Either the front or back of the document.
issuing_countryoptional (required for Proof of Address reports)
The issuing country of the document in 3-letter ISO code.
validate_image_qualityoptional
A Boolean. Defaults to false. When true the submitted image will undergo an image quality validation which may take up to 5 seconds.

Image quality

You can request image quality validation when uploading a document. It is conducted synchronously and you'll receive the result as a response to your request.

When the image passes validation, returns a document object.

When the image fails validation, returns a 422 validation_error. There can be one or more failed image quality validations for a request. The list of reasons is provided in the fields property.

If the image fails validation, you should ask the end user to retake the photo of their document.

FieldMessage
detect_blurblur detected in image
detect_cutoffcutoff document detected in image
document_detectionno document in image

Sample images to trigger various error responses can be provided.

Upload passport.png
1POST /v3.1/documents/ HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>
4Content-Type: multipart/form-data

Retrieve document

GET
/v3.1/documents/{document_id}

Retrieves a single document. Returns a document object.

1GET /v3.1/documents/<DOCUMENT_ID> HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>

List documents

GET
/v3.1/documents?applicant_id={applicant_id}

Lists all documents belonging to an applicant. Returns data in the form: {"documents": [<LIST_OF_DOCUMENT_OBJECTS>]}.

Query string parameters

applicant_id (required): the ID of the applicant ID whose documents you want to list.

List all documents for a specific applicant
1GET /v3.1/documents?applicant_id=<APPLICANT_ID> HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>

Download document

GET
/v3.1/documents/{document_id}/download

Downloads specific documents belong to an applicant. If successful, the response will be the binary data representing the image.

Download a document associated with an applicant
1GET /v3.1/documents/<DOCUMENT_ID>/download HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>

Live photos

Live photos are images of the applicant's face, typically taken at the same time as documents are provided. Some reports require uploaded live photos in order to be processed successfully.

Live photo object

AttributeDescription
idstring
The unique identifier of the live photo.
created_atdatetime
The date and time at which the live photo was uploaded.
hrefstring
The URI of this resource.
download_hrefstring
The URI that can be used to download the live photo.
file_namestring
The name of the uploaded file.
file_typestring
The file type of the uploaded file.
file_sizeinteger
The size of the file in bytes.
Example live photo object
1HTTP/1.1 201 Created
2Content-Type: application/json
3
4{
5 "id": "<LIVE_PHOTO_ID>",
6 "created_at": "2019-10-09T16:59:06Z",
7 "file_name": "<FILE_NAME>.png",
8 "file_type": "image/png",
9 "file_size": 536630,
10 "href": "/v3.1/live_photos/<LIVE_PHOTO_ID>",
11 "download_href": "/v3.1/live_photos/<LIVE_PHOTO_ID>/download"
12}

Upload live photo

POST
/v3.1/live_photos/

Using this endpoint in a live context will cause you to send personal data to Onfido. Always make sure you inform your users about this and obtain any necessary permissions. For more information on how Onfido uses personal data, view our Privacy Policy.

Uploads a live photo as part of a multipart request. Returns a live photo object.

We provide a sample photo to test this endpoint.

Valid file formats for live photos are jpg, jpeg and png. The file size must be between 32KB and 10MB. Live photos are validated at the point of upload to check that they contain exactly one face. This validation can be disabled by setting the advanced_validation argument to false.

Request body parameters

ParameterDescription
filerequired
The file to be uploaded.
applicant_idrequired
The applicant_id to associate the live photo with.
advanced_validationoptional
A Boolean which defaults to true
Validates that the live photo contains exactly one face.
Upload sample_photo.png
1POST /v3.1/live_photos/ HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>
4Content-Type: multipart/form-data

Retrieve live photo

GET
/v3.1/live_photos/{live_photo_id}

Retrieves a single live photo. Returns a live photo object.

Retrieve a single live photos object
1GET /v3.1/live_photos/<LIVE_PHOTO_ID> HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>

List live photos

GET
/v3.1/live_photos/?applicant_id={applicant_id}

Lists the live photos that belong to an applicant. Returns data in the form: {"live_photos": [<LIST_OF_LIVE_PHOTO_OBJECTS>]}.

Query string parameters

applicant_id (required): the ID of the applicant whose live photos you want to list.

List all live photo (objects) for a specific applicant
1GET /v3.1/live_photos/live_photos?applicant_id=<APPLICANT_ID> HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>

Download live photo

GET
/v3.1/live_photos/{live_photo_id}/download

Downloads a live photo. If successful, the response will be the binary data representing the image.

Download a live photo
1GET /v3.1/live_photos/<LIVE_PHOTO_ID>/download HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>

Live videos

Live videos are footage of the applicant's face, recorded and uploaded by the Onfido Smart Capture SDKs (iOS, Android or Web), at the same time as the document image is captured—also by the SDKs. These videos are used for Facial Similarity Video reports.

Live video object

During the video recording end users are asked to perform randomly generated actions, represented in challenge. Challenges always have 2 parts recite and movement, but the order in which these happen can vary. The order of the challenges is maintained in the live video object. recite asks the user to say 3 randomly generated digits, whereas movement asks the user to look over their right or left shoulder.

AttributeDescription
idstring
The unique identifier of the live video.
created_atdatetime
The date and time at which the live video was uploaded.
hrefstring
The URI of this resource.
download_hrefstring
The URI that can be used to download the live video.
file_namestring
The name of the uploaded file.
file_typestring
The file type of the uploaded file.
file_sizeinteger
The size of the file in bytes.
challengearray of objects
Challenge the end user was asked to perform during the video recording.
Example live video object
1HTTP/1.1 201 Created
2Content-Type: application/json
3
4{
5 "id": "<LIVE_VIDEO_ID>",
6 "created_at": "2018-05-14T16:44:53Z",
7 "href": "/v3.1/live_videos/<LIVE_VIDEO_ID>",
8 "download_href": "/v3.1/live_videos/<LIVE_VIDEO_ID>/download",
9 "file_name": "<FILE_NAME>.mp4",
10 "file_type": "video/mp4",
11 "file_size": 1431121,
12 "challenge": [
13 {
14 "type": "recite",
15 "query": [
16 1,
17 2,
18 3
19 ]
20 },
21 {
22 "type": "movement",
23 "query": "turnRight"
24 }
25 ]
26}

Upload live video

Live videos can only be uploaded via one of Onfido's input-capture SDKs, not via the API directly.

As a result, Onfido does not provide an upload live video endpoint.

To upload live videos for Facial Similarity Video reports, integrate with one of our Smart Capture SDKs (iOS, Android or Web).

Retrieve live video

GET
/v3.1/live_videos/{live_video_id}

Retrieves a single live video. Returns the corresponding live video object.

Retrieve a single live videos object
1GET /v3.1/live_videos/<LIVE_VIDEO_ID> HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>

List live videos

GET
/v3.1/live_videos?applicant_id={applicant_id}

Lists all the live videos that belong to an applicant.

Returns data in the form: {"live_videos": [<LIST_OF_LIVE_VIDEO_OBJECTS>]}.

Query string parameters

applicant_id (required): the ID of the applicant whose live videos you want to list.

List all live videos for a specific applicant
1GET /v3.1/live_videos?applicant_id=<APPLICANT_ID> HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>

Download live video

GET
/v3.1/live_videos/{live_video_id}/download

Downloads a live video. Returns the binary data representing the video.

Download the data representing a live video
1GET /v3.1/live_videos/<LIVE_VIDEO_ID>/download HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>

Download live video frame

GET
/v3.1/live_videos/{live_video_id}/frame

Instead of the whole video, a single frame can be downloaded using this endpoint. Returns the binary data representing the frame.

This will be the frame extracted from the video where the end user is facing the camera. If no face can be detected, it will fallback to the first frame of the video.

Download the data representing a live video frame
1GET /v3.1/live_videos/<LIVE_VIDEO_ID>/frame HTTP/1.1
2Host: api.eu.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>

Unsuccessful frame extraction

Frame extraction failed

If a frame cannot be extracted from the live video, a frame_extraction_failed response will be returned.

Unsuccessful frame extraction response: failure
1HTTP/1.1 422 Unprocessable Entity
2Content-Type: application/json
3
4{
5 "error": {
6 "type": "frame_extraction_failed",
7 "message": "<Reason>"
8 }
9}

Frame extraction unavailable

If the extraction feature is temporarily unavailable, a frame_extraction_unavailable response will be returned instead.

Unsuccessful frame extraction response: temporarily unavailable
1HTTP/1.1 503 Service Unavailable
2Content-Type: application/json
3
4{
5 "error": {
6 "type": "frame_extraction_unavailable",
7 "message": "Frame extraction is temporarily unavailable"
8 }
9}

Motion captures

Motion captures are representations of an applicant's face, recorded and uploaded by the Onfido Smart Capture SDKs (iOS, Android or Web), at the same time as the document image is captured—also by the SDKs. These captures are used for Facial Similarity Motion reports.

Motion capture object

AttributeDescription
idstring
The unique identifier of the motion capture.
created_atdatetime (ISO-8601)
The date and time at which the motion capture was uploaded.
hrefstring
The URI of this resource.
download_hrefstring
The URI that can be used to download a motion capture.
file_namestring
The name of the uploaded file.
file_typestring
The file type of the uploaded file.
file_sizeinteger
The size of the file in bytes.
Example motion capture object
1HTTP/1.1 201 Created
2Content-Type: application/json
3
4{
5 "id": "<MOTION_CAPTURE_ID>",
6 "created_at": "2022-11-12T17:12:44Z",
7 "href": "/v3.1/motion_captures/<MOTION_CAPTURE_ID>",
8 "download_href": "/v3.1/motion_captures/<MOTION_CAPTURE_ID>/download",
9 "file_name": "<FILE_NAME>.mp4",
10 "file_type": "video/mp4",
11 "file_size": 1431121
12}

Upload motion capture

Motion captures can only be uploaded via one of Onfido's input-capture SDKs, not via the API directly.

As a result, Onfido does not provide an upload motion capture endpoint.

To upload motion captures for Facial Similarity Motion reports, integrate with one of our Smart Capture SDKs (iOS, Android or Web).

Retrieve motion capture

GET
https://api.onfido.com/v3.1motion_captures/{motion_capture_id}

Retrieves a single motion capture. Returns the corresponding motion capture object.

Retrieve a single motion capture object
1GET /v3.1/motion_captures/<MOTION_CAPTURE_ID> HTTP/1.1
2Host: api.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>

List motion captures

GET
https://api.onfido.com/v3.1/motion_captures?applicant_id={applicant_id}

Lists all the motion captures that belong to an applicant.

Returns data in the form: {"motion_captures": [<LIST_OF_MOTION_CAPTURE_OBJECTS>]}.

Query string parameters

applicant_id (required): the ID of the applicant whose motion captures you want to list.

List all motion captures for a specific applicant
1GET /v3.1/motion_captures?applicant_id=<APPLICANT_ID> HTTP/1.1
2Host: api.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>

Download motion capture

GET
https://api.onfido.com/v3.1/motion_captures/{motion_capture_id}/download

Downloads a motion capture. Returns the binary data representing the motion capture.

