AI-powered OCR API

The Cost-saving
Bank Statement Converter

Valitract extracts every transaction and balance from bank statement, and delivers clean Excel from PDF in under 3 seconds, with 98% accuracy and a 40% cost saving in comparison with other software.

98% accuracy rate
3s per document
$0.05 cost per statement
Enterprise-grade security

Upload a Bank Statement.
See Extraction in Action

Drop any bank statement PDF and watch Valitract extract every transaction, balance, and account detail into a structured spreadsheet in seconds. Download as Excel, copy as JSON, or push straight to your accounting system. No account needed. No setup.

Upload

Drop, Upload and Paste your file here to Extract Text from Image

Supported file types:   PNG | JPG | JPEG

Your privacy is protected! Your files are secure and never stored.

Data security is our top priority

Valitract is built with security and privacy as foundational principles. We follow GDPR-aligned data handling practices, with SOC 2 Type II and ISO 27001 certifications currently in progress.

One Bank Statement Converter
for Every Financial Workflow

Accounting & Bookkeeping

Loan Underwriting

Tax Preparation

Expense Auditing

Financial Reconciliation

Fraud Detection & Compliance

Why choose Valitract
to convert bank statement

Automated Bank statement Processing

Captures every key bank statement field – transaction row, running balance, and account field – to your preferred structure or format.

3 Second Per bank statement

Your team spends an average of 23 minutes per expense report on data entry alone. Valitract’s bank statement OCR software cuts that to under 3 seconds.

Reduced Operational Costs

At $0.05–$0.10 per statement, Valitract help you save 40% of operation cost in comparison with other extraction software.

Seamless System Integration

JSON output plugs directly into QuickBooks, SAP, NetSuite, Xero, or any custom accounting system with minimal engineering effort.

Scalable Solution

Effortlessly scale to handle growing bank statement volumes, processing over 100,000 bank statements per hour with 99.9% uptime.

Bank-Grade Security, Always

Documents are processed securely and never retained after extraction. Full audit logs, encryption in transit and at rest, and GDPR-aligned practices.

Convert Bank Statement PDF to Excel
in 4 Easy Steps

Upload
Upload any file or data from mail attachments to scanned documents. Our AI-powered OCR receives the rest.

Supported formats include: jpg, png, gif, jpeg, tiff, webp, and more.
Extract
Our advanced AI-Powered OCR analyses and extracts data from documents without relying on templates.
Validate
Use AI-powered engine validates data flags any missing or questionable information, ensuring you to enhance data accuracy and without worry.
Export
Forward structured data to your CRM, ERP, application or database directly with the API integration.
OCR Process Illustration

The easiest OCR API for
Bank Statement

Designed for real engineering teams – not demo-ware. Full SDK support. Webhook-ready.
Handles high-volume bursts without rate-limit surprises.

import java.io.*;
import java.net.*;
import org.json.*;

public class ValitractOCR {
  private static final String API_KEY = "your_api_key_here";
  private static final String API_URL = "https://api.valitract.com/api/v1/extract-generic";

  public static void main(String[] args) {
    try {
      File file = new File("document.pdf");
      String result = processOCR(file);
      System.out.println("Extracted Data: " + result);
    } catch (Exception e) {
      e.printStackTrace();
    }
  }

  public static String processOCR(File file) throws Exception {
    HttpURLConnection conn = (HttpURLConnection) new URL(API_URL).openConnection();
    conn.setRequestMethod("POST");
    conn.setRequestProperty("Authorization", "Bearer " + API_KEY);
    conn.setDoOutput(true);
    
    // Upload file and get response
    return "JSON Response";
  }
}
package main

import (
  "bytes"
  "encoding/json"
  "fmt"
  "io"
  "mime/multipart"
  "net/http"
  "os"
)

const (
  apiKey = "your_api_key_here"
  apiURL = "https://api.valitract.com/api/v1/extract-generic"
)

type OCRResponse struct {
  FileName      string `json:"file_name"`
  ExtractedData map[string]interface{} `json:"extracted_data"`
}

func processOCR(filePath string) (*OCRResponse, error) {
  file, err := os.Open(filePath)
  if err != nil {
    return nil, err
  }
  defer file.Close()

  body := &bytes.Buffer{}
  writer := multipart.NewWriter(body)
  part, _ := writer.CreateFormFile("file", filePath)
  io.Copy(part, file)
  writer.Close()

