Get Checks

GET 
/api/v8/partner/checks

Get Checks

Request

Query Parameters

meta.tags array
Return documents containing these tags.
Example: a
meta.external_id string
Return documents with this meta.external_id.
Example: 123f-2aa-33cc
created_date__gt string
Return documents created after this date and time in ISO 8601 format.
Example: 2022-05-03 00:00:00
created_date__lt string
Return documents created before this date and time in ISO 8601 format.
Example: 2023-03-23 00:00:00
created_date__gte string
Return documents created beginning at this date and time in ISO 8601 format.
Example: 2022-04-24 00:00:00
created_date__lte string
Return documents created on and before this date and time in ISO 8601 format.
Example: 2020-10-15 00:00:00
updated_date__gt string
Return documents updated after this date and time in ISO 8601 format.
Example: 2023-07-25 00:00:00
updated_date__lt string
Return documents updated before this date and time in ISO 8601 format.
Example: 2019-03-18 00:00:00
updated_date__gte string
Return documents updated beginning at this date and time in ISO 8601 format.
Example: 2020-02-03 00:00:00
updated_date__lte string
Return documents updated on and before this date and time in ISO 8601 format.
Example: 2023-01-03 00:00:00
page integer

Default value: 1

The page number. The response is capped to maximum of 50 results per page.

page_size integer
Default value: 50
The number of Documents per page.
Example: 10
bounding_boxes boolean

A field used to determine whether or not to return bounding_box and bounding_region for extracted fields in the Document response.

confidence_details boolean

A field used to determine whether or not to return the score and ocr_score fields in the Document response.

q string
Case sensitive. Return documents with this text or any extracted fields matching the value. Use asterisk for partial matches, e.g. q=Walmart* will return documents with either Walmart in ocr text or any extracted field containing Walmart.
Example: Starbucks
track_total_results boolean

Whether to always return accurate count of results, true makes it slower.

Responses

200

A list of previously processed Checks.

