Parsing PDF bank statements

Budget: 9999 UAH Deadline: 6 days

Hello, Konstantin! Your task requires a systematic approach to processing unstructured data. I have experience working with PDF analytics and developing scalable Python projects.

My implementation plan according to your requirements:

Architecture: I will build a modular structure (OOP), where each type of statement is a separate plugin-module. This will allow for easy addition of new banks without changing the core of the system.

Hybrid parsing: I will use pdfplumber for instant text extraction and EasyOCR/Tesseract for graphical elements (stamps, handwritten dates). This will ensure a speed of 1-3 seconds per file.

Normalization: I will create a universal data schema (Transaction Model). In the output, you will receive clean JSON or DataFrame with validated fields (date, amount, purpose, balance).

Training: I will train the logic on your 3 types of statements, ensuring resilience to layout shifts and specific bank encodings.

No cost: I will use exclusively open-source solutions without reliance on paid cloud APIs.

I am ready to discuss the structure of the output template and start developing the prototype.

Best regards,
Victor Expand

Budget: 3000 UAH Deadline: 1 day

Good day
I have done similar projects for my main job under OTP Bank and PrivatBank. I only parsed tabular data from statements. I need to review your files and discuss the terms of reference in more detail.

I am ready for ongoing collaboration.

Budget: 700 UAH Deadline: 1 day

Good day, I cannot say anything about myself. I wish you happiness and health.

Budget: 7000 UAH Deadline: 4 days

Good day.
I am ready to take your project into work.
I can develop such automation for parsing bank statements for you.
Write to me privately, we will discuss all the details with you and choose the best solution for you.

Budget: 10000 UAH Deadline: 1 day

Hello! I can implement it. Write to me privately to discuss all the details. I will be glad to cooperate!

Budget: 5000 UAH Deadline: 7 days

Good day, Kostiantyn!

I have production experience specifically with this task — I developed an OCR microservice for processing 5 types of mixed PDF documents (text + scan). FastAPI + pdfplumber + PaddleOCR, accuracy 100%, output structured JSON.

Architecture:
— pdfplumber for text layers + PaddleOCR for non-text (free)
— auto-detection of bank and type by header/table structure
— plugin architecture: new bank = new module without changing the core
— normalization to an agreed template (date, amount, purpose, balance)

One question: which 3 banks/types of statements are we starting with? The choice of parsing strategy depends on the formats. Expand

Budget: 27000 UAH Deadline: 7 days

Good day!

I have direct experience with a similar task — I developed a production-ready pipeline for processing PDF documents (inspection reports, invoices, scanned forms) with multimodal data extraction.

What I have already solved that is relevant to your project:

Automatic document type identification — in my project, the pipeline distinguished between inspection mode vs service mode based on keywords in the first 500 characters + the number of pages. For bank statements, the approach is similar: identifying the bank by header/logo + type of statement by the structure of tables.

Multimodal extraction — pdfplumber for clean text PDFs, PaddleOCR for scanned parts, with automatic path determination (if text → pdfplumber, if not → OCR). Additionally, I implemented CID-encoded text detection — when the PDF appears text-based, but the characters are unreadable due to embedded fonts. This is a common issue in bank statements.

Normalization to a single template — extraction into structured categories with validation, deduplication, and normalization of names. I will adapt it to your universal transaction template.

Extensible architecture — the system is built modularly: adding a new document type = new config + parsing rules, without changing the core pipeline.

Regarding speed 1-3 seconds: for text PDFs with pdfplumber — realistic even for 30+ pages. For mixed (text + OCR) — it depends on the number of pages that require OCR. I am ready to discuss optimization: batch processing only non-text pages, caching bank templates, preliminary classification without full parsing.

Stack: Python, FastAPI, pdfplumber, PaddleOCR/Tesseract, PostgreSQL, Docker.

I can show the architecture of a similar project (without client details, NDA) and discuss the structure of the modules on the first call.

Estimated cost: $800-1200 depending on the complexity of the templates and the number of edge cases.

Timeline: 1-2 weeks for MVP (3 types of statements). Expand

Budget: 4000 UAH Deadline: 1 day

Good day. I am ready to complete this project as I have extensive experience in application development.

Budget: 4300 UAH Deadline: 1 day

Hello! I will do it in 1 day — I have experience specifically with parsing PDF statements.

Plan:
• Modular structure with plugin architecture — a new bank is added with one module without core modifications
• pdfplumber for text + Tesseract OCR for images — everything is free
• Automatic bank and statement type detection
• Parsing + normalization to a universal JSON template
• API endpoint on FastAPI
• I will train on 3 types of statements, speed 1–3 seconds per file

Send examples of statements and the desired template — I will start immediately. Expand

Budget: 10000 UAH Deadline: 6 days

Hello! I have experience in creating Telegram bots. I offer a loyal price and quality work. Write to me)

Budget: 6000 UAH Deadline: 3 days

Hello, I created something on an open-source PDF parser for myself and my banks. I can't say how fast it is since I didn't pay attention to that at the time, but for the templates, you will need to create a database for each specific type of banking document, and it would also be good to add a mechanism for checking its relevance and some process for updating it, as any parsers work until the first change in the document structure from the bank's side.

