Improving Fintech Operations with a Document Conversion and Data Extraction Tool
Project Summary
This is a Python-based tool developed on Google Colab to streamline document processing for a fintech company. It converts image files (JPEG, PNG) into searchable PDFs and extracts structured data, such as text and tables, for loan processing and compliance tasks. The solution offers fast, accurate automation, integrating seamlessly with existing systems while eliminating the need for expensive software.
The Challenge
A fintech company faced issues with processing client documents. They received many image files, such as scans of bank statements, tax forms, and contracts. These documents needed to be turned into PDFs and have data—like text and tables—pulled out for use in loan processing and compliance tasks. Doing this by hand took a lot of time, led to mistakes, and slowed down their work. The team needed a faster, more accurate way to handle these files without relying on expensive software.
Technology Stack
Python 3.8, Google Colab
Outcome and Business Impact for the Client
Using the tool saved time. Tasks that once took hours were finished much faster, helping the company process loans more quickly. Mistakes from manual work dropped, which improved accuracy for compliance needs. The team could focus on other tasks instead of spending time entering data. The tool ran on Google Colab, so there was no need for costly equipment or software. This kept expenses low while still meeting the company’s needs.
The Solution
A tool was built to solve this problem. It was designed using Google Colab and Python 3.8. The tool converts image files, like JPEGs or PNGs, into PDF documents. It can combine multiple images into one PDF if needed and keeps the quality clear. It also pulls out structured data, such as text and tables, from the PDFs. This data can then be used in other systems, like those for managing loans or meeting regulations.
The Implementation
The team tested the tool with a set of 100 client documents. They uploaded the image files and chose options to either merge them into one PDF or keep them separate. The tool quickly turned the images into searchable PDFs and extracted data, like numbers and text, into organized files. What used to take hours was now done in minutes. It worked well with different types of files, including clear scans and less sharp images. The PDFs were easy to search, and the data fit directly into the company’s existing systems.
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