  req, _ := http.NewRequest("POST", apiURL, body)
  req.Header.Set("Authorization", "Bearer "+apiKey)
  req.Header.Set("Content-Type", writer.FormDataContentType())

  client := &http.Client{}
  resp, err := client.Do(req)
  if err != nil {
    return nil, err
  }
  defer resp.Body.Close()

  var result OCRResponse
  json.NewDecoder(resp.Body).Decode(&result)
  return &result, nil
}

func main() {
  result, err := processOCR("document.pdf")
  if err != nil {
    fmt.Println("Error:", err)
    return
  }
  fmt.Printf("Extracted Data: %+v\n", result)
}
const axios = require('axios');
const FormData = require('form-data');
const fs = require('fs');

const API_KEY = 'your_api_key_here';
const API_URL = 'https://api.valitract.com/api/v1/extract-generic';

async function processOCR(filePath) {
  try {
    const form = new FormData();
    form.append('file', fs.createReadStream(filePath));

    const response = await axios.post(API_URL, form, {
      headers: {
        'Authorization': `Bearer ${API_KEY}`,
        ...form.getHeaders()
      }
    });

    console.log('Extracted Data:', response.data);
    return response.data;
  } catch (error) {
    console.error('Error processing OCR:', error.message);
    throw error;
  }
}

// Usage
processOCR('document.pdf')
  .then(data => console.log('Success:', data))
  .catch(err => console.error('Failed:', err));
<?php

define('API_KEY', 'your_api_key_here');
define('API_URL', 'https://api.valitract.com/api/v1/extract-generic');

function processOCR($filePath) {
  if (!file_exists($filePath)) {
    throw new Exception("File not found: $filePath");
  }

  $ch = curl_init();
  
  $cfile = new CURLFile($filePath, mime_content_type($filePath), basename($filePath));
  
  $data = [
    'file' => $cfile
  ];

  curl_setopt_array($ch, [
    CURLOPT_URL => API_URL,
    CURLOPT_POST => true,
    CURLOPT_POSTFIELDS => $data,
    CURLOPT_RETURNTRANSFER => true,
    CURLOPT_HTTPHEADER => [
      'Authorization: Bearer ' . API_KEY
    ]
  ]);

  $response = curl_exec($ch);
  $httpCode = curl_getinfo($ch, CURLINFO_HTTP_CODE);
  
  curl_close($ch);

  if ($httpCode === 200) {
    return json_decode($response, true);
  } else {
    throw new Exception("API Error: $response");
  }
}

// Usage
try {
  $result = processOCR('document.pdf');
  echo "Extracted Data:\n";
  print_r($result);
} catch (Exception $e) {
  echo "Error: " . $e->getMessage();
}

?>
import requests
import json

API_KEY = 'your_api_key_here'
API_URL = 'https://api.valitract.com/api/v1/extract-generic'

def process_ocr(file_path):
  """
  Process OCR on a document using Valitract API
  
  Args:
    file_path (str): Path to the document file
    
  Returns:
    dict: Extracted data from the document
  """
  headers = {
    'Authorization': f'Bearer {API_KEY}'
  }
  
  with open(file_path, 'rb') as file:
    files = {
      'file': (file_path, file, 'application/pdf')
    }
    
    try:
      response = requests.post(API_URL, headers=headers, files=files)
      response.raise_for_status()
      
      result = response.json()
      return result
      
    except requests.exceptions.RequestException as e:
      print(f'Error processing OCR: {e}')
      raise

# Usage
if __name__ == '__main__':
  try:
    data = process_ocr('document.pdf')
    print('Extracted Data:')
    print(json.dumps(data, indent=2))
  except Exception as e:
    print(f'Failed to process document: {e}')
require 'net/http'
require 'uri'
require 'json'

API_KEY = 'your_api_key_here'
API_URL = 'https://api.valitract.com/api/v1/extract-generic'

def process_ocr(file_path)
  uri = URI.parse(API_URL)
  
  File.open(file_path, 'rb') do |file|
    request = Net::HTTP::Post.new(uri)
    request['Authorization'] = "Bearer #{API_KEY}"
    
    boundary = "-----------RubyMultipartBoundary"
    request['Content-Type'] = "multipart/form-data; boundary=#{boundary}"
    
    post_body = []
    post_body << "--#{boundary}\r\n"
    post_body << "Content-Disposition: form-data; name=\"file\"; filename=\"#{File.basename(file_path)}\"\r\n"
    post_body << "Content-Type: application/pdf\r\n\r\n"
    post_body << file.read
    post_body << "\r\n--#{boundary}--\r\n"
    
    request.body = post_body.join
    
    response = Net::HTTP.start(uri.hostname, uri.port, use_ssl: true) do |http|
      http.request(request)
    end
    
    if response.code == '200'
      JSON.parse(response.body)
    else
      raise "API Error: #{response.body}"
    end
  end
end

