Update a Bank Statement

PUT 
/api/v8/partner/bank-statements/:document_id

Veryfi's Update a Document by ID endpoint allows you to change a Document that Veryfi's Machine Learning models have already processed. This feature will enable users to update Documents previously processed by Veryfi to ensure data extraction accuracy. Updating a Document is especially useful for correcting mistakes and updating information over time. By changing a processed Document, Veryfi's Machine Learning models can re-learn the updated information, allowing them to stay accurate and up-to-date.

Request

Path Parameters

document_id int64required

The unique identifier of the document.

application/json

Body

external_id stringdeprecated

Possible values: non-empty

Deprecated 2025-01-09, use meta.external_id instead.

meta object

external_id stringrequired

Possible values: non-empty

Responses

200

A processed Bank Statement response.

application/json

Schema

Schema

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.
fraud object
An object that contains additional information to identify fraud.
score number
Possible values: <= 1
Confidence of Fraud Detector in it's prediction
types string[]
Possible values: [LCD photo, not a document, duplicate, screenshot]
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.
]
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.

account_holder_address object

The address of the account holder.

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.

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.

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_holder_name object

The name of the account holder.

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.

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.

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 object

The account number associated with the bank statement.

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.

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.

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_numbers object[]required
Array [
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.
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.
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_type object

The type of account associated with the bank statement.

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.

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.

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_vat_number object

The unique identifier for businesses used for tax purposes

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.

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.

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 object

The address of the bank.

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.

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.

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 object

The name of the bank.

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.

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.

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_vat_number object

The unique identifier assigned to a bank for tax purposes

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.

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.

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_website object

The URL for the website of the bank.

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.

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.

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.

beginning_balance object
The balance at the beginning of the statement period.
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.
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.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value numberrequired
currency_code object

The currency code associated with the bank statement.

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.

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.

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.

due_date object
The date the payment is due in ISO 8601 format.
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.
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.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value daterequired
ending_balance object
The balance at the end of the statement period.
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.
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.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value numberrequired
iban_number object

The International Bank Account Number

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.

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.

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.

minimum_due object
The minimum amount due for the statement period.
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.
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.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value numberrequired
period_end_date object
The end date of the statement period in ISO 8601 format.
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.
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.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value daterequired
period_start_date object
The start date of the statement period in ISO 8601 format.
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.
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.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value daterequired
routing_number object

The routing number associated with the bank statement.

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.

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.

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_numbers object[]required
Array [
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.
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.
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.
]
statement_date object
The date of the statement in ISO 8601 format.
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.
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.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value daterequired
statement_number object

The unique identifier associated with the bank statement.

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.

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.

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.

swift object

The unique identifier for a bank used in international transactions

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.

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.

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.

transactions object[]required
A list of transactions associated with the bank statement.
Array [
order integerrequired
The value indicating the position of where the transaction appears on the bank statement.
account_number object
The account number associated with the bank statement.
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.
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.
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.
balance object
The balance after any credit or debits have been applied from this transaction.
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.
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.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value numberrequired
card_number object
A credit card number associated with this transaction.
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.
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.
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.
credit_amount object
The amount credited from this transaction.
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.
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.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value numberrequired
date object
The date of the transaction in ISO 8601 format.
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.
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.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value daterequired
posted_date object
The date the transaction was posted in ISO 8601 format.
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.
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.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value daterequired
debit_amount object
The amount debited from this transaction.
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.
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.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value numberrequired
description object
The description of the transaction.
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.
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.
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.
transaction_id object
The unique identifier of the transaction.
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.
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.
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.
text object
The OCR text extracted from the transaction.
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.
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.
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.
]
summaries object[]required
Summary information
Array [
name object
The title or label that captures the main 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.
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.
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.
total object
The overall amount calculated from all transactions
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.
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.
rotation integer
Possible values: [0, 90, 180, 270]
The angle of rotation of the document in degrees.
value numberrequired
]

Example (from schema)

