Submit Customer Bank Statement (PDF)

Upload a PDF bank statement for automatic transaction extraction and enrichment.

Endpoint: POST https://api.walkerstdata.com.au/v1/customer/{customerId}/transactions/pdf

File Requirements

• Banks supported: CBA, ANZ, NAB, WBC, Bendigo, BOQ, St George, Suncorp, Tyro
• Format: PDF (machine-readable only; scanned images are not supported)
• File Size: Maximum 10MB
• Content: Bank statement containing transaction data
• Upload Method: Multipart form data

Request

cURL

curl -X POST "https://api.walkerstdata.com.au/v1/customer/a3feb546-bc8f-49b3-8f7b-499b6e0d3a28/transactions/pdf" \
  -H "x-api-key: YOUR_API_KEY" \
  -F "file=@/path/to/bank_statement.pdf"

JavaScript

const customerId = 'a3feb546-bc8f-49b3-8f7b-499b6e0d3a28';
const fileInput = document.getElementById('pdfFile'); // HTML file input
const file = fileInput.files[0];

const formData = new FormData();
formData.append('file', file);

const response = await fetch(`https://api.walkerstdata.com.au/v1/customer/${customerId}/transactions/pdf`, {
  method: 'POST',
  headers: {
    'x-api-key': 'YOUR_API_KEY',
  },
  body: formData
});

const result = await response.json();
const jobId = result.data.jobId;
console.log('PDF submitted, job ID:', jobId);

Python

import requests

customer_id = 'a3feb546-bc8f-49b3-8f7b-499b6e0d3a28'

# Open and upload PDF file
with open('/path/to/bank_statement.pdf', 'rb') as pdf_file:
    files = {'file': pdf_file}
    response = requests.post(
        f'https://api.walkerstdata.com.au/v1/customer/{customer_id}/transactions/pdf',
        headers={'x-api-key': 'YOUR_API_KEY'},
        files=files
    )

result = response.json()
job_id = result['data']['jobId']
print(f'PDF submitted, job ID: {job_id}')

Response

{
  "data": {
    "jobId": "550e8400-e29b-41d4-a716-446655440000",
    "status": "New",
    "message": "",
    "type": "Extraction",
    "totalReceivedTransactions": 1,
    "totalProcessedTransactions": 0
  },
  "message": null
}

Processing Flow

The PDF submission triggers a two-stage process:

1. OCR Extraction: PDF content is analyzed to extract individual transaction records
2. Transaction Enrichment: Extracted transactions can be categorized

Both stages are tracked under the single returned jobId for monitoring progress.

Job Monitoring

After submission, monitor the processing status:

cURL

curl -X GET "https://api.walkerstdata.com.au/v1/jobs/550e8400-e29b-41d4-a716-446655440000/status" \
  -H "x-api-key: YOUR_API_KEY"

JavaScript

const jobId = '550e8400-e29b-41d4-a716-446655440000';

const checkStatus = async () => {
  const response = await fetch(`https://api.walkerstdata.com.au/v1/jobs/${jobId}/status`, {
    headers: { 'x-api-key': 'YOUR_API_KEY' }
  });

  const status = await response.json();
  return status.data.status; // 'New', 'Processing', 'Completed', 'Failed'
};

Python

import requests
import time

job_id = '550e8400-e29b-41d4-a716-446655440000'

def check_job_status(job_id):
    response = requests.get(
        f'https://api.walkerstdata.com.au/v1/jobs/{job_id}/status',
        headers={'x-api-key': 'YOUR_API_KEY'}
    )
    return response.json()['data']['status']

# Poll until complete
while True:
    status = check_job_status(job_id)
    if status in ['Completed', 'Failed']:
        break
    time.sleep(10)  # Wait 10 seconds before checking again

Retrieving Results

Once the job shows complete status, retrieve the enriched transactions:

cURL

curl -X GET "https://api.walkerstdata.com.au/v1/customer/a3feb546-bc8f-49b3-8f7b-499b6e0d3a28/transactions?jobId=550e8400-e29b-41d4-a716-446655440000" \
  -H "x-api-key: YOUR_API_KEY"

JavaScript

const customerId = 'a3feb546-bc8f-49b3-8f7b-499b6e0d3a28';
const jobId = '550e8400-e29b-41d4-a716-446655440000';

const response = await fetch(`https://api.walkerstdata.com.au/v1/customer/${customerId}/transactions?jobId=${jobId}`, {
  headers: { 'x-api-key': 'YOUR_API_KEY' }
});

const result = await response.json();
const transactions = result.data.transactions;

Python

import requests

customer_id = 'a3feb546-bc8f-49b3-8f7b-499b6e0d3a28'
job_id = '550e8400-e29b-41d4-a716-446655440000'

response = requests.get(
    f'https://api.walkerstdata.com.au/v1/customer/{customer_id}/transactions',
    headers={'x-api-key': 'YOUR_API_KEY'},
    params={'jobId': job_id}
)

transactions = response.json()['data']['transactions']

Use Cases

• Data digitization: Convert PDF statements to structured, categorized transaction data
• Bulk transaction processing: Handle multiple months of statements efficiently

Next Steps

After successful PDF processing, you can:

• Analyze results: Review extracted and categorized transaction data
• Export data: Integrate enriched transactions into accounting systems
• Validate accuracy: Check OCR extraction quality and AI categorizations
• Process additional statements: Submit more PDFs for the same customer