# Usage
begin
  result = process_ocr('document.pdf')
  puts "Extracted Data:"
  puts JSON.pretty_generate(result)
rescue StandardError => e
  puts "Error: #{e.message}"
end
using System;
using System.IO;
using System.Net.Http;
using System.Net.Http.Headers;
using System.Threading.Tasks;
using Newtonsoft.Json;

namespace ValitractOCR
{
  public class OCRClient
  {
    private const string API_KEY = "your_api_key_here";
    private const string API_URL = "https://api.valitract.com/api/v1/extract-generic";

    public static async Task<string> ProcessOCR(string filePath)
    {
      using (var client = new HttpClient())
      {
        client.DefaultRequestHeaders.Authorization = 
          new AuthenticationHeaderValue("Bearer", API_KEY);

        using (var form = new MultipartFormDataContent())
        {
          var fileContent = new ByteArrayContent(
            File.ReadAllBytes(filePath)
          );
          fileContent.Headers.ContentType = 
            MediaTypeHeaderValue.Parse("application/pdf");
          
          form.Add(fileContent, "file", Path.GetFileName(filePath));

          var response = await client.PostAsync(API_URL, form);
          response.EnsureSuccessStatusCode();

          var result = await response.Content.ReadAsStringAsync();
          return result;
        }
      }
    }

    public static async Task Main(string[] args)
    {
      try
      {
        var result = await ProcessOCR("document.pdf");
        Console.WriteLine("Extracted Data:");
        
        var formatted = JsonConvert.DeserializeObject(result);
        Console.WriteLine(
          JsonConvert.SerializeObject(formatted, Formatting.Indented)
        );
      }
      catch (Exception ex)
      {
        Console.WriteLine($"Error: {ex.Message}");
      }
    }
  }
}

Try Bank Statement Converter
for Free

Start for free with complimentary credits and dedicated developer support to help you get set up quickly.

    FAQs

    Frequently asked question

    Find quick solutions to common queries and get the most out of your learning experience

    A bank statement converter is software that reads a bank statement PDF and extracts its data — transactions, dates, amounts, balances, and account details — into a structured format like Excel, CSV, or JSON. Valitract layers AI on top of traditional OCR to understand any statement layout, regardless of bank, country, or document quality, without needing predefined templates — and at a fraction of what most tools charge.

    Most converters on the market rely on templates (meaning you need to configure a new template for each bank layout), charge by the page rather than by the document, and deliver results through dated interfaces that create extra work. Valitract is template-free, priced at $0.05–$0.10 per full document, achieves 98% field accuracy, and outputs a clean, ready-to-use spreadsheet — or JSON — in one click. Whether you need to pull three months of transactions into Excel for a tax review or automate statement processing at scale via API, the workflow is the same: upload, extract, export.

    Valitract achieves 98% data extraction accuracy across all supported formats and layouts. The AI is trained on millions of bank statement variations and includes a validation layer that automatically flags any low-confidence fields so your team can review them before they hit your system.

    Yes. Valitract returns clean JSON output, making it immediately compatible with any system that accepts JSON — including QuickBooks, SAP, NetSuite, Xero, Sage, and Microsoft Dynamics. Pre-built connectors are available for the most popular platforms.

    Valitract handles statement formats from banks across 50+ countries, covering all major layouts — single-column, multi-column, itemized, and summary statements. Retail banks, digital neobanks, and corporate treasury statements are all supported without configuration.

    Input: PDF, JPG, JPEG, PNG, TIFF, WEBP, GIF, and BMP. Output: Excel (.xlsx), CSV, or JSON — your choice. The Excel output is cleanly formatted with proper column headers, ready to open in Excel, Google Sheets, or any spreadsheet tool immediately. Turning a bank statement PDF into a workable spreadsheet takes seconds, not an afternoon. The JSON output is schema-consistent and integrates directly with any downstream system.

    A free tier includes 50 documents per month at no cost. Paid plans start at $0.05–$0.10 per document, compared to $3–$10 per statement for manual data entry. Enterprise volume pricing is negotiated directly based on monthly throughput.