Bank Statement OCR to JSON

@TanvirKhanPaple

Hi there! Project is very clear to me and I can OCR and accurately parse scanned bank statements into clean, structured JSON containing only the required account-holder information. I can verify every field against the original PDFs, avoid transactions/balances, preserve exact spelling and formatting, and provide a reproducible OCR workflow summary. Just message me I am ready to start now and i will show you few data sample before start. Thank you.

@sohandas

I can OCR scanned bank statements and extract only account-holder fields into accurate JSON. Ready to provide a quick sample.

@Tanmoy236

Hi There! I specialize in OCR and structured data extraction with 9+ years of experience, and I can turn your scanned bank statements into accurate, field-only JSON while preserving the original wording exactly. I’ll use the most suitable OCR engine, validate extracted names, addresses and identifiers against the source PDFs, exclude transaction data, and provide reproducible processing notes. I can also maintain your folder structure and deliver one JSON per statement. Approximately how many statements are in the batch so I can confirm a realistic statements-per-hour rate?

@ZohaibRoy

⭐⭐⭐⭐⭐ Extract Account Holder Data from Scanned Bank Statements with OCR ❇️ Hi My Friend, I hope you are doing well. I reviewed your project requirements and see you are looking for a solution to process scanned bank statements. You have no need to look any further; Zohaib is here to help you! My team has successfully completed 50+ similar projects. I will use efficient OCR tools like Tesseract or AWS Textract to ensure accurate extraction of account-holder information into structured JSON files. ➡️ Why Me? I can easily handle your project as I have 5 years of experience in data extraction and OCR processing. My expertise includes JSON formatting, document verification, and OCR optimization. Not only this, I have a strong grip on tools and techniques to ensure high accuracy and consistency in data extraction. ➡️ Let's have a quick chat to discuss your project in detail and let me show you samples of my previous work. I look forward to discussing this with you in our chat. ➡️ Skills & Experience: ✅ OCR Processing ✅ Data Extraction ✅ JSON Formatting ✅ Document Verification ✅ Tesseract ✅ ABBYY FineReader ✅ AWS Textract ✅ Workflow Optimization ✅ Data Validation ✅ Error Checking ✅ Confidential Data Handling ✅ File Management Waiting for your response! Best Regards, Zohaib

@MashoodurRehman1

I am a seasoned software developer with extensive experience in Optical Character Recognition (OCR) and data parsing. I have successfully executed similar projects using technologies like Tesseract, ABBYY FineReader, and AWS Textract, ensuring high accuracy and consistency in capturing data from complex documents. My expertise includes processing scanned bank statements to extract key personal identifiers into clean JSON formats while maintaining high precision. Understanding your requirement for zero tolerance towards spelling mistakes or truncation, I employ a robust workflow combining advanced OCR engines and custom post-processing scripts tailored to your needs for superior character recognition and data accuracy. I can process approximately 10-12 statements per hour, providing you with detailed documentation of the workflow, including tool versions and key settings used. I am committed to handling all data with strict confidentiality under your NDA requirements. I am keen to discuss this project further to tailor my approach to best meet your needs. Let me know if you require more information or have any questions regarding the process.

@Hubready

Hello!, This is James from Hollywood... Your main pain point here is not just OCR, it is turning messy scanned bank statements into clean, structured JSON without missing transactions, headers, or totals. That is exactly the kind of data problem I like solving. My approach: 1. Review the statement formats and variations 2. Build an OCR flow using AWS Textract or ABBYY FineReader, based on scan quality 3. Parse and normalize fields into JSON 4. Validate against sample outputs so the data is consistent and usable I focus on accuracy first, then structure, then scale. If needed, I can also add a QA pass for low-confidence rows so you are not stuck with noisy output. I have worked on data extraction and automation pipelines for financial and operational systems, so I understand how important clean downstream data is. Relevant work examples: - invoice and receipt parsing pipeline for a bookkeeping tool - PDF to JSON extraction for a document archive system - OCR cleanup workflow for a compliance dashboard - structured data pipeline for a finance reporting app A couple of questions before I start: 1. Are the statements all from the same bank/template, or multiple formats? 2. Do you want every transaction field mapped to a fixed JSON schema? 3. Should I optimize for speed, or highest accuracy with manual review on low-confidence cases? If you want, send me 2 or 3 sample statements and I can tell you the best extraction path right away.

