When using the callback, ShareID can return the customer_data you provided. This information is for your internal use and will only be included in the callback
4
document
object
1.applicant_id
The applicant_id uniquely identifies the user in our system. You should keep track of this value in order to later. If you're using a callback, the applicant_id will also be send to your server (check here ).
"ap-...
2.reasons
The list of rejection reasons among the values below. This list is empty if the onboarding is accepted.
doc_expired
document expired
no_doc
document blurry, occluded or poorly illuminated
doc_spoof
document printed or shown on screen (spoofing)
doc_inject
document injected or digitally modified
doc_mismatch
document front and back do not match
doc_fraud
fraud suspicion on document
no_face
face detection problem: blurry, occluded or poorly illuminated
face_spoof
face printed or shown on screen (spoofing)
face_inject
face injected or DeepFake
face_fraud
fraud on document ownership
multiple_faces
Multiple faces present in the video
analysis_failed
Analysis has failed
operator_failed
Operator has failed
name_not_extracted or surname_not_extracted
Name or surname couldn't be extracted
3.customer_data
Any data you sent with the onboarding request here:
4.document
This field contains the information extracted from the user ID document and the analysis result.
{
"type": {
"doc_type": "",
"doc_model": "",
"country_code": "",
},
"ocr": {
// Personal data extracted from user document -- see examples below
},
"doc_front": "",
"doc_back": "",
"face_face": "",
"face_doc": ""
}
Field
Type
doc_type
string
one of: "id_card" "passport" "driver_permit" "residency_permit"
doc_model
string
internal model reference detected
country_code
string
country code ISO 3166-1.alpha-2
doc_front
string | null
base64 encoded image of document front page
doc_back
string | null
base64 encoded image of document back page
face_face
string | null
base64 encoded image of face from liveness
face_doc
string | null
base64 encoded image of face from document
As you'll receive the images in a json document they will be encoded in base64. So you will need to decode them on your side.
Note that those images are not sent by default because it makes the json document largely heavier.
Result examples
{
"type": {
"doc_type": "passport",
"doc_model": "2006",
"country_code": "fr",
},
"ocr": {
"doc_num": "", //if it appears on the document
"surname": "",//if it appears on the document
"alternate_name": "",//if it appears on the document
"widow_of": "",//if it appears on the document
"mariage_name": "",//if it appears on the document
"name": "",//if it appears on the document
"height": "",//if it appears on the document
"birth_place": "",//if it appears on the document
"birth_date": "",//if it appears on the document
"address": "",//if it appears on the document
"expiration_date": "",//if it appears on the document
"issuance_date": "",//if it appears on the document
"issuance_place": "",//if it appears on the document
},
"doc_front": "",
"doc_back": "",
"face_face": "",
"face_doc": ""
}
The same applicant_id you receive when
If rejected, this will indicate theof the rejection
The document field contains the information extracted from the user ID document and the analysis result see for details