Download the data representing a motion capture
1GET /v3.1/motion_captures/<MOTION_CAPTURE_ID>/download HTTP/1.1
2Host: api.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>

Download motion capture frame

GET
https://api.onfido.com/v3.1/motion_captures/{motion_capture_id}/frame

Instead of the whole motion capture data, a single frame can be downloaded using this endpoint. Returns the binary data representing the frame.

Download the data representing a motion capture frame
1GET /v3.1/motion_captures/<MOTION_CAPTURE_ID>/frame HTTP/1.1
2Host: api.onfido.com
3Authorization: Token token=<YOUR_API_TOKEN>

Unsuccessful frame extraction

Frame extraction failed

If a frame cannot be extracted from the motion capture, a frame_extraction_failed response will be returned.

Unsuccessful frame extraction response: failure
1HTTP/1.1 422 Unprocessable Entity
2Content-Type: application/json
3
4{
5 "error": {
6 "type": "frame_extraction_failed",
7 "message": "<Reason>"
8 }
9}

Frame extraction unavailable

If the extraction feature is temporarily unavailable, a frame_extraction_unavailable response will be returned instead.

Unsuccessful frame extraction response: temporarily unavailable
1HTTP/1.1 503 Service Unavailable
2Content-Type: application/json
3
4{
5 "error": {
6 "type": "frame_extraction_unavailable",
7 "message": "Frame extraction is temporarily unavailable"
8 }
9}

Report Types

Document report

For a general introduction to the Document report, you can read our product documentation.

After you've familiarised yourself with the information here, you can read our guide on suggested client actions for different result scenarios.

There are 5 different types of Document reports:

Request body in APINotes
"report_names": ["document"]Primary Document report
"report_names": ["document_video"]Document Video report
"report_names": ["document_with_address_information"]In beta
"report_names": ["document_video_with_address_information"]In beta
"report_names": ["document_with_driving_licence_information"]In beta

Document with Address Information, Document Video with Address Information and Document with Driving Licence Information are in beta. They are supersets of the Document report which add functionality for specific use cases. Contact your account manager for more information about the features in these beta reports.

By default, the most recently uploaded document will be used.

To specify which uploaded document to run the Document report against in the API, use the document_ids field. This takes an array of up to 2 strings (2 document IDs):

"document_ids": ["<DOCUMENT_ID>"]

The Document report is composed of data integrity, visual authenticity and police record checks. It checks the internal and external consistency of the document provided by the applicant to identify potential discrepancies.

In addition, any data extracted from the document through OCR is returned in the properties attribute.

The Document report combines software and an expert team to maximise fraud detection. The majority of documents will be processed instantly. However, when document analysis falls back to expert review, the report status will be delivered asynchronously via webhook notifications.

Expert review is required when we encounter images that use sophisticated counterfeiting techniques, or the image is of poor quality (blurred, low resolution, obscured, cropped, or held at an unreadable angle).

Supported Documents

In your Onfido Dashboard, you can configure which documents you want to accept in your verification workflow, filtering according to issuing country and document type.

When an applicant submits a restricted document (i.e. a document not included in your supported documents), the Supported document breakdown of the Document Report will flag as consider, producing a sub-result of reject.

Required applicant data

For Document reports, first_name and last_name must be provided but can be sample values if you don't know an applicant's name.

Document type and issuing country

If you’re creating a check containing a Document report, we do not validate that the properties type and issuing_country in the uploaded document match extracted values (which are returned in the Document report object).

Document report: Object

Our newly expanded OpenAPI specification is also a resource for understanding the Document report response object structure.

We host a separate page which contains a detailed description of the Document report object values from an API user's perspective.

Results

The result field indicates the overall report result. Possible values for Document reports are clear and consider:

Report resultDescription
clearIf all underlying verifications pass, the overall result will be clear.
considerIf the report has returned information that needs to be evaluated, the overall result will be consider.

Sub-results

The sub_result field indicates a more detailed result, and is unique to Document reports. Possible values of sub_result are as follows:

Sub-resultDescription
clearIf all underlying verifications pass, the overall sub result will be clear. There are no indications the document is fraudulent.
cautionWe can't successfully complete all verifications, but this doesn’t necessarily point to a suspected document (for example, expired document).
suspectedDocument shows signs of suspect fraud.
rejectedWe can't process the document image, or the document isn't supported by Onfido for processing. Another reason is if the age of the applicant is too low (the standard threshold is 16 years old but you can write to your Onfido contact to have this changed).

Document report: Breakdowns

Breakdowns can have the values clear and consider.

A breakdown will have the result consider when at least one sub-breakdown contains a consider or unidentified result. For example, a consider result for the mrz sub-breakdown will produce a consider result for the data_validation breakdown. This will then also set the report sub_result value to suspected.

Some breakdowns contain sub-breakdowns. For example, the image_integrity breakdown comprises the sub-breakdowns supported_document, image_quality, colour_picture and conclusive_document_quality.

The possible values for sub-breakdowns are clear, consider, null and unidentified.

Breakdown order priority

Breakdown sub-results have the following order of priority:

rejected->suspected->caution->clear

For example, a caution sub-result will only ever be asserted when the following conditions are met:

  • no individual breakdown has caused a rejected or suspected sub-result
  • a breakdown which maps to a caution sub-result has been flagged

Breakdown mapping

Breakdowns and sub-breakdowns are mapped to particular sub-results. Certain mappings can be changed, where possible, depending on your configuration.

See our Document report breakdown tree for an illustration of this logic:

Diagram showing the possible breakdowns and sub-breakdowns for a Document report.

Note: Some breakdowns have sub-breakdowns that are mapped to different sub-results. For example, in the Data Validation breakdown, gender, document_numbers, expiry_date, date_of_birth and mrz map to Suspected whereas document_expiration maps to Caution. Note: When a sub-breakdown mapped to a rejected sub-result is flagged, all other breakdowns and the document properties will be omitted from the response object.

Breakdown descriptions and logic

data_comparison:

Establishes whether the data provided by the applicant matches the data extracted from the document. This breakdown is only returned if Comparison Checks are enabled for your account. Otherwise, the breakdown and its sub-breakdowns are returned as null and will not affect the final report result. To enable Comparison Checks, please contact Client Support.

We compare the following fields:

  • first_name
  • last_name
  • date_of_birth
  • gender

first_name and last_name can be configured to use a fuzzy or exact mechanism for the comparison. We take into account all available names for comparison, including spouse, widow or alias names.

date_of_birth and gender will always be compared using an exact mechanism.

Fuzzy comparison

Fuzzy comparison allows for greater flexibility during comparison, catering for discrepancies which may occur, for example, when an applicant uses their middle or spouse name, or there's been an extraction error.

Note:

  • When an applicant hasn’t provided data the sub-breakdown result is null for the missing field
  • When an applicant has provided names but names have not been extracted from the document, the sub-breakdown result is consider
  • When an applicant has provided date of birth and/or gender, but these fields have not been extracted from the document, the sub-breakdown result is null

Any other sub-breakdowns present under data_comparison in the document report object exist only for legacy reasons.

data_validation:

Asserts whether the format and length of the fields are correct for that document type. Uses the following sub-breakdowns:

  • gender
  • date_of_birth
  • document_numbers
  • document_expiration 1
  • expiry_date 2
  • mrz
  1. If this is flagged, the document has expired. Onfido uses UTC as a fixed reference point for the current date and time when the dates are compared.
  2. If this is flagged, the expiration date has the incorrect format or the date is in the past.

age_validation:

Asserts whether the age calculated from the document’s date of birth data point is greater than or equal to the minimum accepted age set at account level. The default minimum accepted age is 18 years. Configurable to set a different minimum age value. Onfido uses UTC as a fixed reference point for the current date and time when the applicant's age is calculated.

Uses the following sub-breakdown:

  • minimum_accepted_age

image_integrity:

Asserts whether the document was of sufficient quality to verify. Uses the following sub-breakdowns:

  • image_quality:

    Asserts whether the quality of the image was sufficient for processing.

  • conclusive_document_quality:

    A result of clear for this sub-breakdown will assert if the document was of enough quality to be able to perform a fraud inspection. A result of consider will mean that even if sub breakdowns of visual_authenticity fail, we cannot positively say the document is fraudulent or not (in cases such as parts of the document are not visible).

  • supported_document:

    Asserts whether the submitted document is supported. Takes value of clear or unidentified.

  • colour_picture:

    Asserts whether the image was a colour one. A black and white picture will map to a caution Document report sub-result. Configurable to map to rejected.

visual_authenticity:

Asserts whether visual (non-textual) elements are correct given the document type. Uses the following sub-breakdowns:

  • fonts:

    Fonts in the document don’t match the expected ones.

  • picture_face_integrity:

The pictures of the person identified on the document show signs of tampering or alteration. In most cases this will focus on the primary picture yet it may also apply to the secondary and tertiary pictures when documents contain them.

  • template:

    The document doesn’t match the expected template for the document type and country it is from.

  • security_features:

    Security features expected on the document are missing or wrong.

  • original_document_present:

    The document was not present when the photo was taken. For example, a photo of a photo of a document or a photo of a computer screen. Configurable to map to caution instead of suspected.

  • digital_tampering:

    Indication of digital tampering in the image (for example, name altered).

  • other:

    This sub-breakdown is returned for backward compatibility reasons. Its value will be consider when at least one of the other breakdowns is consider, and clear when all the other breakdowns are clear.

  • face_detection:

    No face was detected on the document.

data_consistency:

  • data_consistency:

    Asserts whether data represented in multiple places on the document is consistent. For example, between MRZ lines and OCR extracted text on passports. Uses the following sub-breakdowns:

    • multiple_data_sources_present1
    • document_type
    • gender
    • date_of_expiry
    • nationality
    • issuing_country
    • document_numbers
    • date_of_birth
    • last_name
    • first_name
  1. multiple_data_sources_present is for cases where we don’t obtain a US barcode because it wasn’t extracted, wasn’t decoded, or wasn’t there at all (e.g. if the back of the document wasn’t available). It acts as a validation for the data_consistency breakdown: if 2 sources are present, then data consistency is possible and the other sub-breakdowns are enabled. multiple_data_sources_present can be disabled if needed. In this case, it will be returned as null and have no impact on the sub-result.

police_record:

Asserts whether the document has been identified as lost, stolen or otherwise compromised. Applies to all documents that have been reported as stolen or fraudulent to the UK Metropolitan Police.

This breakdown is only returned if Police Record Checks are enabled for your account. Otherwise, the breakdown and its sub-breakdowns are returned as null and will not affect the final report result. To enable Police Record Checks, please contact Client Support.

compromised_document:

Asserts whether the image of the document has been found in our internal database of compromised documents.

Document report: Breakdown reasoning

We will return a reason whenever a report flags for one of the following breakdowns:

  • visual_authenticity : original_document_present

  • image_integrity : conclusive_document_quality

  • image_integrity : image_quality

This works by returning the contributing reason and corresponding fail result (a consider result) in the breakdown properties.

There can be more than one reason per breakdown, as they aren’t mutually exclusive.

All other signals and potential reasons will be omitted.

The following diagram illustrates this logic:

Diagram showing the possible reasons for a Document report to be flagged.

