When individuals attempt to verify themselves, verification checksverification checks - A set of configurable criteria that are evaluated upon each verification attempt and determine whether it passes or fails. indicate something of note with the information that was submitted. They determine whether the verification attempt passes or fails and help you understand whether the submission is valid and meets your requirements, or if additional investigation is needed.

Configure and consume checks

There are a set of default checks that are required for the submission to be passed, while others are running and used for additional review but do not affect whether an attempt passes or fails. The defaults are determined based on the common needs across our customers, but we are happy to work with you to configure the defaults to meet your unique requirements. For more information about configuring requirements and the potential tradeoffs, please contact us.

Verification checks are returned in the Retrieve a Verification API response and are viewable in the DashboardDashboard - A hub for organizations to review inquiries and manage their integration with Persona. for each verification attempt.

Different checks are evaluated across different Verification Types, which are specified at the beginning of the check slug.

Check statuses

Check Status	Description
Passed	The check passed for the verification attempt.
Failed	The check failed for the verification attempt.
Not Applicable	The check was not evaluated for the verification attempt (e.g. `id_barcode_detection` will not be evaluated if the back of the ID is not required to be submitted).

Check types

There are two check types:

User action required: The individual did not submit the at-minimum high-quality and unobstructed images needed for verification. For instance, if an individual submits a blurry image. Persona exposes these checks back to the individual in the inquiry flow as hints to help individuals submit better images.
Fraud: The individual may be trying to verify with false or altered information. For instance, if the face portrait from the ID doesn't the face from the selfie. There may be additional, noteworthy details about the submission that can be used to meet specific fraud requirements for different use cases. For instance, if the individual submitted an ID from a country that was not allowed on the templatetemplate - A configuration that defines the steps an individual must take to verify their identity..

Match results

For Database Verifications, each piece of information submitted like name or birthdate is matched against the record returned from the source database, and Persona returns three possible match results for each piece of information as separate checks:

None: The information did not match.
Partial: The property matched, but did not match exactly. Persona utilizes algorithmic processes (i.e. fuzzy matching) to determine the mathematical similarity between two pieces of information. This allows for the passing of near matches, which avoids unnecessary failures if the individual inputs an accidental typo or, in the case of name, a nickname (e.g. "Mike" instead of "Mikey"). For example, a date of birth of 12/15/1990 would partially against a birthdate of 12/14/1990.
Full: The information matched exactly.

For more information about configuring the minimum match requirement for each piece of information, please contact us.