application/json

Schema

Schema

anyOf
API_V8_PARTNER_CHECKS_LISTRESPONSESCHEMA
count integerrequired
The total number of results retrieved across all pages.
next string
The URL to the next page of results.
previous string
The URL to the previous page of results.
results object[]required
The collection of processed Check documents
Array [
external_id string
Possible values: non-empty
A custom identification value. Use this if you would like to assign your own ID to documents. This parameter is useful when mapping this document to a service or resource outside Veryfi.
meta object
external_id string
Possible values: non-empty
A custom identification value. Use this if you would like to assign your own ID to documents. This parameter is useful when mapping this document to a service or resource outside Veryfi.
pages object[]
Pages meta details
Array [
ocr_score number
Possible values: <= 1
The average OCR score of the page.
width integer
The width of the page.
height integer
The height of the page.
is_front boolean
Specifies whether the image represents the front side of the check.
tiff_url uri
Possible values: non-empty and <= 2083 characters
The urls of the tiff file.
]
tags string[]
Possible values: non-empty
Default value: ``
Tags associated with the document.
ocr_score number
Possible values: <= 1
The average OCR score of the whole document.
model string
Possible values: non-empty
The version of the model used to process the document.
fraud object
An object that contains additional information to help check for fraud.
pages object[]
An array containing fraud info about each extracted page
Array [
anyOf
CheckFraudPage
is_lcd object
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
value booleanrequired
The extracted value.
four_corners_detected boolean
Indicates that all four corners of the check are visible and within the boundaries of the image.
flags object[]
Array [
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
value stringrequired
Possible values: non-empty
]
]
score number
Possible values: <= 1
Confidence of Fraud Detector in it's prediction
types string[]
Possible values: [LCD photo, not a document, duplicate, screenshot, aspect ratio mismatch]
List of attributions which marked the document as fraud
duplicates object[]
An array of duplicate documents found in the system.
Array [
id integerrequired
The id of the duplicate document.
url urirequired
Possible values: non-empty and <= 2083 characters
The url of the duplicate document.
]
amount_text_value number
The original amount_text found in the check converted to a float.
handwritten_fields string[]
Possible values: [amount, amount_text, bank_address, bank_name, fractional_routing_number, micr.raw, check_number, date, memo, payer_address, payer_name, receiver_address, receiver_name]
Default value: ``
Handwritten fields on check
pdf_url uri
Possible values: non-empty and <= 2083 characters
A signed URL to access the auto-generated PDF created from the submitted document. This URL expires 15 minutes after the response object is returned and is resigned during every GET request.
id integerrequired
The unique number created to identify the document.
created_date date-timerequired
updated_date date-timerequired
img_thumbnail_url uri
Possible values: non-empty and <= 2083 characters
A signed URL to access the auto-generated thumbnail created for the submitted document. This URL expires 15 minutes after the response object is returned and is resigned during every GET request.
text string
The text returned from converting the document into a machine-readable text format.
custom_fields object
A user-defined dictionary that contains all the custom fields generated by applying specific rules and regular expressions to the extracted data.
property name* any
Default value: [object Object]
A user-defined dictionary that contains all the custom fields generated by applying specific rules and regular expressions to the extracted data.
amount numberrequired
The numeric value representing the amount found on the document.
amount_text stringrequired
Possible values: non-empty
The value as a string representing the amount found on the document.
bank_address stringrequired
Possible values: non-empty
The address of the bank.
bank_name stringrequired
Possible values: non-empty
The name of the bank.
fractional_routing_number string
Possible values: non-empty
The numbers appearing as the denominator of a fraction that is printed in the upper portion of a check.
routing_from_fractional stringrequired
Possible values: non-empty
The routing number from the found in the fractional_routing_number.
check_number stringrequired
Possible values: non-empty
The check number.
date stringrequired
Possible values: non-empty
The date in ISO 8601 format. Typically found on invoices.
memo stringrequired
Possible values: non-empty
The description found in the memo line of the check.
payer_address stringrequired
Possible values: non-empty
The address of the payer.
payer_name stringrequired
Possible values: non-empty
The name of the payer.
receiver_address stringrequired
Possible values: non-empty
The address of the receiver.
receiver_name stringrequired
Possible values: non-empty
The name of the receiver.
is_signed boolean
Presence of a signature on the check (front of check image)
is_endorsed booleandeprecated
deprecated and will be removed at 2024-11-10. Use endorsement.is_signed instead
currency_code stringrequired
Possible values: [SBD, CUP, PEN, BBD, COP, NZD, RSD, BRL, SVC, MOP, KWD, CZK, AMD, AUD, SOS, IDR, GGP, ZAR, EEK, CRC, AZN, MVR, LTL, DOP, TRY, KHR, NIO, MNT, GNF, SCR, IMP, JPY, INR, TTD, HNL, SYP, GHC, ILS, KRW, BGN, FKP, KPW, HKD, NGN, EGP, LBP, RUB, NOK, BOB, TVD, ANG, MXN, HUF, RON, CHF, HRK, BAM, FJD, MZN, PHP, USD, GIP, MYR, NPR, TRL, AFN, JMD, DKK, SRD, SGD, GEL, ALL, UZS, PYG, JEP, LSL, QAR, LRD, ZWD, SEK, GTQ, KZT, LAK, KYD, LKR, GBP, LVL, YER, AWG, TWD, MUR, UAH, OMR, CLP, UGX, MKD, GYD, IRR, SAR, NAD, PKR, VEF, BWP, KGS, SHP, ISK, EUR, AED, CAD, HTG, ARS, XCD, THB, SZL, PAB, PLN, UYU, CNY, VND, BHD, IQD, BYR, BSD, BND, BZD, BMD]