Original Document Present reasons:

photo_of_screen - When we can see that the applicant's document is on a physical screen or device, e.g. when the device is visible, software applications are seen, a computer cursor is present, or the pixels on the image appearing to have a different texture than expected

screenshot - When the applicant has used their mobile phone, tablet, or computer to take a photo within the device, e.g. when software applications are seen, the time and mobile provider are visible, or any digitally added component that wouldn't be seen on a physical document, such as an upload icon

document_on_printed_paper - when the applicant has previously captured an image of the document, printed it out, and has now taken a photo of this print out to upload, e.g. when the edges of the paper are visible, when there are fold creases on the paper, or the document's edges blending into the background and appearing flat

scan - When the document has clearly been captured using a scanner and there are visible indicators of this, e.g. unusual shadows on the edges of the document, or written text around the document

Conclusive Document Quality reasons:

obscured_data_points - This refers to when data points are obscured to the point that we cannot confirm if the fonts match the expected ones

obscured_security_features - This refers to whenever a critical security feature is obscured. This can also refer to when the holder's wet signature, necessary for the document to be valid, is not present

abnormal_document_features - This refers to when something other than obscuration of data points and security features makes the document insufficient to be assessed (i.e. poor image resolution, poor lighting, distortions due to capturing devices, misalignment due to cracks, visual alterations due to cases/laminates, some stickers etc.)

watermarks_digital_text_overlay - Any digital text or electronic watermarks on the document

corner_removed - If the corner has been physically cut off. This can be found on some documents that are no longer valid

punctured_document - A punched hole is present. This can be found on DLs that are no longer valid, for example

missing_back - When the back of a document is needed for processing (e.g. for key data points to extract), but is not available (e.g. if the same front was uploaded twice)

digital_document - When a document has been published digitally, there aren’t enough security features to review so we cannot perform a full fraud assessment

Image Quality reasons:

dark_photo - When an image of the document is too dark to be able to see data points

glare_on_photo - When there is light reflecting on the document causing glare to obstruct data points

blurred_photo - When data points are blurred and no reference can be made elsewhere in the document or if the data points are too blurry and 'they could be something else' (e.g. "I" could be "1", "B" could be "8")

covered_photo - When data points have been covered either by the applicant or by another object such as a sticker

other_photo_issue - Any other reason not listed, such as when holograms are obscuring data points

damaged_document - When a document is damaged and we are unable to make out data points

incorrect_side - When the incorrect side of a document has been uploaded, and we have not received the front

cut_off_document - When data points are not included in the image due to the document being cut off (i.e. out of the frame of the image)

no_document_in_image - If no document has been uploaded or there is a blank image

two_documents_uploaded - When 2 different documents are submitted in the same check

Example Document report object
1HTTP/1.1 201 Created
2Content-Type: application/json
3
4{
5 "breakdown": {
6 "age_validation": {
7 "breakdown": {
8 "minimum_accepted_age": {
9 "properties": {},
10 "result": "clear"
11 }
12 },
13 "result": "clear"
14 },
15 "compromised_document": {
16 "result": "clear"
17 },
18 "data_comparison": {
19 "breakdown": {
20 "date_of_birth": {
21 "properties": {},
22 "result": "clear"
23 },
24 "date_of_expiry": {
25 "properties": {},
26 "result": "null"
27 },
28 "document_numbers": {
29 "properties": {},
30 "result": "null"
31 },
32 "document_type": {
33 "properties": {},
34 "result": "null"
35 },
36 "first_name": {
37 "properties": {},
38 "result": "clear"
39 },
40 "gender": {
41 "properties": {},
42 "result": "null"
43 },
44 "issuing_country": {
45 "properties": {},
46 "result": "null"
47 },
48 "last_name": {
49 "properties": {},
50 "result": "clear"
51 }
52 },
53 "result": "clear"
54 },
55 "data_consistency": {
56 "breakdown": {
57 "date_of_birth": {
58 "properties": {},
59 "result": "clear"
60 },
61 "date_of_expiry": {
62 "properties": {},
63 "result": "clear"
64 },
65 "document_numbers": {
66 "properties": {},
67 "result": "clear"
68 },
69 "document_type": {
70 "properties": {},
71 "result": "clear"
72 },
73 "first_name": {
74 "properties": {},
75 "result": "clear"
76 },
77 "gender": {
78 "properties": {},
79 "result": "clear"
80 },
81 "issuing_country": {
82 "properties": {},
83 "result": "clear"
84 },
85 "last_name": {
86 "properties": {},
87 "result": "clear"
88 },
89 "multiple_data_sources_present": {
90 "properties": {},
91 "result": "clear"
92 },
93 "nationality": {
94 "properties": {},
95 "result": "clear"
96 }
97 },
98 "result": "clear"
99 },
100 "data_validation": {
101 "breakdown": {
102 "date_of_birth": {
103 "properties": {},
104 "result": "clear"
105 },
106 "document_expiration": {
107 "properties": {},
108 "result": "clear"
109 },
110 "document_numbers": {
111 "properties": {},
112 "result": "clear"
113 },
114 "expiry_date": {
115 "properties": {},
116 "result": "clear"
117 },
118 "gender": {
119 "properties": {},
120 "result": "clear"
121 },
122 "mrz": {
123 "properties": {},
124 "result": "clear"
125 }
126 },
127 "result": "clear"
128 },
129 "image_integrity": {
130 "breakdown": {
131 "colour_picture": {
132 "properties": {},
133 "result": "clear"
134 },
135 "conclusive_document_quality": {
136 "properties": {},
137 "result": "clear"
138 },
139 "image_quality": {
140 "properties": {},
141 "result": "clear"
142 },
143 "supported_document": {
144 "properties": {},
145 "result": "clear"
146 }
147 },
148 "result": "clear"
149 },
150 "police_record": {
151 "result": "clear"
152 },
153 "visual_authenticity": {
154 "breakdown": {
155 "digital_tampering": {
156 "properties": {},
157 "result": "clear"
158 },
159 "face_detection": {
160 "properties": {},
161 "result": "clear"
162 },
163 "fonts": {
164 "properties": {},
165 "result": "clear"
166 },
167 "original_document_present": {
168 "properties": {},
169 "result": "clear"
170 },
171 "other": {
172 "properties": {},
173 "result": "clear"
174 },
175 "picture_face_integrity": {
176 "properties": {},
177 "result": "clear"
178 },
179 "security_features": {
180 "properties": {},
181 "result": "clear"
182 },
183 "template": {
184 "properties": {},
185 "result": "clear"
186 }
187 },
188 "result": "clear"
189 }
190 },
191 "check_id": "<CHECK_ID>",
192 "created_at": "2021-03-22T17:13:12Z",
193 "documents": [
194 {
195 "id": "<DOCUMENT_ID>"
196 }
197 ],
198 "href": "/v3.1/reports/<REPORT_ID>",
199 "id": "<REPORT_ID>",
200 "name": "document",
201 "properties": {
202 "date_of_birth": "1990-01-01",
203 "date_of_expiry": "2030-01-01",
204 "document_numbers": [
205 {
206 "type": "document_number",
207 "value": "999999999"
208 }
209 ],
210 "document_type": "passport",
211 "first_name": "Jane",
212 "gender": "",
213 "issuing_country": "GBR",
214 "last_name": "Doe",
215 "nationality": ""
216 },
217 "result": "clear",
218 "status": "complete",
219 "sub_result": "clear"
220}

Document video report

For a general introduction to the Document Video Report, you can read our product documentation.

To request a Document Video Report as part of a check in the API, use the report_names field (which takes an array of strings):

"report_names": ["document_video"]

Document video report: Breakdown reasoning

The image_integrity breakdown of the Document Video Report response includes a video_document_presence sub-breakdown, which has the results clear and unidentified.

video_document_presence also has a property, called invalid_signature. If the media signature of a recorded video is not valid, the property will return consider, and the sub-breakdown will return unidentified. In this case, the Document Video Report will be rejected.

With a clear report result, the following snippet is an example showing what is added to the Document report response object:

json
1"image_integrity": {
2 "breakdown": {
3 "video_document_presence": {
4 "properties": {},
5 "result": "clear"
6 }
7 },
8 "result": "clear"
9 },

BETA Document report options

Document with Address Information

This report is in beta. Contact your account manager for more information about the features in this report.

To request a Document with Address Information report as part of a check in the API, use the report_names field (which takes an array of strings):

"report_names": ["document_with_address_information"]

By default, the most recently uploaded document will be used.

If you use this report, Onfido will use a third-party subprocessor for address cleansing after the address has been extracted.

To specify which uploaded document to run the Document with Address Information report against in the API, use the document_ids field. This takes an array of up to 2 strings (2 document IDs):

"document_ids": ["<DOCUMENT_ID>"]

For a clear result, the following snippet is an example showing what is added to the Document report response object:

bash
1...
2 "address_lines": {
3 "city": "EDINBURGH",
4 "country": "United Kingdom (UK)",
5 "postal_code": "EH1 9GP",
6 "state": "",
7 "street_address": "122 BURNS CRESCENT",
8 "country_code": "GBR"
9 },
10 "address": "<ADDRESS_STRING>",
11...

Contact your account manager for more information about the features in the Document with Address Information report.

Document Video Report with Address Information

This report is in beta. Contact your account manager for more information about the features in this report.

To request a Document Video with Address Information report as part of a check in the API, use the report_names field (which takes an array of strings):

"report_names": ["document_video_with_address_information"]

By default, the most recently uploaded document will be used.

If you use this report, Onfido will use a third-party subprocessor for address cleansing after the address has been extracted.

To specify which uploaded document to run the Document Video with Address Information report against in the API, use the document_ids field. This takes an array of up to 2 strings (2 document IDs):

"document_ids": ["<DOCUMENT_ID>"]

For a clear result, the following snippet is an example showing what is added to the Document report response object:

json
1...
2 "address_lines": {
3 "city": "EDINBURGH",
4 "country": "United Kingdom (UK)",
5 "postal_code": "EH1 9GP",
6 "state": "",
7 "street_address": "122 BURNS CRESCENT",
8 "country_code": "GBR"
9 },
10 "address": "<ADDRESS_STRING>",
11...

Contact your account manager for more information about the features in the Document Video with Address Information report.

Document with Driving Licence Information

This report is in beta. Contact your account manager for more information about the features in this report.

To request a Document with Driving Licence Information report as part of a check in the API, use the report_names field (which takes an array of strings):

"report_names": ["document_with_driving_licence_information"]

By default, the most recently uploaded document will be used.

To specify which uploaded document to run the Document with Driving Licence Information report against in the API, use the document_ids field. This takes an array of up to 2 strings (2 document IDs):

"document_ids": ["<DOCUMENT_ID>"]

For a clear result, the following snippet is an example showing what is added to the Document report response object:

json
1...
2"driving_licence_information": [
3 {
4 "category": "A",
5 "codes": "79.03,79.04",
6 "expiry_date": "<YYYY-MM-DD>",
7 "obtainment_date": "<YYYY-MM-DD>"
8 },
9 {
10 "category": "A1",
11 "codes": "79.03,79.04",
12 "expiry_date": "<YYYY-MM-DD>",
13 "obtainment_date": "<YYYY-MM-DD>"
14 },
15 {
16 "category": "AM",
17 "codes": "",
18 "expiry_date": "<YYYY-MM-DD>",
19 "obtainment_date": "<YYYY-MM-DD>"
20 },
21 {
22 "category": "B",
23 "codes": "",
24 "expiry_date": "<YYYY-MM-DD>",
25 "obtainment_date": "<YYYY-MM-DD>"
26 }
27 ],
28...

