• Projects 12
  • Rating 5.0
  • Rating 4 869

Budget: 19000 UAH Deadline: 10 days

Hello.
I have reviewed the task. Here I see not just PDF parsing, but an MVP of a system for structural analysis of statements: determining the bank by fingerprint characteristics of the document, detecting anomalies, signs of editing or incompleteness, with a subsequent transition to parsing and categorizing transactions.

I can implement the first stage in Python as a working pipeline:

classification of PDF type

extraction of structural features of the document

determining the bank by layout / blocks / fonts / table geometry

  • Projects 118
  • Rating 5.0
  • Rating 10 376

Budget: 4500 UAH Deadline: 3 days

Hello.

I am a NodeJS developer. I can create a Telegram bot for you with this functionality. I am ready to take it on. Write to me, we will discuss.

  • Projects 41
  • Rating 4.9
  • Rating 19 784

Budget: 16000 UAH Deadline: 10 days

Hello! The task is extremely relevant, especially in the fintech and security niche. I understand the headache: classic OCR often struggles with non-standard fonts or "hand-drawn" statements created from scratch. Your request for an analysis of the structure (layout) is the only correct way to detect forgeries.
I have experience working with Python tools for document processing and automation (n8n/Make, complex parsers). To solve your task, I will use a combination of computer vision and structural analysis.
My approach to implementing Stage 1:
* Layout Analysis: Instead of reading text, the system will analyze the "skeleton" of the document (grid tables, margins, logo placements, specific graphic markers for each bank) using libraries like LayoutParser or PyMuPDF.
* Forgery Detection: I will compare the topology of the provided file with reference matrices of banks. If the structure matches by 99%, but the font or metadata is "floating" — the system marks this as suspicious.
* Hybrid Processor: For text PDFs — quick parsing of metadata; for scans — light OCR (Tesseract or lightweight models) only for checkpoints, to fit within 2 seconds and a budget of $0.005.
* Validation: Creating an algorithm to check transaction checksums (if the final balance does not match the math of the operations — the statement is truncated or altered).
Deadlines and costs (Stage 1):
* Development of the core and testing on your examples (95%+ accuracy): 7–10 days.
* Cost: 12,000 – 16,000 UAH (depending on the number of types of banks that need to be included in the database at the start).

  • Projects 8
  • Rating 5.0
  • Rating 1 911

Budget: 14000 UAH Deadline: 7 days

Hello!

The Dev Company team is interested in developing a Python tool for detecting fake bank statements and parsing/categorizing transactions.

As we see Stage 1
- Determining the bank and the authenticity of the statement through document structure analysis, not just text (positions of blocks, tables, columns, fonts, typical templates for each bank).
- Support for both text PDFs and scans/images and non-standard fonts (combination of PyMuPDF / pdfplumber + layout analysis, with OCR if needed).
- Building a separate classifier for:
- identifying the bank by structure;
- detecting "bad" statements (forged from scratch / cropped / incomplete).

  • Projects -
  • Rating -
  • Rating 496

Budget: 10000 UAH Deadline: 1 day

✋ Hello! We are the IT company dZENcode.

We are implementing a Python service for detecting counterfeit bank statements based on the PDF structure (including scans), with ML anomaly detection and a module for parsing/categorizing transactions, relying on the team's experience, best practices, and our own developments.

We understand that you will provide examples of normal and suspicious statements. How many banks and templates need to be supported at the start?

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 scope and requirements.

Сервис аренды автомобилей
  • Projects 8
  • Rating 5.0
  • Rating 2 187

Budget: 1234 UAH Deadline: 1 day

I am ready to develop a tool for determining the authenticity of bank statements and their analysis.

I have experience working with PDF parsing (including scans/non-standard fonts), OCR, as well as building systems for analyzing document structures. I propose to solve the task through a combination of: structural analysis (layout, blocks, tables), format features (positions, intervals, patterns), and ML/heuristics for determining the bank and identifying anomalies/frauds.

I will provide:
— support for text PDF + image PDF
— accuracy of 95%+ (with a training dataset)
— speed of up to 1–2 seconds/document
— cost optimization

  • Projects 12
  • Rating 5.0
  • Rating 1 175

Budget: 15000 UAH Deadline: 10 days

Hello! My partner (designer + full-stack) and I have been specializing for over 4 years in the development of automation systems, computer vision, and data analysis algorithms, so we are implementing a bank statement verification tool for you with an accuracy of over 95%, using methods of geometric structure and document topology analysis. We will develop an architecture based on Python (OpenCV + LayoutML), which will identify the bank not by text, but by the "digital fingerprint" of the table grid, margins, and the arrangement of graphic elements, allowing for the instant detection of forgeries created from scratch or manipulations with file integrity. Our experience in development is 4 years; take a look at our work from the perspective of document processing logic and speed: hyperfi.tech, espressolab.com.ua, hudi.com.ua.