If you have questions, write to me privately, and we will arrange it.

P.S. I created a module for Firefly III to automatically retrieve data from banks that do not support API integration, so writing an interface according to your requirements will not be a problem.

Budget: 6666 UAH Deadline: 6 days

Hello. I processed PDF with OCR, I understand how to quickly extract data even from mixed statements. I use PyMuPDF/pdfplumber for text, Tesseract for OCR, I will assemble everything into a normal modular structure with the ability to add new banks.

Could you please let me know if you have examples of statements (PDF) for testing?

Budget: 3000 UAH Deadline: 4 days

Hello! I am ready to take on your project.

My main specialization is data parsing. I have experience in the banking sector: my previous successfully completed project was related to the development of an application for parsing push notifications from banks (you can view the client's feedback in my profile).

The technical requirements are quite clear, I will be able to implement them.

Since I am currently building my rating, I am willing to do the work at a price lower than the market rate, without compromising quality.

Write to me, and we will discuss the details.

Budget: 2000 UAH Deadline: 3 days

Hello! I have reviewed your project and am ready to start working. I guarantee high quality and prompt execution.

Budget: 700 UAH Deadline: 1 day

Good evening, Konstantin!
In general, the task is clear, but for an accurate response regarding the deadlines and price, I would like to clarify some questions that arose after analyzing your task.
Please write in private messages – we will discuss the details and your wishes.

Budget: 10000 UAH Deadline: 10 days

hello
here we need ocr, there are various local and paid options, and then extract data from this text
there is a problem here, because without ai it will be difficult or impossible
so it is unlikely to work with free options, write, we will discuss

Budget: 15000 UAH Deadline: 6 days

Good day.

The task is clear: not just a "PDF parser," but a well-structured Python project that can identify the bank and type of statement, extract text data, connect OCR for non-text parts, parse transactions, and bring everything to a single universal format with the ability to scale to other banks.

I can implement this in the following approach:
— design the module structure for extensibility;
— create bank/type of statement identification;
— separately process the text layer and OCR layers;
— compile normalization into a consistent template;
— prepare a solution for batch processing;
— lay the groundwork so that new banks can be added later without rewriting the entire project.

I like that you immediately have the right focus on architecture, speed, and adaptability. I would also do this as a modular pipeline: classify → extract → OCR fallback → parse → normalize → validate. This provides a more stable result than "one big script."

If we agree on the normalization template at the start and the scope is within the described limits, I am ready to quickly engage in the implementation. Expand

Budget: 2000 UAH Deadline: 1 day

Hello! I can develop a project for parsing such statements in Python!!!! Contact me, I guarantee quality!!!

Budget: 10000 UAH Deadline: 5 days

Good day, I am ready to complete your task quickly and efficiently. I have extensive experience in creating various parsers. Please write to me in private messages to discuss the details. I will be happy to help)

Budget: 1000 UAH Deadline: 1 day

Hello, I am a Python developer, I have experience in developing parsers of various complexity. I can complete your project quickly and efficiently. Write to me - we will discuss the details. I am ready to start working today.

Budget: 6000 UAH Deadline: 3 days

Hello
I have experience working with processing PDF documents, recognition, parsing, and recording information in databases, setting up API projects.
I would be happy to collaborate.
Please provide an example of the extracts so that I can familiarize myself with the structure of the input data.

Budget: 10000 UAH Deadline: 1 day

✋ Hello! We are the IT company dZENcode.

We can develop a Python solution for you to recognize and parse bank statements.

What three types of statements should we take to start?
Are there examples of files for template approval?

We work in iterations, rates starting from 750 UAH/hour.
You can find detailed information about our services and rates on our website: Freelancehunt
Take a look – we will discuss the details of the work further, write when you are ready.

The final cost is determined only after clarifying the volume and requirements.

___________________
Best regards,
Manager of dZENcode

Our strengths:
💎 10+ years providing IT services: Outsourcing, Outstaffing
🔥 90+ in-house specialists
🚀 Projects "from scratch" and for support
⚙️ SLA and post-production support
✅ Contract with the company, guaranteed results!
🔥 250+ public reviews since 2015. Expand

Budget: 1500 UAH Deadline: 4 days

Good day, I am ready to implement your project, I have extensive experience with Python projects. Write to me privately, we will discuss the details.

Budget: 3000 UAH Deadline: 3 days

Good day, I made a similar tool for a law firm - I parsed the UBCI statement. I can help, write to me privately.

Budget: 3000 UAH Deadline: 1 day

Good day
I am ready to complete your work
Write to me, I will be happy to help with your task