The report must be completed using a manual only review process to guarantee the driving license data is extracted.

Contact your account manager for more information about the features in the Document with Driving Licence Information report.

Facial Similarity reports

This section contains API documentation for the Facial Similarity reports. You can also read our product documentation.

After you've familiarised yourself with the information here, you can read our guide on [suggested client guide/facial-similarity-reports/#suggested-client-actions) for different result scenarios.

Creating a check with a Facial Similarity report will cause you to process facial biometric personal data. Always make sure you inform your users about this and obtain any necessary permissions. For more information on how Onfido uses personal data, view our Privacy Policy.

There are 4 different types of Facial Similarity report:

Report nameRequest body in API
Photo"report_names": ["facial_similarity_photo"]
Photo Fully Auto"report_names": ["facial_similarity_photo_fully_auto"]
Video"report_names": ["facial_similarity_video"]
Motion"report_names": ["facial_similarity_motion"]

All Facial Similarity reports will compare the most recent live photo, live video or motion capture provided by the applicant to the face on the specified document provided during check creation in the document_ids field.

"document_ids": ["<DOCUMENT_ID>"]

By default, the most recently uploaded document specified will be used. Where the document has two sides, we will search both sides of the document for a face.

If unspecified, the most recently uploaded document will be used.

When side is not specified, it will take a default value of front. We recommend that all documents contain the side attribute, as this minimises the cases where the back of the document is used for comparison and thus failed as no face is detected.

Required applicant data

For all Facial Similarity report types, first_name and last_name must be provided but can be sample values if you don't know an applicant's name.

Facial Similarity Photo

If applicant_provides_data is true, the Facial Similarity Photo report needs to be paired with a Document report.

Facial Similarity Photo: Object

The following table describes the unique fields returned in this version of the Onfido API for a completed Facial Similarity Photo report:

AttributeFormatPossible values
resultString"clear", "consider"
image_integrityString or null"clear", "consider", null
(sub-breakdown) face_detectedString or null"clear", "consider", null
(sub-breakdown) source_integrity1String or null"clear", "consider", null
face_comparisonString or null"clear", "consider", null
(sub-breakdown) face_match2String or null"clear", "consider", null
visual_authenticityString or null"clear", "consider", null
(sub-breakdown) spoofing_detection3String or null"clear", "consider", null

1: source_integrity may contain reasons under the properties bag (see Facial Similarity Photo: Source Integrity)

2: face_match contains a score value under the properties bag (see Facial Similarity Photo: Face Match Score)

3: spoofing_detection contains a score value under the properties bag (see Facial Similarity Photo: Spoofing Detection Score)

A breakdown or sub-breakdown will have the result null when it has not been completed. This occurs when it is not available, or has failed to process the media due to a timeout or an internal error. In this case, the report will go to manual review.

Facial Similarity Photo: Breakdowns

BreakdownDescription
image_integrityobject
Asserts whether the quality and integrity of the uploaded files were sufficient to perform a face comparison.
(sub-breakdown) face_detectedobject
Asserts a single face of good enough quality has been found in both the document image and the live photo.
(sub-breakdown) source_integrityobject
Asserts whether the live photo is trustworthy - i.e. not digitally tampered, from a fake webcam, or from other dubious sources.
face_comparisonobject
Asserts whether the face in the document matches the face in the live photo.
(sub-breakdown) face_matchobject
Contains a score value under the properties bag (see Facial Similarity Photo: Match Score).
visual_authenticityobject
Asserts whether the person in the live photo is real (not a spoof).
(sub-breakdown) spoofing_detectionobject
Contains a score value under the properties bag (see Facial Similarity Photo: Spoofing Detection Score).

Facial Similarity Photo: Source Integrity

We will return a reason whenever a report flags for source_integrity. This works by returning the contributing reason and a consider result in the source_integrity breakdown properties. There can be more than one reason, because they aren’t mutually exclusive. All other signals and potential reasons will be omitted.

For Facial Similarity Photo, the source_integrity sub-breakdown is composed of the following properties:

  • digital_tampering - when evidence is found that the image was manipulated by Photoshop, or other software
  • fake_webcam - when evidence is found that a fake webcam was used
  • time_of_capture - when evidence is found that the live photo was taken more than 24 hours before live photo upload
  • emulator - when evidence is found that an Android emulator was used
  • sanctioned_document_country - when a document is issued by a country subject to comprehensive US sanctions (you can find the list of countries here). The report (either in conjunction with or separate from a document report) will return a consider result, accompanied by a reasons property clarifying that it is not supported due to sanctions
  • reasons - additional comma separated details such as the exact digital tampering software used, or the name of the fake webcam

Facial Similarity Photo: Face Match Score

The face_match breakdown contains a properties object with a score value. This score is a floating point number between 0 and 1 that expresses how similar the two faces are, where 1 is a perfect match.

If the face matching algorithm fails to detect a face, the score property will not be present and the face matching task will be done manually. The score only measures how similar the faces are, and does not make an assessment of the nature of the photo. If spoofing (such as photos of printed photos or photos of digital screens) is detected the applicant will be rejected independently of the face match score.

Facial Similarity Photo: Spoofing Detection Score

The spoofing_detection breakdown contains a properties object with a score value. This score is a floating point number between 0 and 1. The closer the score is to 0, the more likely it is to be a spoof (i.e. photos of printed photos, or photos of digital screens). Conversely, the closer it is to 1, the less likely it is to be a spoof.

Example Facial Similarity Photo report object
1HTTP/1.1 201 Created
2Content-Type: application/json
3
4{
5 "created_at": "2019-12-11T09:39:05Z",
6 "href": "/v3.1/reports/<REPORT_ID>",
7 "id": "<REPORT_ID>",
8 "name": "facial_similarity_photo",
9 "properties": {},
10 "result": "clear",
11 "status": "complete",
12 "sub_result": null,
13 "breakdown": {
14 "face_comparison": {
15 "result": "clear",
16 "breakdown": {
17 "face_match": {
18 "result": "clear",
19 "properties": {
20 "score": 0.6512
21 }
22 }
23 }
24 },
25 "image_integrity": {
26 "result": "clear",
27 "breakdown": {
28 "face_detected": {
29 "result": "clear",
30 "properties": {}
31 },
32 "source_integrity": {
33 "result": "clear",
34 "properties": {}
35 }
36 }
37 },
38 "visual_authenticity": {
39 "result": "clear",
40 "breakdown": {
41 "spoofing_detection": {
42 "result": "clear",
43 "properties": {
44 "score": 0.9512
45 }
46 }
47 }
48 }
49 },
50 "check_id": "<CHECK_ID>",
51 "documents": []
52}

Photo Fully Auto

If applicant_provides_data is true, the Photo Fully Auto report needs to be paired with a Document report.

Photo Fully Auto: Object

The following table describes the unique fields returned in this version of the Onfido API for a completed Photo Fully Auto report:

AttributeFormatPossible values
resultString"clear", "consider"
image_integrityString or null"clear", "consider", null
(sub-breakdown) face_detectedString or null"clear", "consider", null
(sub-breakdown) source_integrity1String or null"clear", "consider", null
face_comparisonString or null"clear", "consider", null
(sub-breakdown) face_match2String or null"clear", "consider", null
visual_authenticityString or null"clear", "consider", null
(sub-breakdown) spoofing_detection3String or null"clear", "consider", null

1: source_integrity may contain reasons under the properties bag (see Source Integrity for Photo Fully Auto)

2: face_match contains a score value under the properties bag (see Face Match Score for Photo Fully Auto)

3: spoofing_detection contains a score value under the properties bag (see Spoofing Detection Score for Photo Fully Auto)

Photo Fully Auto: Breakdowns

BreakdownDescription
image_integrityobject
Asserts whether the quality and integrity of the uploaded files were sufficient to perform a face comparison.
(sub-breakdown) face_detectedobject
Asserts a single face of good enough quality has been found in both the document image and the live photo.
(sub-breakdown) source_integrityobject
Asserts whether the live photo is trustworthy - i.e. not digitally tampered, from a fake webcam, or from other dubious sources.
face_comparisonobject
Asserts whether the face in the document matches the face in the live photo.
(sub-breakdown) face_matchobject
Contains a score value under the properties bag (see Face Match Score for Fully Auto).
visual_authenticityobject
Asserts whether the person in the live photo is real (not a spoof).
(sub-breakdown) spoofing_detectionobject
Contains a score value under the properties bag (see Spoofing Detection Score for Fully Auto).

Photo Fully Auto: Source Integrity

We will return a reason whenever a report flags for source_integrity. This works by returning the contributing reason and a consider result in the source_integrity breakdown properties. There can be more than one reason, because they aren’t mutually exclusive. All other signals and potential reasons will be omitted.

For Photo Fully Auto, the source_integrity sub-breakdown is composed of the following properties:

  • digital_tampering - when evidence is found that the image was manipulated by Photoshop, or other software
  • fake_webcam - when evidence is found that a fake webcam was used
  • time_of_capture - when evidence is found that the live photo was taken more than 24 hours before live photo upload
  • emulator - when evidence is found that an Android emulator was used
  • sanctioned_document_country - when a document is issued by a country subject to comprehensive US sanctions (you can find the list of countries here). The report (either in conjunction with or separate from a document report) will return a consider result, accompanied by a reasons property clarifying that it is not supported due to sanctions
  • reasons - additional comma separated details such as the exact digital tampering software used, or the name of the fake webcam

Photo Fully Auto: Face Match Score

The face_match breakdown contains a properties object with a score value. This score is a floating point number between 0 and 1 that expresses how similar the two faces are, where 1 is a perfect match.

If the face matching algorithm fails to detect a face, the score property will not be present.

The score only measures how similar the faces are, and does not make an assessment of the nature of the photo. If spoofing (such as photos of printed photos or photos of digital screens) is detected the applicant will be rejected independently of the face match score.

Photo Fully Auto: Spoofing Detection Score

The spoofing_detection breakdown contains a properties object with a score value. This score is a floating point number between 0 and 1. The closer the score is to 0, the more likely it is to be a spoof (i.e. photos of printed photos, or photos of digital screens). Conversely, the closer it is to 1, the less likely it is to be a spoof.

If the anti-spoofing algorithm fails to detect a face, the score property will not be present.

Example Photo Fully Auto report object
1HTTP/1.1 201 Created
2Content-Type: application/json
3
4{
5 "created_at": "2020-01-01T14:16:21Z",
6 "href": "/v3.1/reports/<REPORT_ID>",
7 "id": "<REPORT_ID>",
8 "name": "facial_similarity_photo_fully_auto",
9 "result": "clear",
10 "status": "complete",
11 "sub_result": null,
12 "breakdown": {
13 "visual_authenticity": {
14 "result": "clear",
15 "breakdown": {
16 "spoofing_detection": {
17 "result": "clear",
18 "properties": {
19 "score": 0.9901
20 }
21 }
22 }
23 },
24 "image_integrity": {
25 "result": "clear",
26 "breakdown": {
27 "face_detected": {
28 "result": "clear",
29 "properties": {}
30 },
31 "source_integrity": {
32 "result": "clear",
33 "properties": {}
34 }
35 }
36 },
37 "face_comparison": {
38 "result": "consider",
39 "breakdown": {
40 "face_match": {
41 "result": "consider",
42 "properties": {
43 "score": 0.2097
44 }
45 }
46 }
47 }
48 },
49 "check_id": "<CHECK_ID>"
50}

Facial Similarity Video

In the Facial Similarity Video report, live videos are collected and uploaded by one of the Onfido SDKs (iOS, Android or Web).