@leopedia

I can extract all the account-holder details from your scanned bank statements and give you clean JSON files. Here's what I'll do for you: • Accurate JSON files, one per statement, named to match the originals • Each JSON will have only the account holder’s name, address, account number, and other personal identifiers • A clear summary of the OCR tools, settings, and any post-processing scripts I use • All files delivered to your shared drive, keeping your folder structure intact I can process around 10-15 statements per hour, and can start immediately to wrap this up quickly. You only pay once you've reviewed the output and are completely satisfied. Let's get this done for you.

@muneeb6767

I can build a reliable OCR → parsing pipeline using Python with Tesseract/ABBYY/Textract as appropriate, preprocessing noisy scans and validating extracted account-holder fields against the source to avoid truncation or spelling errors. I’ll output one clean JSON per statement with only the requested identifiers, preserve filenames/folders, and provide the exact OCR settings and post-processing workflow; processing speed can be confirmed after a small sample.

@ImranAli01

Hi there, I went through your project description and understand you need scanned bank statements processed through OCR and converted into clean, structured JSON containing only account-holder information, with exact field accuracy and no transaction or balance data. I will process each statement using Python with an appropriate OCR engine such as Tesseract, ABBYY, or AWS Textract based on document quality. I will extract names, addresses, account numbers, and clearly labeled identifiers, then apply structured parsing and validation to prevent truncation, spelling errors, field leakage, or missing values. I will also build a post-processing workflow to validate the extracted fields against the OCR output, preserve the original filenames and folder structure, and generate one JSON file per statement. Alongside the files, I will provide a concise processing summary covering tools, versions, settings, and scripts used for reproducibility. How many statements are included in the initial batch, and are they primarily PDF scans or mixed image formats? I will share a project blueprint within 24–48 hours of award and begin immediately. Let’s get the extraction pipeline accurate, consistent, and reproducible. Kind Regards, Imran Ali

@codefusion53

Hi I can process your scanned bank statements into clean, structured JSON containing only the account-holder information you specify. I have experience with OCR pipelines, document parsing, JSON extraction, validation, and post-processing using tools such as Tesseract, AWS Textract, and Python. I would first benchmark OCR quality on a sample set, then use field-aware extraction and validation rules to capture names, addresses, account numbers, and other clearly labeled identifiers while excluding transactions, balances, and unrelated data. For accuracy, I would include normalization checks, confidence review, and document-by-document verification so the JSON matches the source exactly rather than relying on raw OCR output alone. I can preserve filenames and folder structure and provide a reproducible workflow summary with tools, versions, settings, and scripts used. Throughput will depend on scan quality, but I can give a reliable statements-per-hour estimate after reviewing a small sample. Best, Justin

@mayr81

I’ll build a reliable pipeline to convert each scanned bank statement into a single structured JSON file containing only the account-holder fields exactly as they appear (name, address, account number, and any other clearly labeled personal identifiers). The workflow will combine OCR engines where they perform best for your scans (e.g., Tesseract/ABBYY/AWS Textract), followed by deterministic extraction rules that prevent inclusion of transactions, balances, or unrelated sections. I will implement strict field validation against the original PDFs and add post-processing to normalize spacing/newlines while preserving spelling, capitalization, and formatting so every captured character matches. Deliverables: one JSON per statement named to match the original document, with the folder structure preserved for shared-drive delivery. I’ll also provide a brief, reproducible workflow summary including tool versions, key OCR settings, and any post-processing scripts used so you can rerun the process consistently on your side.