endorsement object
An object containing the endorsement details
is_signed boolean
Presence of an endorsement signature (back of check image).
is_mobile_or_remote_deposit_only boolean
Presence of restricted endorsement text such as mobile or remote deposit only
micr object
An object containing the details for the Magnetic ink character recognition.
routing_number string
Possible values: non-empty
The Transit Field. It is always 8-9 digits, preceded by a ⑆, and followed by a ⑆.
account_number stringrequired
Possible values: non-empty
The bank account number.
serial_number string
Possible values: non-empty
The serial number on checks.
raw string
Possible values: non-empty
The text returned from converting the document into a machine-readable text format.
]
API_V8_PARTNER_CHECKS_DETAILEDLISTRESPONSESCHEMA
count integerrequired
The total number of results retrieved across all pages.
next string
The URL to the next page of results.
previous string
The URL to the previous page of results.
results object[]required
The collection of processed Check documents
Array [
external_id string
Possible values: non-empty
A custom identification value. Use this if you would like to assign your own ID to documents. This parameter is useful when mapping this document to a service or resource outside Veryfi.
meta object
external_id string
Possible values: non-empty
A custom identification value. Use this if you would like to assign your own ID to documents. This parameter is useful when mapping this document to a service or resource outside Veryfi.
pages object[]
Pages meta details
Array [
ocr_score number
Possible values: <= 1
The average OCR score of the page.
width integer
The width of the page.
height integer
The height of the page.
is_front boolean
Specifies whether the image represents the front side of the check.
tiff_url uri
Possible values: non-empty and <= 2083 characters
The urls of the tiff file.
]
tags string[]
Possible values: non-empty
Default value: ``
Tags associated with the document.
ocr_score number
Possible values: <= 1
The average OCR score of the whole document.
model string
Possible values: non-empty
The version of the model used to process the document.
fraud object
An object that contains additional information to help check for fraud.
pages object[]
An array containing fraud info about each extracted page
Array [
anyOf
CheckFraudPage
is_lcd object
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
value booleanrequired
The extracted value.
four_corners_detected boolean
Indicates that all four corners of the check are visible and within the boundaries of the image.
flags object[]
Array [
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
value stringrequired
Possible values: non-empty
]
]
score number
Possible values: <= 1
Confidence of Fraud Detector in it's prediction
types string[]
Possible values: [LCD photo, not a document, duplicate, screenshot, aspect ratio mismatch]
List of attributions which marked the document as fraud
duplicates object[]
An array of duplicate documents found in the system.
Array [
id integerrequired
The id of the duplicate document.
url urirequired
Possible values: non-empty and <= 2083 characters
The url of the duplicate document.
score numberrequired
Possible values: >= 0.7 and <= 1
The confidence score between 0 and 1.
]
amount_text_value number
The original amount_text found in the check converted to a float.
handwritten_fields string[]
Possible values: [amount, amount_text, bank_address, bank_name, fractional_routing_number, micr.raw, check_number, date, memo, payer_address, payer_name, receiver_address, receiver_name]
Default value: ``
Handwritten fields on check
pdf_url uri
Possible values: non-empty and <= 2083 characters
A signed URL to access the auto-generated PDF created from the submitted document. This URL expires 15 minutes after the response object is returned and is resigned during every GET request.
id integerrequired
The unique number created to identify the document.
created_date date-timerequired
updated_date date-timerequired
img_thumbnail_url uri
Possible values: non-empty and <= 2083 characters
A signed URL to access the auto-generated thumbnail created for the submitted document. This URL expires 15 minutes after the response object is returned and is resigned during every GET request.
text string
The text returned from converting the document into a machine-readable text format.
custom_fields object
A user-defined dictionary that contains all the custom fields generated by applying specific rules and regular expressions to the extracted data.
property name* any
Default value: [object Object]
A user-defined dictionary that contains all the custom fields generated by applying specific rules and regular expressions to the extracted data.
amount objectrequired
The numeric value representing the amount found on the document.
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
bounding_region number[]
Possible values: >= 8, <= 8
An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.
bounding_box object[]
Possible values: >= 5, <= 5
An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.
Array [
anyOf
MOD1
number
MOD2
integer
]
ocr_score number
Possible values: <= 1
The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value numberrequired
amount_text objectrequired
The value as a string representing the amount found on the document.
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
bounding_region number[]
Possible values: >= 8, <= 8
An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.
bounding_box object[]
Possible values: >= 5, <= 5
An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.
Array [
anyOf
MOD1
number
MOD2
integer
]
ocr_score number
Possible values: <= 1