Checks where applicant_provides_data is true are not compatible with Facial Similarity Video reports.

In addition to confirming the two faces match, Facial Similarity Video assesses active liveness by asking users to repeat randomly generated numbers and perform a random head movement. This prevents impersonation - for example masks, and deep fakes displayed on digital screens. This process is reflected in visual_authenticity, which is composed of the sub-breakdowns spoofing_detection and liveness_detected. See Facial Similarity Video Object and Facial Similarity Video Breakdowns.

In order for a Facial Similarity Video report to complete automatically, the user needs to turn their head in the correct direction and correctly say the 3 randomly generated digits in one of our supported languages (see table below).

Language nameLanguage code
English"en"
Spanish"es"
Italian"it"
Indonesian"id"
German"de"
French"fr"
Portuguese"pt"
Polish"pl"
Japanese"ja"
Dutch"nl"
Romanian"ro"
Basque"eu"
Catalan"ca"
Galician"gl"
Chinese"cn"
Turkish"tr"
Malay"ms"

If the user does not say the correct digits, or speak in another language, the live video will be reviewed by an analyst for evidence of spoofing.

SDK localization

We recommend that you localize the strings if you're using one of the Onfido SDKs, so the user is more likely to understand the liveness headturn and speaking instructions.

The Onfido voice processor will attempt to detect the language the user is speaking. This will be more successful if you pass the code for the expected language to the locale mechanism, in any of the Onfido SDKs:

  • iOS SDK - pass the onfido_locale parameter
  • Android SDK - pass the onfido_locale parameter
  • Web SDK - pass the locale parameter

Some string localisations are available out of the box, but this differs depending on the SDK.

You can also provide your own custom translations to your users.

Facial Similarity Video: Object

The following table describes the unique fields returned in this version of the Onfido API for a completed Facial Similarity Video report:

AttributeFormatPossible values
resultString"clear", "consider"
image_integrityString or null"clear", "consider", null
(sub-breakdown) face_detectedString or null"clear", "consider", null
(sub-breakdown) source_integrity1String or null"clear", "consider", null
face_comparisonString or null"clear", "consider", null
(sub-breakdown) face_match2String or null"clear", "consider", null
visual_authenticityString or null"clear", "consider", null
(sub-breakdown) spoofing_detection3String or null"clear", "consider", null
(sub-breakdown) liveness_detectedString or null"clear", "consider", null

1: source_integrity may contain reasons under the properties bag (see Facial Similarity Video: Source Integrity)

2: face_match contains a score value under the properties bag (see Facial Similarity Video: Face Match Score)

3: spoofing_detection contains a score value under the properties bag (see Facial Similarity Video: Spoofing Detection Score)

Facial Similarity Video: Breakdowns

BreakdownDescription
face_comparisonobject
Asserts whether the face in the document matches the face in the live video.
(sub-breakdown) face_matchobject
Contains a score value (see Facial Similarity Video Match Score).
image_integrityobject
Asserts whether the quality of the uploaded files and the content contained within them were sufficient to perform a face comparison.
(sub-breakdown) face_detectedobject
Asserts a single face of good enough quality has been found in both the document image and in the live video.
(sub-breakdown) source_integrityobject
Asserts whether the live video is trustworthy - e.g. not from a fake webcam.
visual_authenticityobject
Asserts whether the person in the live video is real (not a spoof) and live.
(sub-breakdown) spoofing_detectionobject
Asserts whether the live video is not a spoof (such as videos of digital screens).
(sub-breakdown) liveness_detectedobject
Asserts whether the numbers and head movements were correctly executed.

Facial Similarity Video: Source Integrity

We will return a reason whenever a report flags for source_integrity. This works by returning the contributing reason and a consider result in the source_integrity breakdown properties. There can be more than one reason, because they aren’t mutually exclusive. All other signals and potential reasons will be omitted.

For Facial Similarity Video, the source_integrity sub-breakdown is composed of the following properties:

  • fake_webcam - when evidence is found that a fake webcam was used
  • emulator - when evidence is found that an Android emulator was used
  • challenge_reuse - when evidence is found that the video was uploaded in an attempt to circumvent the randomness of the speaking and head turn challenges
  • sanctioned_document_country - when a document is issued by a country subject to comprehensive US sanctions (you can find the list of countries here). The report (either in conjunction with or separate from a document report) will return a consider result, accompanied by a reasons property clarifying that it is not supported due to sanctions
  • reasons - additional comma separated details, such as the name of the fake webcam

Facial Similarity Video: Face Match Score

The face_match breakdown contains a properties object with a score value. This score is a floating point number between 0 and 1 that expresses how similar the two faces are, where 1 is a perfect match.

If the face matching algorithm fails to detect a face, the score property will not be present and the face matching task will be done manually. The score only measures how similar the faces are, and does not make an assessment of the nature of the live video. If spoofing (such as videos of digital screens, masks or print-outs) is detected the applicant will be rejected independently of the face match score.

Facial Similarity Video: Spoofing Detection Score

The spoofing_detection breakdown contains a properties object with a score value. This score is a floating point number between 0 and 1. The closer the score is to 0, the more likely it is to be a spoof (i.e. videos of digital screens, masks or print-outs). Conversely, the closer it is to 1, the less likely it is to be a spoof.

The score value is based on passive facial information only, regardless of whether or not the user said the expected digits or turned their head in the correct direction. For example, a user who performs no action but is a real person should receive a score close to 1.

Example Facial Similarity Video report object
1HTTP/1.1 201 Created
2Content-Type: application/json
3
4{
5 "created_at": "2019-12-11T10:06:38Z",
6 "href": "/v3.1/reports/<REPORT_ID>",
7 "id": "<REPORT_ID>",
8 "name": "facial_similarity_video",
9 "properties": {},
10 "result": "clear",
11 "status": "complete",
12 "sub_result": null,
13 "breakdown": {
14 "face_comparison": {
15 "result": "clear",
16 "breakdown": {
17 "face_match": {
18 "result": "clear",
19 "properties": {
20 "score": 0.6512
21 }
22 }
23 }
24 },
25 "image_integrity": {
26 "result": "clear",
27 "breakdown": {
28 "face_detected": {
29 "result": "clear",
30 "properties": {}
31 },
32 "source_integrity": {
33 "result": "clear",
34 "properties": {}
35 }
36 }
37 },
38 "visual_authenticity": {
39 "result": "clear",
40 "breakdown": {
41 "liveness_detected": {
42 "result": "clear",
43 "properties": {}
44 },
45 "spoofing_detection": {
46 "result": "clear",
47 "properties": {
48 "score": 0.9512
49 }
50 }
51 }
52 }
53 },
54 "check_id": "<CHECK_ID>",
55 "documents": []
56}

Facial Similarity Motion

In the Facial Similarity Motion report, motion captures are collected and uploaded by one of the Onfido SDKs (iOS, Android or Web).

Checks where applicant_provides_data is true are not compatible with Facial Similarity Motion reports.

In addition to confirming the two faces match, Facial Similarity Motion assesses liveness by asking users to complete a head turn in both directions. This process is reflected in visual_authenticity, which is composed of the sub-breakdowns spoofing_detection and liveness_detected. See Facial Similarity Motion Object and Facial Similarity Motion Breakdowns.

Facial Similarity Motion reports always complete automatically.

Facial Similarity Motion: Object

The following table describes the unique fields returned in this version of the Onfido API for a completed Facial Similarity Motion report:

AttributeFormatPossible values
resultString"clear", "consider"
image_integrityString or null"clear", "consider", null
(sub-breakdown) face_detectedString or null"clear", "consider", null
(sub-breakdown) source_integrity1String or null"clear", "consider", null
face_comparisonString or null"clear", "consider", null
(sub-breakdown) face_match2String or null"clear", "consider", null
visual_authenticityString or null"clear", "consider", null
(sub-breakdown) spoofing_detection3String or null"clear", "consider", null
(sub-breakdown) liveness_detectedString or null"clear", "consider", null

1: source_integrity may contain reasons under the properties bag (see Facial Similarity Motion: Source Integrity)

2: face_match contains a score value under the properties bag (see Facial Similarity Motion: Face Match properties)

3: spoofing_detection contains a score value under the properties bag (see Facial Similarity Motion: Spoofing Detection Score)

Facial Similarity Motion: Breakdowns

BreakdownDescription
face_comparisonobject
Asserts whether the face in the document matches the face in the motion capture.
(sub-breakdown) face_matchobject
Contains a score value (see Facial Similarity Motion Match Score).
image_integrityobject
Asserts whether the quality of the uploaded files and the content contained within them were sufficient to perform a face comparison.
(sub-breakdown) face_detectedobject
Asserts a face of good enough quality has been found in both the document image and in the motion capture.
(sub-breakdown) source_integrityobject
Asserts whether the motion capture is trustworthy - e.g. not from a fake webcam.
visual_authenticityobject
Asserts whether the person in the motion capture is real (not a spoof) and live.
(sub-breakdown) spoofing_detectionobject
Asserts whether the motion capture is not a spoof (such as videos of digital screens).
(sub-breakdown) liveness_detectedobject
Asserts whether the head movements were correctly executed.

Facial Similarity Motion: Source Integrity

We will return a reason whenever a report flags for source_integrity. This works by returning the contributing reason and a consider result in the source_integrity breakdown properties. There can be more than one reason, because they aren’t mutually exclusive. All other signals and potential reasons will be omitted.

For Facial Similarity Motion, the source_integrity sub-breakdown is composed of the following properties:

  • fake_webcam - when evidence is found that a fake webcam was used
  • emulator - when evidence is found that an Android emulator was used
  • payload_integrity - when evidence is found that the payload was tampered with
  • sanctioned_document_country - when a document is issued by a country subject to comprehensive US sanctions (you can find the list of countries here). The report (either in conjunction with or separate from a document report) will return a consider result, accompanied by a reasons property clarifying that it is not supported due to sanctions
  • reasons - additional comma separated details, such as the name of the fake webcam

Facial Similarity Motion: Face Match Properties

The face_match breakdown contains a properties object with a score value. This score is a floating point number between 0 and 1 that expresses how similar the two faces are, where 1 is a perfect match.

The score only measures how similar the faces are, and does not make an assessment of the nature of the motion capture. If spoofing (such as videos of digital screens, masks or print-outs) is detected the applicant will be rejected independently of the face match score.

Facial Similarity Motion: Spoofing Detection Score

The spoofing_detection breakdown contains a properties object with a score value. This score is a floating point number between 0 and 1. The closer the score is to 0, the more likely it is to be a spoof (i.e. videos of digital screens, masks or print-outs). Conversely, the closer it is to 1, the less likely it is to be a spoof.