Check list

Slug	Name	Type	Description	Failure Reason(s)
`id_account_comparison`	Account comparison	Fraud	Compare if ID details like name or birthdate are inconsistent.	`property_conflict`: ID details like name or birthdate are inconsistent with the account details.
`id_age_inconsistency_detection`	Portrait age	Fraud	Detect if the age listed on the ID is different than the age estimated from the face portrait.	`inconsistent_age`: The age listed on the ID appears to be different than the age estimated from the age portrait.
`id_barcode_detection`	Barcode	User action required	Detect if there is a barcode on the ID.	`barcode_unreadable`: The barcode on the ID is unreadable. `barcode_not_found`: The barcode on the ID is not found. `back_missing`: The image does not contain the whole backside of the card.
`id_barcode_inconsistency_detection`	Barcode inconsistency	Fraud	Detect inconsistencies in the barcode on the ID.	`format_invalid`: The barcode does not follow ID specifications. `subfile_missing`: The barcode is missing data blocks required by the ID. `legacy_version_found`: The barcode uses a version format that was replaced 10 years before the issue date. `required_field_missing`: The barcode is missing required fields. `designators_invalid`: The barcode has invalid data block names. `field_invalid`: The barcode has fields in invalid formats. `issuer_invalid`: The barcode specifies an issuer that is invalid. `issuer_mismatch`: The barcode has inconsistent issuer information.
`id_blur_detection`	Blur	User action required	Detect if the submission is blurry.	`too_blurry`: The submission is blurry.
`id_color_inconsistency_detection`	Color	Fraud	Detect if the colors on the ID are different than the expected colors.	`too_few_colors`: The colors detected on the ID appear to be different than the expected colors.
`id_compromised_detection`	Compromised submission	Fraud	Detect if the submission can be found from a publicly available source (e.g. the internet).	`publicly_available`: The ID is likely a sample ID or publicly available. `fraudulent`: The ID is reported as fraudulent.
`id_disallowed_country_detection`	Allowed country	User action required	Detect if the country of the ID is not allowed based on template requirements.	`not_allowed_by_configuration`: The country of the ID is not allowed based on template requirements.
`id_disallowed_type_detection`	Allowed ID type	User action required	Detect if the ID type submitted is not allowed based on template requirements.	`not_allowed_by_configuration`: 'The ID type is not allowed based on template requirements. `type_mismatch`: The ID type detected does not match the ID type the user selected.
`id_double_side_detection`	Double side	User action required	Detect if one side of the ID is submitted as both front and back.	`side_submitted_twice`: The back and front submissions of the ID are of the same side.
`id_electronic_replica_detection`	Electronic replica	Fraud	Detect if the submission is a replica of an image presented on another electronic device or screen.	`device_found`: The submission may be a replica of an image presented on another electronic device or screen.
`id_entity_detection`	Government Entity ID	User action required	Detect if there is a government ID in the submission.	`confidence_score_below_threshold`: The submission does not appear to include a government ID.
`id_expired_detection`	Expiration	User action required	Detect if the ID is expired.	`expired`: The ID is expired.
`id_extracted_properties_detection`	Extracted properties	User action required	Detect if required ID details like name or birthdate are extracted.	`property_not_extracted`: A required property was not extracted. `no_required_properties`: The template is not configured to require extraction of certain properties.
`id_extraction_inconsistency_detection`	Extraction inconsistency	Fraud	Detect if the details extracted from the front of the ID are different than the details extracted from the barcode.	`property_match`: Details extracted from the front of the ID are different than the details extracted from the barcode.
`id_glare_detection`	Glare	User action required	Detect if the submission has glare.	`too_much_glare`: The submission has glare.
`id_handwriting_detection`	Handwriting	Fraud	Detect if the handwriting is found on the ID.	`handwriting_found`: The ID appears to have handwriting on it.
`id_inconsistent_repeat_detection`	Inconsistent repeat	Fraud	Detect if either the ID details or face portrait match that of a previously submitted ID.	`inconsistent_details`: The face portrait matches that of a previously submitted ID with different details. `inconsistent_face`: The ID details matches that of a previously submitted ID with a different face portrait.
`id_inquiry_comparison`	Inquiry comparison	Fraud	Compare if ID details like name or birthdate are inconsistent between different submission attempts.	`property_conflict`: ID details like name or birthdate are inconsistent between different submission attempts.
`id_mrz_detection`	MRZ	User action required	Detect if there is encoded, machine-readable text on the ID.	`mrz_not_found`: The encoded, machine-readable text on the ID is not found.
`id_po_box_detection`	PO box	User action required	Detect if the address is a PO box.
`id_portrait_clarity_detection`	Portrait clarity	User action required	Detect if the face portrait is clear and in focus.	`portrait_not_clear`: The face portrait is unclear and out of focus.
`id_portrait_detection`	Portrait	User action required	Detect if there is a face portrait in the submission.	`portrait_not_found`: The submission has no face portrait.
`id_public_figure_detection`	Public figure	Fraud	Detect if the face portrait matches that of a known public figure.	`public_figure_detected`: The face portrait appears to match that of a known public figure.
`id_repeat_detection`	Repeat	Fraud	Detect if the ID details and face portrait match that of a previously submitted ID on a different account.	`repeat`: The ID details and face portrait match that of a previously submitted ID on a different account.
`id_selfie_comparison`	Selfie-to-ID comparison	Fraud	Compare if the face portrait on the ID and the selfie are different faces.	`face_mismatch`: The face portrait on the ID and the selfie appear to be different faces.
`id_tamper_detection`	Image tampering	Fraud	Detect if the submission is image tampered or manipulated by an editor.	`exif_inconsistency`: The submission has inconsistencies in the file metadata that imply image tampering. `image_manipulated`: The submission appears to have been digitally tampered.
`id_unprocessable_submission_detection`	Processable submission	User action required	Detect if the submission is unprocessable.	`submission_invalid`: The submission is unprocessable.
`id_valid_dates_detection`	Valid dates	Fraud	Detect if the dates on the ID are in violation of issuing authority rules.	`issuer_rules_inconsistency`: The dates on the ID appear to be in violation of issuing authority rules.
`selfie_account_comparison`	Account comparison	Fraud	Compare if the selfie is inconsistent with the selfie of the account.	`face_mismatch`: The selfie is inconsistent with the selfie of the account.
`selfie_age_comparison`	Age comparison	Fraud	Detect if the perceived age from the selfie is different from the reference age.
`selfie_glare_detection`	Glare	User action required	Detect if the submission has glare.	`glare`: The submission has glare.
`selfie_glasses_detection`	Glasses	User action required	Detect if glasses are present.	`glasses`: Glasses are detected and may interfere with selfie face detection.
`selfie_id_comparison`	Selfie-to-ID comparison	Fraud	Compare if the selfie and the face portrait in the ID are different faces.	`face_mismatch`: The selfie and the face portrait in the ID appear to be different faces. `suspiciously_high_similarity`: The selfie and the face portrait in the ID appear to be the exact same submission.
`selfie_multiple_faces_detection`	Multiple faces	Fraud	Detect if the selfies are different faces across poses.	`face_conflict`: The selfies appear to be different faces across poses.
`selfie_pose_detection`	Pose position	Fraud	Detect if the face in the selfies are correctly positioned across all poses.	`required_poses_not_found`: The selfies appear to be incorrectly positioned in one or more poses.
`selfie_public_figure_detection`	Public figure	Fraud	Detect if the selfie submission matches a known public figure.
`selfie_pose_repeat_detection`	Pose repeat	Fraud	Detect if the selfies are exact repeats across poses.	`poses_repeated`: The selfies appear to repeat across poses.
`selfie_suspicious_entity_detection`	Suspicious entity	Fraud	Detect if the selfie submission is that of a government ID.	`suspicious_photo`: The selfie submission appears to be a government ID.
`database_address_comparison`	Address	Fraud	Detect if the address matches any databases.	`insufficient_match`: The address provided did not sufficiently match any databases.
`database_address_deliverable_detection`	Deliverable address	Fraud	Detect if the address is deliverable.
`database_birthdate_comparison`	Birthdate	Fraud	Detect if the birthdate matches any databases.	`insufficient_match`: The birthdate provided did not sufficiently match any databases.
`database_deceased_detection`	Alive	User action required	Detect if person is living.
`database_name_comparison`	Name	Fraud	Detect if the name matches any databases.	`insufficient_match`: The name provided did not sufficiently match any databases.
`database_phone_number_comparison`	Phone number	Fraud	Detect if the phone number matches any databases.	`insufficient_match`: The phone number provided did not sufficiently match any databases.
`database_po_box_detection`	PO box	User action required	Detect if the address is a PO box.
`database_social_security_number_comparison`	SSN	Fraud	Detect if the SSN matches any databases.	`insufficient_match`: The SSN provided did not sufficiently match any databases.
`document_compromised_detection`	Compromised submission	Fraud	Detect if the submission can be found from a publicly available source (e.g. the internet).	`publicly_available`: The submission exists in publicly available sources.
`document_tamper_detection`	Image tampering	Fraud	Detect if the submission is image tampered or manipulated by an editor.	`exif_inconsistency`: The submission has inconsistencies in the file metadata that imply image tampering. `image_manipulated`: The submission appears to have been digitally tampered.
`document_extracted_properties_detection`	Extracted properties	User action required	Detect if the details extracted from the document match patterns.	`match_rejected`: Match was rejected for a pattern. `match_missing`: The submission is missing a match pattern.
`document_recency_detection`	Recency	User action required	Detect if the document is recent.	`not_recent`: Document is not recent enough.
`document_type_detection`	Type	User action required	Detect if the document one of the expected types.