The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value stringrequired
Possible values: non-empty
The extracted value.
bank_address objectrequired
The address of the bank.
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
bounding_region number[]
Possible values: >= 8, <= 8
An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.
bounding_box object[]
Possible values: >= 5, <= 5
An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.
Array [
anyOf
MOD1
number
MOD2
integer
]
ocr_score number
Possible values: <= 1
The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value stringrequired
Possible values: non-empty
The extracted value.
bank_name objectrequired
The name of the bank.
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
bounding_region number[]
Possible values: >= 8, <= 8
An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.
bounding_box object[]
Possible values: >= 5, <= 5
An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.
Array [
anyOf
MOD1
number
MOD2
integer
]
ocr_score number
Possible values: <= 1
The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value stringrequired
Possible values: non-empty
The extracted value.
fractional_routing_number object
The numbers appearing as the denominator of a fraction that is printed in the upper portion of a check.
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
bounding_region number[]
Possible values: >= 8, <= 8
An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.
bounding_box object[]
Possible values: >= 5, <= 5
An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.
Array [
anyOf
MOD1
number
MOD2
integer
]
ocr_score number
Possible values: <= 1
The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value stringrequired
Possible values: non-empty
The extracted value.
routing_from_fractional objectrequired
The routing number from the found in the fractional_routing_number.
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
bounding_region number[]
Possible values: >= 8, <= 8
An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.
bounding_box object[]
Possible values: >= 5, <= 5
An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.
Array [
anyOf
MOD1
number
MOD2
integer
]
ocr_score number
Possible values: <= 1
The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value stringrequired
Possible values: non-empty
The extracted value.
check_number objectrequired
The check number.
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
bounding_region number[]
Possible values: >= 8, <= 8
An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.
bounding_box object[]
Possible values: >= 5, <= 5
An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.
Array [
anyOf
MOD1
number
MOD2
integer
]
ocr_score number
Possible values: <= 1
The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value stringrequired
Possible values: non-empty
The extracted value.
date objectrequired
The date in ISO 8601 format. Typically found on invoices.
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
bounding_region number[]
Possible values: >= 8, <= 8
An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.
bounding_box object[]
Possible values: >= 5, <= 5
An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.
Array [
anyOf
MOD1
number
MOD2
integer
]
ocr_score number
Possible values: <= 1
The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value daterequired
memo objectrequired
The description found in the memo line of the check.
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
bounding_region number[]
Possible values: >= 8, <= 8
An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.
bounding_box object[]
Possible values: >= 5, <= 5
An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.
Array [
anyOf
MOD1
number
MOD2
integer
]
ocr_score number
Possible values: <= 1
The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value stringrequired
Possible values: non-empty
The extracted value.
payer_address objectrequired
The address of the payer.
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
bounding_region number[]
Possible values: >= 8, <= 8
An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.
bounding_box object[]
Possible values: >= 5, <= 5
An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.
Array [
anyOf
MOD1
number
MOD2
integer
]
ocr_score number
Possible values: <= 1
The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value stringrequired
Possible values: non-empty
The extracted value.
payer_name objectrequired
The name of the payer.
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
bounding_region number[]
Possible values: >= 8, <= 8
An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.
bounding_box object[]
Possible values: >= 5, <= 5
An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.
Array [
anyOf
MOD1
number
MOD2
integer
]
ocr_score number
Possible values: <= 1
The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value stringrequired
Possible values: non-empty
The extracted value.
receiver_address objectrequired
The address of the receiver.
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
bounding_region number[]
Possible values: >= 8, <= 8
An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.
bounding_box object[]
Possible values: >= 5, <= 5
An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.
Array [
anyOf
MOD1
number
MOD2
integer
]
ocr_score number
Possible values: <= 1
The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value stringrequired
Possible values: non-empty
The extracted value.
receiver_name objectrequired
The name of the receiver.
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
bounding_region number[]
Possible values: >= 8, <= 8
An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.
bounding_box object[]
Possible values: >= 5, <= 5
An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.
Array [
anyOf
MOD1
number
MOD2
integer
]
ocr_score number