The score value is based on passive facial information only, regardless of whether or not the user performed the head turn. For example, a user who performs no action but is a real person should receive a score close to 1.

Example Facial Similarity Motion report object
1HTTP/1.1 201 Created
2Content-Type: application/json
3
4{
5 "check_id": "<CHECK_ID>",
6 "created_at": "2022-12-11T15:14:58Z",
7 "documents": [
8 {
9 "id": "<DOCUMENT_ID>"
10 }
11 ],
12 "href": "/v3.1/reports/<REPORT_ID>",
13 "id": "<REPORT_ID>",
14 "name": "facial_similarity_motion",
15 "properties": {},
16 "result": "clear",
17 "status": "complete",
18 "sub_result": null,
19 "breakdown": {
20 "face_comparison": {
21 "result": "clear",
22 "breakdown": {
23 "face_match": {
24 "result": "clear",
25 "properties": {
26 "score": 0.6512,
27 "document_id": "<DOCUMENT_ID>"
28 }
29 }
30 }
31 },
32 "image_integrity": {
33 "result": "clear",
34 "breakdown": {
35 "face_detected": {
36 "result": "clear",
37 "properties": {}
38 },
39 "source_integrity": {
40 "result": "clear",
41 "properties": {}
42 }
43 }
44 },
45 "visual_authenticity": {
46 "result": "clear",
47 "breakdown": {
48 "liveness_detected": {
49 "result": "clear",
50 "properties": {}
51 },
52 "spoofing_detection": {
53 "result": "clear",
54 "properties": {
55 "score": 0.9512
56 }
57 }
58 }
59 }
60 }
61}

Suggested client actions

We host a guide on our Developer Hub for suggested client actions in specific scenarios for clients using our Facial Similarity reports.

Known Faces report

This section contains API documentation for the Known Faces report. You can also read our product documentation.

The Known Faces report requires that we keep a database of facial biometric identifiers (personal data) so that individuals can be identified in future checks. Always make sure you inform your users about this and obtain any necessary permissions. For more information on how Onfido uses personal data, view our Privacy Policy.

Each applicant you run a Known Faces report against must have an uploaded live photo, live video or motion capture.

If no live photo, live video or motion capture is found, the Known Faces report will be automatically withdrawn and return an error in the report properties:

json
1"properties":{
2 "reason": "Report withdrawn due to missing media (photo, video or motion capture) required for processing."
3}

It is highly recommended the Known Faces report always be run in conjunction with a Facial Similarity report. Only faces processed through Facial Similarity are kept on the database. Thus, although it can be requested on its own, a Known Faces report can only match against applicants who have previously gone through a Facial Similarity report.

No matches will be returned against any permanently deleted applicants.

To request a Known Faces report as part of a check in the API, use the report_names field (which takes an array of strings):

"report_names": ["known_faces"]

Required applicant data

For Known Face reports, first_name and last_name must be provided but can be sample values if you don't know an applicant's name.

Known Faces: Object

The following table describes the unique fields returned in this version of the Onfido API for a completed Known Faces report:

AttributeFormatPossible values
resultString"clear", "consider"
previously_seen_facesString or null1"clear", "consider" , null
image_integrityString"clear", "consider"
  1. null is returned when image_integrity is "consider". This is because, when no face is detected in the input media, there is nothing to match against previously seen faces.

Known Faces: Breakdowns

BreakdownDescription
previously_seen_facesobject
Asserts whether the applicant's most recent facial media (live photo or live video) matches any other live photos or live videos already in your Onfido account database.
image_integrityobject
Asserts whether the uploaded live photo or live video and the content contained within it were of sufficient quality to perform a face comparison.

Known Faces: Score

The Known Faces response will return any matching applicant IDs as entries inside a matches array under a properties bag. Each applicant ID has a corresponding score and the media type (for example live_photos or live_videos), and the corresponding UUID for that media type. For example, the live photo or live video ID.

This score is a floating point number between 0 and 1 that expresses how similar the two faces are, where 1 is a perfect match.

json
1"matches": [
2 {
3 "applicant_id": "NTH_MATCHED_APPLICANT_ID",
4 "score": 0.9915,
5 "media_id": "LIVE_PHOTO_ID",
6 "media_type": "live_photos"
7 }
8]

If any matches are found, the response will also contain "result": "consider".

Example Known Faces report object
1HTTP/1.1 201 Created
2Content-Type: application/json
3
4{
5 "created_at": "2020-06-19T09:44:14Z",
6 "documents": [],
7 "href": "/v3.1/reports/<REPORT_ID>",
8 "id": "<REPORT_ID>",
9 "name": "known_faces",
10 "properties": {
11 "matches": [
12 {
13 "applicant_id": "<1ST_MATCHED_APPLICANT_ID>",
14 "score": 1,
15 "media_id": "<1ST_MEDIA_ID>",
16 "media_type": "live_photos"
17 },
18 {
19 "applicant_id": "<2ND_MATCHED_APPLICANT_ID>",
20 "score": 1,
21 "media_id": "<2ND_MEDIA_ID>",
22 "media_type": "live_videos"
23 },
24 {
25 "applicant_id": "<3RD_MATCHED_APPLICANT_ID>",
26 "score": 0.8903,
27 "media_id": "<3RD_MEDIA_ID>",
28 "media_type": "live_photos"
29 },
30 {
31 "applicant_id": "<4TH_MATCHED_APPLICANT_ID>",
32 "score": 0.8903,
33 "media_id": "<4TH_MEDIA_ID>",
34 "media_type": "live_photos"
35 },
36 {
37 "applicant_id": "<5TH_MATCHED_APPLICANT_ID>",
38 "score": 0.8903,
39 "media_id": "<5TH_MEDIA_ID>",
40 "media_type": "motion"
41 }
42 ]
43 },
44 "result": "consider",
45 "status": "complete",
46 "sub_result": null,
47 "breakdown": {
48 "previously_seen_faces": {
49 "result": "consider"
50 },
51 "image_integrity": {
52 "result": "clear"
53 }
54 },
55 "check_id": "<CHECK_ID>"
56}

Identity Enhanced report

This section contains API documentation for the Identity Enhanced report. You can also read our product documentation, which includes a list of the sources used in the Identity Enhanced report, with corresponding definitions, and the report logic.

To request an Identity Enhanced report as part of a check in the API, use the report_names field (which takes an array of strings):

"report_names": ["identity_enhanced"]

For checks containing Identity Enhanced reports, the applicant's last name must have at least 2 characters.

Required applicant data

For Identity Enhanced reports, the following applicant data must be provided:

  • first_name

  • last_name

  • dob

  • address.flat_number or address.building_number or address.building_name

  • address.street

  • address.state (US only)

  • address.postcode (ZIP code in US)

  • address.country (must be a 3-letter ISO code e.g. "GBR")

The applicant address object is nested inside the applicant object. You must provide full address information in the request. The address field will not return a match if only address.postcode is provided.

If you don't provide date of birth or address information in the request, a consider response with no breakdown information is returned. This is an invalid response and should be interpreted as a failed report.

Supported countries for Identity Enhanced

You can review the full list of supported countries for Identity Enhanced reports. The column Identity Enhanced Report on that page lists supported and unsupported countries.

This is not a list of documents that Onfido supports: you can review that list separately.

Identity Enhanced: Report object

The report object varies depending on the applicant's address country field.

United Kingdom

Example report object where the applicant's address is in the United Kingdom.

Sources (credit_agencies, voting_register, telephone_database) are displayed as breakdowns with their own result value.

Example UK Identity Enhanced report object
1HTTP/1.1 201 Created
2Content-Type: application/json
3
4{
5 "created_at": "2019-10-03T15:54:20Z",
6 "href": "/v3.1/reports/<REPORT_ID>",
7 "id": "<REPORT_ID>",
8 "name": "identity_enhanced",
9 "properties": {
10 "matched_address": 19099121,
11 "matched_addresses": [
12 {
13 "id": 19099121,
14 "match_types": [
15 "credit_agencies",
16 "voting_register"
17 ]
18 }
19 ]
20 },
21 "result": "clear",
22 "status": "complete",
23 "sub_result": null,
24 "breakdown": {
25 "sources": {
26 "result": "clear",
27 "breakdown": {
28 "total_sources": {
29 "result": "clear",
30 "properties": {
31 "total_number_of_sources": "3"
32 }
33 }
34 }
35 },
36 "address": {
37 "result": "clear",
38 "breakdown": {
39 "credit_agencies": {
40 "result": "clear",
41 "properties": {
42 "number_of_matches": "1"
43 }
44 },
45 "telephone_database": {
46 "result": "clear",
47 "properties": {}
48 },
49 "voting_register": {
50 "result": "clear",
51 "properties": {}
52 }
53 }
54 },
55 "date_of_birth": {
56 "result": "clear",
57 "breakdown": {
58 "credit_agencies": {
59 "result": "clear",
60 "properties": {}
61 },
62 "voting_register": {
63 "result": "clear",
64 "properties": {}
65 }
66 }
67 },
68 "mortality": {
69 "result": "clear"
70 }
71 },
72 "check_id": "<CHECK_ID>",
73 "documents": []
74}

United States

Example report object where the applicant's address is in the United States.

Any elements that are positively matched will be returned as clear in the report object breakdowns, including the source or sources of the database match in the properties field. When a match cannot be found (i.e. result is not clear) the corresponding properties bucket will be empty as such "properties":{}.

The report includes Social Security Number for a US applicant as an additional match under the ssn breakdown. This breakdown will not be returned if a SSN is not provided.

If an Identity enhanced report includes a Social Security Number breakdown, this will be returned in the ssn object for a report that was run using the using the https://api.us.onfido.com/ base URL, and ssn1 for a report that was run using the https://api.eu.onfido.com/ base URL.

Example US Identity Enhanced report object (with Social Security Number provided)
1HTTP/1.1 201 Created
2Content-Type: application/json
3
4{
5 "check_id": "<CHECK_ID>",
6 "created_at": "2022-05-06T08:44:54Z",
7 "documents": [],
8 "href": "/v3.1/reports/<REPORT_ID>",
9 "id": "<REPORT_ID>",
10 "name": "identity_enhanced",
11 "properties": {},
12 "result": "clear",
13 "status": "complete",
14 "sub_result": null,
15 "breakdown": {
16 "date_of_birth": {
17 "result": "clear",
18 "breakdown": {
19 "date_of_birth_matched": {
20 "result": "clear",
21 "properties": {
22 "sources": "Credit Agencies"
23 }
24 }
25 }
26 },
27 "address": {
28 "result": "clear",
29 "breakdown": {
30 "address_matched": {
31 "result": "clear",
32 "properties": {
33 "sources": "Credit Agencies, Telephone Database"
34 }
35 }
36 }
37 },
38 "ssn": {
39 "result": "clear",
40 "breakdown": {
41 "last_4_digits_match": {
42 "result": "clear",
43 "properties": {}
44 },
45 "full_match": {
46 "result": "clear",
47 "properties": {}
48 }
49 }
50 }
51 }

Non UK or US

Example report object where the applicant's address is not the United Kingdom or United States.

Sources are shown as comma separated under properties.