Legacy Checks

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If you are using our legacy verification checks, known as confidence reasons, please refer to the Confidence Reason(s) column in the table below to understand how they map to the new verification checks.

Check Slug	Confidence Reason Slug
`id_account_comparison`	`account_comparison_failure`
`id_age_inconsistency_detection`	`portrait_age_inconsistency`
`id_barcode_detection`	`barcode_not_detected`
`id_blur_detection`	`blurry`
`id_color_inconsistency_detection`	`color_inconsistency`
`id_compromised_detection`	`compromised_image_matched`
`id_disallowed_country_detection`	`disabled_country_code`
`id_disallowed_type_detection`
`id_double_side_detection`	`double_front`
`id_electronic_replica_detection`	`replica_detected`
`id_entity_detection`
`id_expired_detection`	`expired`
`id_extracted_properties_detection`	`layout_mismatched` `attribute_missing`
`id_extraction_inconsistency_detection`	`attribute_missing`
`id_glare_detection`	`glare`
`id_handwriting_detection`
`id_inconsistent_repeat_detection`	`reused_image_matched`
`id_inquiry_comparison`	`claims_conflict`
`id_mrz_detection`	`mrz_not_detected`
`id_portrait_clarity_detection`
`id_portrait_detection`	`portrait_missing`
`id_public_figure_detection`
`id_selfie_comparison`	`selfie_comparison_failure`
`id_tamper_detection`	`image_manipulated` `exif_inconsistency`
`id_unprocessable_submission_detection`	`unprocessable_image`
`id_valid_dates_detection`	`date_inconsistency`
`selfie_account_comparison`	`account_comparison_failure`
`selfie_glare_detection`	`glare`
`selfie_glasses_detection`	`glasses`
`selfie_id_comparison`	`document_comparison_failure`
`selfie_multiple_faces_detection`	`pose_comparison_failure`
`selfie_pose_detection`	`pose_failure`
`selfie_pose_repeat_detection`	`pose_repeat_detected`
`selfie_suspicious_entity_detection`
`database_address_comparison`
`database_birthdate_comparison`
`database_name_comparison`
`database_phone_number_comparison`
`database_social_security_number_comparison`
`document_compromised_detection`
`document_tamper_detection`