@denisSolution

Hi, I’m Denis, a developer who’s worked with document processing workflows that involve extracting cleanly structured data from scanned files. I understand you need bank statements converted from scanned images to JSON with precise extraction of personal identifiers like name, address, and account number, while excluding transactions and balances. The deliverables include one JSON file per statement named to match the original, along with a brief workflow summary for reproducibility—accuracy and consistency are essential here. For this project, I’d start by evaluating the OCR engine that delivers the highest character recognition rate, likely AWS Textract or ABBYY FineReader depending on the document quality. After processing the batch, I’d validate each JSON output against the original statements to ensure every field matches exactly, then package the results with the workflow summary. Confidentiality will be handled through secure file handling as specified. I can start working right away. Let's connect and discuss the details. Thanks, Denis.

@XRProConnect

Hi, Aashiq here from Cape Town, South Africa. This project instantly caught my eye, so I had to reach out. I see you are looking for accurate OCR processing of bank statements into clean, structured JSON files. Ensuring that every detail, from account-holder information to identifiers, is captured exactly as it appears is crucial for your needs. I have extensive experience in data extraction and transformation using tools like Tesseract and AWS Textract. I have successfully helped clients streamline their data processing while maintaining high accuracy and consistency. I'm confident I can deliver the results you want and can provide samples of similar projects upon request. Based on what you mentioned, here is how we would approach the project: - Use the best OCR engine based on the document's characteristics. - Implement a strict validation process to ensure data accuracy. - Provide a detailed summary of the workflow for reproducibility. You can count on clear communication throughout the project. I will deliver a seamless, user-focused solution that meets your accuracy requirements. Best Regards, Aashiq

@ASSAMWEB

Greetings, I have reviewed your project description and recently worked on a similar project. I believe I can help you deliver this successfully. Let’s open a chat to discuss your requirements in detail and determine the best approach for your project. Regards

@asifkhan268

Hi, I can process your scanned bank statements using OCR and deliver clean, structured JSON containing only the account-holder information you specified. I’ll use the OCR engine best suited to the document quality, followed by validation and post-processing to ensure names, addresses, account numbers, and other clearly labeled identifiers are captured exactly as shown. I understand the confidentiality requirements and will handle the data accordingly. Processing capacity: approximately 10–15 statements per hour, depending on scan quality and document complexity. I’m ready to start as soon as the files and shared-drive access are provided. Regards Karim

@TeraByte26

Hi Benke, I will OCR each scanned bank statement and create a matching‑named JSON file containing only the holder’s name, address and account number. I can process eight statements per hour and finish the batch within two days for $500. I’ll send a sample JSON now. Best, Alex Waiting for your response in chat! Best Regards.

@MSaadJaved

I’ll OCR the scanned bank statements and extract only the account holder fields into clean, structured JSON, with one file per statement named to match the source document. I’ll use the OCR engine that gives the best accuracy for mixed fonts and background noise, then validate the output against each PDF to preserve exact spelling and field values. I’ll also deliver a brief workflow summary with the tool versions, key settings, and any post processing steps so the process is reproducible. I can work through your shared drive folder structure exactly as provided. How many statements are in the batch? Best, NexLoom Labs

@sf264

Hello, Fahad here from Pakistan. I would love to help you in running and parsing the batch of scanned bank statements through OCR so that you receive clean, structured JSON containing only the account holder information. I am confident in my ability to deliver high quality results. Let's connect here via chatbox to discuss our potential collaboration. Looking forward to the opportunity to work together.

@nikhilgarg96

Hello Greetings, After reviewing your project description, I feel confident and excited to work on this project for you. But I have some crucial things and queries to clear up. Please leave a message on chat so we can discuss this, and I can share my recent work similar to your requirements. Thanks for your time! I look forward to hearing from you soon. Best Regards.