Non UK/US Identity Enhanced report object
1HTTP/1.1 201 Created
2Content-Type: application/json
3
4{
5 "check_id": "<CHECK_ID>",
6 "created_at": "2022-05-06T08:44:54Z",
7 "documents": [],
8 "href": "/v3.1/reports/<REPORT_ID>",
9 "id": "<REPORT_ID>",
10 "name": "identity_enhanced",
11 "properties": {},
12 "result": "clear",
13 "status": "complete",
14 "sub_result": null,
15 "breakdown": {
16 "date_of_birth": {
17 "result": "clear",
18 "breakdown": {
19 "date_of_birth_matched": {
20 "result": "clear",
21 "properties": {
22 "sources": "Credit Agencies"
23 }
24 }
25 }
26 },
27 "address": {
28 "result": "clear",
29 "breakdown": {
30 "address_matched": {
31 "result": "clear",
32 "properties": {
33 "sources": "Credit Agencies, Telephone Database"
34 }
35 }
36 }
37 }
38 }
39}

Identity Enhanced report custom logic

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Watchlist reports

This section contains API documentation for the Onfido Watchlist reports. You can also read our product documentation.

There are 5 different types of Watchlist report:

Report nameRequest body in API
Watchlist AML"report_names": ["watchlist_aml"]
Watchlist Enhanced"report_names": ["watchlist_enhanced"]
Watchlist Standard"report_names": ["watchlist_standard"]
Watchlist PEPs Only"report_names": ["watchlist_peps_only"]
Watchlist Sanctions Only"report_names": ["watchlist_sanctions_only"]

Watchlist AML

The Watchlist AML report provides a granular breakdown of any records found when screening global watchlists and media sources. These include:

  • sanction: Government and International Organisations Sanctions Lists
  • politically_exposed_person: Proprietary database of Politically Exposed Persons sourced from government lists, websites and other media sources
  • legal_and_regulatory_warnings: Law-Enforcement and Regulatory bodies Monitored Lists (including Terrorism, Money Laundering and Most Wanted lists)
  • adverse_media: Negative events reported by publicly and generally available media sources
The Watchlist AML report is 6AMLD compliant.

Records

If no match is found against the subject, the records field will read [] and the overall result will be clear.

If one or more matches are found, each match will be returned under records and the overall result will be consider.

As matches are done based on the available information, none of these properties are guaranteed to be present in the response.

FieldDescription
associatesstring
Any linked persons, for example family relatives or business partners
keywordsstring
last_updated_utcstring
The date and time the entry was last updated
entity_typestring
Should always be "person"
sourcesstring
Where the information was obtained, for example "PEPs list"
typesstring
The type of the source, for example "pep-class-1"
namestring
The name on file. Allows for custom cross-referencing of input details against output details
external_idstring
Returns an empty string
match_typesstring
The type of match, for example, "name_exact"
related_urlsstring
URL to the data source
picture_urlsstring
URL to the picture of the individual found in the match
all_dobsstring
All the date of births on file. Allows for custom cross-referencing of input details against output details
report_idinteger
The ID of the report
entity_fields_dobsstring
Date of birth
entity_fields_dodstring
Date of death
entity_fields_podstring
Place of birth
entity_fields_ofacstring
Office of Foreign Assets Control (OFAC) ID
entity_fields_addressstring
Address
entity_fields_countriesstring
Countries

Where applicable, if multiple values are found from the raw response, string concatenation with a delimiter of ", " is used.

Entity fields are additional, optional fields so they may not be present in the final result.

Required applicant data

For watchlist_aml reports, first_name and last_name must be provided.

dob

address[]postcode (ZIP code in US)

address[]country

address[]state (required for US addresses)

Date of birth

Submitting a date_of_birth with the name is optional but recommended, to narrow the search of the relevant individual.

More than one date of birth might be found per match due to the nature of the data sources, such as newspaper articles, which might include someone's age but not their full date of birth.

Address

Submitting an address with the country is optional but recommended.

The applicant address object is nested inside the applicant object.

Results are filtered by country of operation or office, under these circumstances:

  • There are PEP matches only
  • There are PEP matches with Adverse Media

The country filter is not applied, or in other words, results will still appear regardless of the address country, under these circumstances:

  • There are adverse media matches only
  • Address does not have a country
  • Sanctions, Money Laundering or Terrorist related events will always appear even if the country filter is applied

If a match is found but the date_of_birth or address fields are null, this means there is no date_of_birth or address data on file associated with that match.

Example Watchlist AML report object
1HTTP/1.1 201 Created
2Content-Type: application/json
3
4{
5 "created_at": "2019-10-03T15:42:36Z",
6 "href": "/v3.1/reports/<REPORT_ID>",
7 "documents": [],
8 "id": "<REPORT_ID>",
9 "name": "watchlist_aml",
10 "properties": {
11 "records": []
12 },
13 "result": "clear",
14 "status": "complete",
15 "sub_result": null,
16 "breakdown": {
17 "sanction": {
18 "result": "clear"
19 },
20 "politically_exposed_person": {
21 "result": "clear"
22 },
23 "legal_and_regulatory_warnings": {
24 "result": "clear"
25 },
26 "adverse_media": {
27 "result": "clear"
28 }
29 },
30 "check_id": "<CHECK_ID>"
31}

Watchlist Enhanced

The Watchlist Enhanced report provides a granular breakdown of any records found when screening global watchlists and media sources. These include the following breakdowns:

  • sanction: Government and International Organisations Sanctions Lists.
  • politically_exposed_person: Proprietary database of Politically Exposed Persons sourced from government lists, websites and other media sources.
  • monitored_lists: Law-Enforcement and Regulatory bodies Monitored Lists (including Terrorism, Money Laundering and Most Wanted lists).
  • adverse_media: Negative events reported by publicly and generally available media sources.

Records

If no match is found against the subject, the records field will read [] and the overall result will be clear.

If one or more matches are found, each match will be returned under records and the overall result will be consider. Each event will correspond to a relevant category of list, which drives one of the breakdowns.

As matches are done based on the available information, none of these properties are guaranteed to be present in the response.

FieldDescriptionSub-fields
addressarray of objects
All addresses on file
address_line1
country
postal_code
state_province
town
locator_type
aliasarray of objects
Any names that the person is also known as
alias_name
alias_type
associatearray of objects
Any linked persons, for example family relatives or business partners
entity_name
relationship_direction
relationship_type
attributearray of objects
Information about the person, for example hair color or nationality
attribute_type
attribute_value
date_of_birtharray of DOB objects
All the date of births on file
eventarray of objects
Information about events that have occurred to the person, for example deportation or arrest
category
event_date
event_description
source (source_date, source_format, source_name)
sub_category
full_namestring
The name on file
positionarray of strings
The role, country and date of each position
sourcearray of objects
Details about where the information was obtained
source_headline
source_name
source_url

Required applicant data

For watchlist_enhanced reports, first_name and last_name must be provided.

dob

address[]postcode (ZIP code in US)

address[]country

address[]state (required for US addresses)

Date of birth

Submitting a date_of_birth with the name is optional but recommended, to narrow the search of the relevant individual.

More than one date of birth might be found per match due to the nature of the data sources, such as newspaper articles, which might include someone's age but not their full date of birth.

Address

Address

Submitting an address with the country is optional but recommended.

The applicant address object is nested inside the applicant object.

Results are filtered by country of operation or office, under these circumstances:

  • There are PEP matches only
  • There are PEP matches with Adverse Media

The country filter is not applied, or in other words, results will still appear regardless of the address country, under these circumstances:

  • There are adverse media matches only
  • Address does not have a country
  • Sanctions, Money Laundering or Terrorist related events will always appear even if the country filter is applied

If a match is found but the date_of_birth or address fields are null, this means there is no date_of_birth or address data on file associated with that match.

Example Watchlist Enhanced report object
1HTTP/1.1 201 Created
2Content-Type: application/json
3
4{
5 "created_at": "2019-10-03T15:37:03Z",
6 "href": "/v3.1/reports/<REPORT_ID>",
7 "id": "<REPORT_ID>",
8 "name": "watchlist_enhanced",
9 "properties": {
10 "records": []
11 },
12 "result": "clear",
13 "status": "complete",
14 "sub_result": null,
15 "breakdown": {
16 "politically_exposed_person": {
17 "result": "clear"
18 },
19 "sanction": {
20 "result": "clear"
21 },
22 "adverse_media": {
23 "result": "clear"
24 },
25 "monitored_lists": {
26 "result": "clear"
27 }
28 },
29 "check_id": "<CHECK_ID>",
30 "documents": []
31}

Watchlist Standard

The Watchlist Standard report provides a granular breakdown of any records found when screening global watchlists. These include:

  • sanction: Government and International Organisations Sanctions Lists.
  • politically_exposed_person: Proprietary database of Politically Exposed Persons sourced from government lists, websites and other media sources.
  • legal_and_regulatory_warnings: Law-Enforcement and Regulatory bodies Monitored Lists (including Terrorism, Money Laundering and Most Wanted lists).

You can use a Watchlist PEPs Only report to search only PEPs lists, or a Watchlist Sanctions Only` report to search only sanctions and warnings lists. The Watchlist Standard report will search all types.

Records

If no match is found against the subject, the records field will read [] and the overall result will be clear.

If one or more matches are found, each match will be returned under records and the overall result will be consider.

See Watchlist AML records for details of the possible fields.

Required applicant data

For watchlist_standard reports, first_name and last_name must be provided.

dob

address[]postcode (ZIP code in US)

address[]country

address[]state (required for US addresses)

The applicant address object is nested inside the applicant object. If you create an applicant object with an address, you must provide postcode and country, and state for US addresses.

If the applicant's address is provided, the address[]country field will narrow the search to include only PEPs who hold office in that country. The country filter will also be applied if an individual is both a PEP and has warnings or adverse media.

The country filter has no impact on sanctions results.

Example Watchlist Standard report object
1HTTP/1.1 201 Created
2Content-Type: application/json
3
4{
5 "created_at": "2019-10-03T15:42:36Z",
6 "href": "/v3.1/reports/<REPORT_ID>",
7 "id": "<REPORT_ID>",
8 "name": "watchlist_standard",
9 "properties": {
10 "records": []
11 },
12 "result": "clear",
13 "status": "complete",
14 "sub_result": null,
15 "breakdown": {
16 "sanction": {
17 "result": "clear"
18 },
19 "politically_exposed_person": {
20 "result": "clear"
21 },
22 "legal_and_regulatory_warnings": {
23 "result": "clear"
24 }
25 },
26 "check_id": "<CHECK_ID>",
27 "documents": []
28}

Watchlist PEPs Only

The Watchlist PEPs Only report is a subset of the Watchlist Standard report. It provides a granular breakdown of politically_exposed_person breakdown matches.

Each match will be returned under records and includes, but is not limited to: name of match, associates, date of birth, related keywords, type of list, name of list, and when the entry was last updated. When available, URLs to data sources are provided, as well as pictures of the individual found in the match. This allows you to quickly assess the relevancy of the match and eliminate false positives. See Watchlist AML records for details of the possible fields.

More than one date of birth might be found per match, due to the nature of the data sources, such as news papers articles, which might include someone's age but not their full date of birth.