  • Projects -
  • Rating -
  • Rating 160

Budget: 9999 UAH Deadline: 5 days

Good day! My colleague and I have been professionally engaged in technical automation and the development of intelligent image recognition systems for over 4 years, so we will help you create a reliable filter for bank documents that recognizes counterfeits based on anomalies in structure and formatting. We will implement a comparison algorithm of the "skeleton" of the statement with reference templates from specific banks, which will eliminate the possibility of bypassing the system through simple text changes or the use of non-standard fonts. Our 4 years of experience is confirmed by projects drkukharevich.rivne.ua, crave-agency.com.ua, jk-solution.com.ua, where we have already worked with data verification and complex parsers. We optimize the processing pipeline to achieve a target cost of $0.005 per operation, implement a validation system for document completeness, and prepare the groundwork for the second stage — intelligent categorization of expenses. We work quickly and with a focus on the technical stability of the solution.

  • Projects 7
  • Rating 5.0
  • Rating 1 562

Budget: 1000 UAH Deadline: 1 day

I am among the top 10 developers in the category of "Artificial Intelligence and Machine Learning" among ~2100 specialists on the platform.
I guarantee:
- Fast and high-quality task execution
- Strict adherence to deadlines
- Regular communication throughout the entire process
I would be happy to discuss the details of your project in private messages.

  • Projects -
  • Rating -
  • Rating 296

Budget: 20000 UAH Deadline: 7 days

Hello, Konstantin!

This is exactly our specialization. We currently have an active project for a large enterprise client — a document analysis system: 15 types of files, text PDFs + scans + photos from a phone, 95% accuracy, processing.

  • Projects 14
  • Rating 5.0
  • Rating 1 506

Budget: 1000 UAH Deadline: 1 day

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

  • Projects -
  • Rating -
  • Rating 556

Budget: 1111 UAH Deadline: 30 days

Good day.

I can create a tool for determining the authenticity/falsification of a PDF file and parsing/categorizing data using the Python programming language. This tool will be capable of analyzing the structure of a statement to identify the bank and determine authenticity, as well as processing both text PDFs and PDFs with images/non-standard fonts. For this project, I plan to use libraries such as PyPDF2, pdfminer, and others for processing PDF files, as well as machine learning libraries for analyzing the structure of the statement.

What I will do:
— Create a tool to identify the bank to which the statement belongs
— Develop an algorithm for determining authenticity (falsification) of the statement by analyzing the document structure
— Implement processing for both text PDFs and PDFs with images/non-standard fonts
— Conduct speed analysis of the tool to ensure task execution within 2 seconds
— Evaluate the results of the tool to ensure accuracy of at least 95%

  • Projects 29
  • Rating 5.0
  • Rating 5 235

Budget: 10000 UAH Deadline: 1 day

Hello. I am ready to help. Let's discuss in more detail.

I have created scripts for automating payments and working with payment systems, as well as implemented scripts for working with APIs of various banks and payment systems. I also have experience with neural networks for text recognition and have created self-learning neural networks on large data sets. I have ideas on how to accomplish your task!

  • Projects 571
  • Rating 4.4
  • Rating 14 253

Budget: 10000 UAH Deadline: 10 days

Hello, Konstantin! We have experience in developing our own AI systems with a 10-level agent architecture for document analysis. One of our team members works in R&D at Samsung in the area of training LLM, so we understand data processing architecture at the highest level.

Our previous technical approach:
Fraud Detection: Analysis of the integrity of PDF layers and embedded fonts (glyphs). This allows us to detect interference from third-party software or text overlay.
Layout Fingerprinting: Identification of the bank by the "skeleton" of the document (grid coordinates, margins, logos), which eliminates errors in reading the text.
Cross-Validation: Automatic verification of the mathematical balance of transactions to detect cropped or incomplete files.
Speed and cost: Using PyMuPDF and lightweight CV models will ensure processing in up to 1 second with a cost of up to $0.005/file.

We are ready to test your "bad" examples and confirm 95%+ accuracy in practice.

  • Projects 9
  • Rating 5.0
  • Rating 644

Budget: 700 UAH Deadline: 1 day

Good day, 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.

  • Projects 23
  • Rating -
  • Rating 2 114

Budget: 9999 UAH Deadline: 10 days

Hello
Please send examples to assess if it is possible to determine.

  • Projects 6
  • Rating -
  • Rating 410

Budget: 4500 UAH Deadline: 1 day

Hello!

I am a Full-Stack Software Engineer with over 7 years of experience in developing websites, SaaS solutions, complex web platforms, and MVPs for startups - from idea and architecture to production and support.

I work not only as a developer but also with a focus on business logic, scalability, and long-term support of solutions. My portfolio includes examples of implemented projects of varying complexity.

Technology stack:
PHP (Laravel, Symfony, Yii2),
Frontend: JavaScript (Vue.js, React.js), HTML5, CSS3,
Databases: MySQL, PostgreSQL.

  • Projects 3
  • Rating 5.0
  • Rating 2 110

Budget: 17000 UAH Deadline: 12 days

Hello, Konstantin!

I have experience working with PDF parsing (pdfplumber, PyMuPDF, OCR through Tesseract/EasyOCR) and analyzing document structures. I have worked with bank statements from various banks — I understand that each has its own structure, fonts, and layout.

For Stage 1, I see an approach through fingerprinting the PDF structure (metadata, fonts, layout, margins) without reading the text with the bank's name — this will allow identifying the bank and detecting fakes/cropped files. For PDF images — OCR + analysis of visual structure.

Regarding speed and cost — 2 seconds and $0.005 is realistic if the main logic is based on rule-based analysis with minimal use of LLM (or without it for Stage 1).

I am ready to discuss the details and show the approach using examples from your statements.

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