{
  "external_id": "string",
  "meta": {
    "external_id": "string",
    "fraud": {
      "score": 0,
      "types": [
        "LCD photo"
      ]
    },
    "duplicates": [
      {
        "id": 0,
        "url": "string",
        "score": 0
      }
    ]
  },
  "pdf_url": "string",
  "id": 0,
  "created_date": "2025-01-25T22:06:11.771Z",
  "updated_date": "2025-01-25T22:06:11.771Z",
  "img_thumbnail_url": "string",
  "account_holder_address": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "account_holder_name": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "account_number": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "account_numbers": [
    {
      "bounding_region": [
        0
      ],
      "bounding_box": [
        0,
        0
      ],
      "ocr_score": 0,
      "score": 0,
      "rotation": 0,
      "value": "string"
    }
  ],
  "account_type": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "account_vat_number": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "bank_address": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "bank_name": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "bank_vat_number": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "bank_website": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "beginning_balance": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": 0
  },
  "currency_code": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "due_date": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "2025-01-25"
  },
  "ending_balance": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": 0
  },
  "iban_number": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "minimum_due": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": 0
  },
  "period_end_date": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "2025-01-25"
  },
  "period_start_date": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "2025-01-25"
  },
  "routing_number": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "routing_numbers": [
    {
      "bounding_region": [
        0
      ],
      "bounding_box": [
        0,
        0
      ],
      "ocr_score": 0,
      "score": 0,
      "rotation": 0,
      "value": "string"
    }
  ],
  "statement_date": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "2025-01-25"
  },
  "statement_number": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "swift": {
    "bounding_region": [
      0
    ],
    "bounding_box": [
      0,
      0
    ],
    "ocr_score": 0,
    "score": 0,
    "rotation": 0,
    "value": "string"
  },
  "transactions": [
    {
      "order": 0,
      "account_number": {
        "bounding_region": [
          0
        ],
        "bounding_box": [
          0,
          0
        ],
        "ocr_score": 0,
        "score": 0,
        "rotation": 0,
        "value": "string"
      },
      "balance": {
        "bounding_region": [
          0
        ],
        "bounding_box": [
          0,
          0
        ],
        "ocr_score": 0,
        "score": 0,
        "rotation": 0,
        "value": 0
      },
      "card_number": {
        "bounding_region": [
          0
        ],
        "bounding_box": [
          0,
          0
        ],
        "ocr_score": 0,
        "score": 0,
        "rotation": 0,
        "value": "string"
      },
      "credit_amount": {
        "bounding_region": [
          0
        ],
        "bounding_box": [
          0,
          0
        ],
        "ocr_score": 0,
        "score": 0,
        "rotation": 0,
        "value": 0
      },
      "date": {
        "bounding_region": [
          0
        ],
        "bounding_box": [
          0,
          0
        ],
        "ocr_score": 0,
        "score": 0,
        "rotation": 0,
        "value": "2025-01-25"
      },
      "posted_date": {
        "bounding_region": [
          0
        ],
        "bounding_box": [
          0,
          0
        ],
        "ocr_score": 0,
        "score": 0,
        "rotation": 0,
        "value": "2025-01-25"
      },
      "debit_amount": {
        "bounding_region": [
          0
        ],
        "bounding_box": [
          0,
          0
        ],
        "ocr_score": 0,
        "score": 0,
        "rotation": 0,
        "value": 0
      },
      "description": {
        "bounding_region": [
          0
        ],
        "bounding_box": [
          0,
          0
        ],
        "ocr_score": 0,
        "score": 0,
        "rotation": 0,
        "value": "string"
      },
      "transaction_id": {
        "bounding_region": [
          0
        ],
        "bounding_box": [
          0,
          0
        ],
        "ocr_score": 0,
        "score": 0,
        "rotation": 0,
        "value": "string"
      },
      "text": {
        "bounding_region": [
          0
        ],
        "bounding_box": [
          0,
          0
        ],
        "ocr_score": 0,
        "score": 0,
        "rotation": 0,
        "value": "string"
      }
    }
  ],
  "summaries": [
    {
      "name": {
        "bounding_region": [
          0
        ],
        "bounding_box": [
          0,
          0
        ],
        "ocr_score": 0,
        "score": 0,
        "rotation": 0,
        "value": "string"
      },
      "total": {
        "bounding_region": [
          0
        ],
        "bounding_box": [
          0,
          0
        ],
        "ocr_score": 0,
        "score": 0,
        "rotation": 0,
        "value": 0
      }
    }
  ]
}

400

User error

application/json

Schema

Schema

oneOf

MALFORMED_PARAMETERS

status string

Default value: fail

error string

Default value: Malformed parameters

details undefined[]

Default value: [object Object]

Example (from schema)

{}

403

User error

application/json

Schema

Schema

oneOf

AUTHENTICATION_CREDENTIALS_WERE_NOT_PROVIDED

status string

Default value: fail

error string

Default value: Authentication credentials were not provided.

Example (from schema)

{}

404

Not found

application/json

Schema

Schema

oneOf

NOT_FOUND

status string

Default value: fail

error string

Default value: Not found.

DOCUMENT_NOT_FOUND

status string

Default value: fail

error string

Default value: Document Not Found

Example (from schema)

{}

429

Rate limit

application/json

Schema

Schema

oneOf

YOU_HAVE_BEEN_RATE_LIMITED

status string

Default value: fail

error string

Default value: You have been rate limited

details undefined[]

Default value: [object Object]

Example (from schema)

{}

499

User error

application/json

Schema

Schema

oneOf

CLIENT_CLOSED_REQUEST_OR_LOST_CONNECTION

status string

Default value: fail

error string

Default value: Client closed request or lost connection

Example (from schema)

{}

503

Service is temporarily unavailable

application/json

Schema

Schema

oneOf

SERVICE_IS_TEMPORARILY_UNAVAILABLE_PLEASE_TRY_AGAIN_LATER

status string

Default value: fail

error string

Default value: Service is temporarily unavailable. Please try again later

Example (from schema)

{}

504

Gateway timeout. Returned if request takes more than 150 seconds. The request might finish successfully later.

application/json

Schema

Schema

oneOf

GATEWAY_TIMEOUT

status string

Default value: fail

error string

Default value: Gateway timeout

Example (from schema)

{}

default

OperationStatus

application/json

Schema

Schema

status string

Default value: fail

error stringrequired
details object[]

Example (from schema)

{
  "status": "fail",
  "error": "string",
  "details": [
    {}
  ]
}

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