Possible values: <= 1
The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value stringrequired
Possible values: non-empty
The extracted value.
is_signed objectrequired
Presence of a signature on the check (front of check image)
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
bounding_region number[]
Possible values: >= 8, <= 8
An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.
bounding_box object[]
Possible values: >= 5, <= 5
An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.
Array [
anyOf
MOD1
number
MOD2
integer
]
ocr_score number
Possible values: <= 1
The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value booleanrequired
is_endorsed objectdeprecated
deprecated and will be removed at 2024-11-10. Use endorsement.is_signed instead
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
bounding_region number[]
Possible values: >= 8, <= 8
An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.
bounding_box object[]
Possible values: >= 5, <= 5
An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.
Array [
anyOf
MOD1
number
MOD2
integer
]
ocr_score number
Possible values: <= 1
The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value booleanrequired
currency_code objectrequired
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
value stringrequired
Possible values: [SBD, CUP, PEN, BBD, COP, NZD, RSD, BRL, SVC, MOP, KWD, CZK, AMD, AUD, SOS, IDR, GGP, ZAR, EEK, CRC, AZN, MVR, LTL, DOP, TRY, KHR, NIO, MNT, GNF, SCR, IMP, JPY, INR, TTD, HNL, SYP, GHC, ILS, KRW, BGN, FKP, KPW, HKD, NGN, EGP, LBP, RUB, NOK, BOB, TVD, ANG, MXN, HUF, RON, CHF, HRK, BAM, FJD, MZN, PHP, USD, GIP, MYR, NPR, TRL, AFN, JMD, DKK, SRD, SGD, GEL, ALL, UZS, PYG, JEP, LSL, QAR, LRD, ZWD, SEK, GTQ, KZT, LAK, KYD, LKR, GBP, LVL, YER, AWG, TWD, MUR, UAH, OMR, CLP, UGX, MKD, GYD, IRR, SAR, NAD, PKR, VEF, BWP, KGS, SHP, ISK, EUR, AED, CAD, HTG, ARS, XCD, THB, SZL, PAB, PLN, UYU, CNY, VND, BHD, IQD, BYR, BSD, BND, BZD, BMD]
endorsement object
An object containing the endorsement details
is_signed object
Presence of an endorsement signature (back of check image).
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
bounding_region number[]
Possible values: >= 8, <= 8
An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.
bounding_box object[]
Possible values: >= 5, <= 5
An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.
Array [
anyOf
MOD1
number
MOD2
integer
]
ocr_score number
Possible values: <= 1
The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value booleanrequired
is_mobile_or_remote_deposit_only object
Presence of restricted endorsement text such as mobile or remote deposit only
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
bounding_region number[]
Possible values: >= 8, <= 8
An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.
bounding_box object[]
Possible values: >= 5, <= 5
An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.
Array [
anyOf
MOD1
number
MOD2
integer
]
ocr_score number
Possible values: <= 1
The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value booleanrequired
micr object
An object containing the details for the Magnetic ink character recognition.
routing_number object
The Transit Field. It is always 8-9 digits, preceded by a ⑆, and followed by a ⑆.
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
bounding_region number[]
Possible values: >= 8, <= 8
An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.
bounding_box object[]
Possible values: >= 5, <= 5
An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.
Array [
anyOf
MOD1
number
MOD2
integer
]
ocr_score number
Possible values: <= 1
The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value stringrequired
Possible values: non-empty
The extracted value.
account_number objectrequired
The bank account number.
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
bounding_region number[]
Possible values: >= 8, <= 8
An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.
bounding_box object[]
Possible values: >= 5, <= 5
An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.
Array [
anyOf
MOD1
number
MOD2
integer
]
ocr_score number
Possible values: <= 1
The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value stringrequired
Possible values: non-empty
The extracted value.
serial_number object
The serial number on checks.
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
bounding_region number[]
Possible values: >= 8, <= 8
An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.
bounding_box object[]
Possible values: >= 5, <= 5
An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.
Array [
anyOf
MOD1
number
MOD2
integer
]
ocr_score number
Possible values: <= 1
The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value stringrequired
Possible values: non-empty
The extracted value.
raw object
The text returned from converting the document into a machine-readable text format.
score number
Possible values: <= 1
The score shows how confident the model is that the predicted value belongs to the field. See confidence scores explained for more information.
bounding_region number[]
Possible values: >= 8, <= 8
An array containing (x,y) coordinates in the format [x1,y1,x2,y2,x3,y3,x4,y4]` for skewed images and handwritten fields. The bounding region is more precise than bounding box, otherwise it's the same.
bounding_box object[]
Possible values: >= 5, <= 5
An array containing relative coordinates in the format [page_number,x1,y1,x2,y2] for the extracted field from img_url before any rotation.
Array [
anyOf
MOD1
number
MOD2
integer
]
ocr_score number
Possible values: <= 1
The score which shows how confident the model in recognizing value symbols. See confidence scores explained for more information.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value stringrequired
Possible values: non-empty
The extracted value.
]

Example (from schema)

{}

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