Required applicant data

For watchlist_peps_only reports, first_name and last_name must be provided.

dob

If applicant's address is provided, address[]country field will be treated as the country where the PEP holds office, not the applicant nationality.

Watchlist Sanctions Only

The Watchlist Sanctions Only report is a subset of the Watchlist Standard report. It provides a granular breakdown of sanction breakdown matches.

Each match will be returned under records and includes, but is not limited to: name of match, associates, date of birth, related keywords, type of list, name of list, and when the entry was last updated. When available, URLs to data sources are provided, as well as pictures of the individual found in the match. This allows you to quickly assess the relevancy of the match and eliminate false positives. See Watchlist AML records for details of the possible fields.

More than one date of birth might be found per match, due to the nature of the data sources, such as news papers articles, which might include someone's age but not their full date of birth.

Required applicant data

For Watchlist Sanctions Only reports, first_name and last_name must be provided.

dob

Proof of Address report

This section contains API documentation for the Proof of Address report. You can also read our product documentation , which contains a guide on the logic the Proof of Address report uses.

To request a Proof of Address report as part of a check in the API, use the report_names field (which takes an array of strings):

"report_names": ["proof_of_address"]

The Proof of Address (PoA) report is for use with UK documents only.

You must set the issuing_country field to "GBR" when uploading the document via the document upload endpoint.

If the issuing_country field is not specified or is from an unsupported country, the document will be uploaded however it will not be processed and the report will complete with the status set to withdrawn and the result set to null.

Applicants are able to upload documents from anywhere in the world, but the document must have been issued by the United Kingdom and be a supported document for this report.

Required applicant data

For Proof of Address reports, the following applicant data must be provided:

first_name

last_name

address[]street

address[]town

address[]postcode

address[]country (must be a 3-letter ISO code e.g. "GBR")

The applicant address object is nested inside the applicant object. If you create an applicant object with an address, you must provide postcode and country, and state for US addresses.

Checks where applicant_provides_data is set to true are not compatible with Proof of Address reports.

Supported document types

The following document types are supported for a PoA report:

DocumentAPI document type
Bank Statement/Building Society Statementsbank_building_society_statement
Utility Bill (electricity, water, gas, broadband )utility_bill
Local Government Tax Lettercouncil_tax
Benefits Letter (i.e. Job seeker allowance, House benefits, Tax credits)benefit_letters

Proof of Address: Breakdowns

A PoA report is composed of the following 3 breakdowns:

BreakdownDescription
image_integrityobject
Asserts whether the quality of the uploaded document was sufficient to verify the address
document_classificationobject
Asserts whether the document is a supported document type
data_comparisonobject
Asserts whether the first name, last name and address provided by the applicant match those on the PoA document
source_integrityobject
Asserts whether the source integrity of the uploaded document is sufficient to verify the address

Proof of Address: Properties

In addition, data points extracted from PoA documents are returned in the properties attribute.

FieldDescription
document_typeThis property provides the document type according to the set of supported documents
issue_dateThis property provides the issue date of the document
expiry_dateThis property provides the expiry date of the document
summary_period_startThis property provides the summary period start date
summary_period_endThis property provides the summary period end date
issuerThis property provides the document issuer (e.g. HSBC, British Gas)
first_namesThis property provides the first names on the document, including any initials and middle names
last_namesThis property provided the last names on the document
addressThis property provides the address on the document

Only the summary period or the issue date will be returned in the report properties attribute as they are mutually exclusive. Issue date may not be returned if document has only expiry date.

Proof of Address report: Overall Result Logic

We've moved this content.

Example Proof of Address report object
1HTTP/1.1 201 Created
2Content-Type: application/json
3
4{
5 "created_at": "2021-04-27T14:51:35Z",
6 "documents": [],
7 "href": "/v3.1/reports/<REPORT_ID>",
8 "id": "<REPORT_ID>",
9 "name": "proof_of_address",
10 "properties": {
11 "document_type": "council_tax",
12 "issuer": "city of london",
13 "issue_date": "2020-01-01",
14 "first_names": "John",
15 "last_names": "Smith",
16 "address": "123 sample street london xyz 1ab"
17 },
18 "result": "clear",
19 "status": "complete",
20 "sub_result": null,
21 "breakdown": {
22 "image_integrity": {
23 "result": "clear",
24 "breakdown": {
25 "image_quality": {
26 "result": "clear",
27 "properties": {}
28 }
29 }
30 },
31 "document_classification": {
32 "result": "clear",
33 "breakdown": {
34 "supported_document": {
35 "result": "clear",
36 "properties": {}
37 }
38 }
39 },
40 "data_comparison": {
41 "result": "clear",
42 "breakdown": {
43 "first_name": {
44 "result": "clear",
45 "properties": {}
46 },
47 "last_name": {
48 "result": "clear",
49 "properties": {}
50 },
51 "address": {
52 "result": "clear",
53 "properties": {}
54 }
55 }
56 },
57 "source_integrity": {
58 "result": "clear",
59 "breakdown": {
60 "digital_tampering": {
61 "result": "clear",
62 "properties": {}
63 }
64 }
65 }
66 },
67 "check_id": "<CHECK_ID>"
68}

Driver's License Data Verification report

This section contains API documentation for the Driver's License Data Verification (DLDV) report. You can also read our product documentation.

The DLDV report is for United States documents only.

To request a DLDV report as part of a check in the API, use the report_names field (which takes an array of strings):

"report_names": ["us_driving_licence"]

To upload document data, use the us_driving_licence field (which is an object containing all accepted fields for the DLDV report).

json
1...
2"report_names": ["us_driving_licence"],
3"us_driving_licence":{
4 "id_number": "<DRIVER_LICENCE_ID>", // required
5 "issue_state": "<TWO_LETTER_STATE_CODE>", // required
6 ... // all other optional fields
7 }
8...

See optional document data for a table of the accepted optional fields in the us_driving_licence object for a DLDV report.

See create a check for a full list of the possible request body parameters.

If you use this report, Onfido will use a third-party subprocessor to verify driving license data against the American Association of Motor Vehicle Administrators (AAMVA) facilitated Department of Motor Vehicles (DMV) driver's license database.

Required applicant data

For DLDV reports, first_name and last_name must be provided.

Required document data

For DLDV reports, the following document data must be provided in the report request in the us_driving_licence field:

FieldFormat
id_numberString
issue_stateString
(2-character state code)

Optional document data

The following optional fields are also accepted in the us_driving_licence object:

FieldFormatPossible values
address_line_1String
address_line_2String
cityString
date_of_birthDate
YYYY-MM-DD
document_categoryEnum"driver license", "driver permit", "id card"
expiration_dateDate
YYYY-MM-DD
eye_color_codeEnum"BLK", "BLU", "BRO", "DIC", "GRY", "GRN", "HAZ", "MAR", "PNK"
first_nameString
genderString
height_measure_feetInteger
height_measure_inchesInteger
issue_dateDate
YYYY-MM-DD
last_nameString
middle_nameString
name_suffixString
postal_codeString
stateString
(2-character state code)
weight_measureInteger
(in pounds)

Supported document types

  • US driver's license
  • US learner's permit or provisional license
  • ID card

A DLDV report does not require a document upload. Data is entered manually in the report request.

Supported Issue States

  • AR
  • AZ
  • CO
  • CT
  • DC
  • DE
  • HI
  • FL
  • IA
  • ID
  • IN
  • IL
  • KS
  • KY
  • MA
  • MD
  • ME
  • MI
  • MO
  • MS
  • MT
  • NC
  • ND
  • NE
  • NJ
  • NM
  • OH
  • PA
  • RI
  • SD
  • TN
  • TX
  • VA
  • VT
  • WI
  • WA
  • WY
  • GA
  • OR

DLDV: Results

The result field indicates the overall report result. Any optional fields submitted in the report request will be accounted for in the final result.

Possible values for DLDV reports are clear, consider and unidentified:

Report resultDescription
clearAll fields exact match
considerName fields have been flagged as a mismatch through fuzzy matching* or any optional fields don't match
unidentifiedID number or name field doesn't match

* Onfido's third-party subprocessor uses fuzzy matching on the name fields during DLDV checks. This is because information can be provided in many different ways and errors in data submission or collection can be quite high.

DLDV: Breakdowns

Breakdowns can have a clear or consider result. Breakdowns will only have a clear result when all included sub-breakdowns are clear.

Breakdowndescriptionsub-breakdowns
documentobject
Asserts whether the document data provided matches a real driving license in the DMV driver's license database.
category
expiration_date
issue_date
document_number
addressobject
Asserts whether the address data provided matches a real driving license in the DMV driver's license database.
city
line_1
line_2
state_code
zip4
zip5
personalobject
Asserts whether the personal data provided matches a real driving license in the DMV driver's license database.
name_suffix
height
weight
sex_code
eye_color
date_of_birth
first_name
last_name
middle_name
first_name_fuzzy
middle_name_fuzzy
last_name_fuzzy
middle_initial
Example DLDV report object
1HTTP/1.1 201 Created
2Content-Type: application/json
3
4{
5 "created_at": "2021-03-26T19:51:37Z",
6 "documents": [],
7 "href": "/v3.1/reports/<REPORT_ID>",
8 "id": "<REPORT_ID>",
9 "name": "us_driving_licence",
10 "properties": {},
11 "result": "clear",
12 "status": "complete",
13 "sub_result": null,
14 "breakdown": {
15 "document": {
16 "result": "clear",
17 "breakdown": {
18 "category": {
19 "result": "clear",
20 "properties": {}
21 },
22 "expiration_date": {
23 "result": "clear",
24 "properties": {}
25 },
26 "issue_date": {
27 "result": "clear",
28 "properties": {}
29 },
30 "document_number": {
31 "result": "clear",
32 "properties": {}
33 }
34 }
35 },
36 "address": {
37 "result": "clear",
38 "breakdown": {
39 "city": {
40 "result": "clear",
41 "properties": {}
42 },
43 "line_1": {
44 "result": "clear",
45 "properties": {}
46 },
47 "line_2": {
48 "result": "clear",
49 "properties": {}
50 },
51 "state_code": {
52 "result": "clear",
53 "properties": {}
54 },
55 "zip4": {
56 "result": "clear",
57 "properties": {}
58 },
59 "zip5": {
60 "result": "clear",
61 "properties": {}
62 }
63 }
64 },
65 "personal": {
66 "result": "clear",
67 "breakdown": {
68 "first_name": {
69 "result": "clear",
70 "properties": {}
71 },
72 "name_suffix": {
73 "result": "clear",
74 "properties": {}
75 },
76 "height": {
77 "result": "clear",
78 "properties": {}
79 },
80 "weight": {
81 "result": "clear",
82 "properties": {}
83 },
84 "sex_code": {
85 "result": "clear",
86 "properties": {}
87 },
88 "eye_color": {
89 "result": "clear",
90 "properties": {}
91 },
92 "date_of_birth": {
93 "result": "clear",
94 "properties": {}
95 },
96 "last_name": {
97 "result": "clear",
98 "properties": {}
99 },
100 "middle_name": {
101 "result": "clear",
102 "properties": {}
103 },
104 "first_name_fuzzy": {
105 "result": "clear",
106 "properties": {}
107 },
108 "middle_name_fuzzy": {
109 "result": "clear",
110 "properties": {}
111 },
112