End-to-End Financial Report Automation & OCR Pipeline_
An autonomous system monitoring stock exchange portals, downloading financial filings, and extracting structured data via OCR — reducing data availability lag from 48 hours to 15 minutes with zero manual entry.
Entity_Client
Quantitative Investment Firm (NDA)
Primary_Role
AI Automation & Backend Architect
Duration_Log
12 weeks
Resource_Team
1 dev, 1 design
Project_Overview
A quantitative asset management firm relied on timely financial data from company filings — but reports were locked in non-searchable PDFs across multiple exchange portals. Analysts spent 48+ hours manually gathering and entering data after each release. We built an autonomous pipeline that monitors portals, downloads reports the moment they're published, extracts all financial data via OCR, validates it mathematically, and outputs ML-ready structured datasets.
Operational_Process
Built a headless browser automation layer for portal navigation and document download. Developed a custom OCR pipeline with OpenCV table detection for financial statement extraction. Added a Pandas-based data cleaning and normalization engine. Exposed results through a React dashboard for monitoring and manual triggers.
Core_Capabilities
Performance_Metrics
Data Availability Lag
DATA_POINT: post-release
Manual Data Entry
DATA_POINT: zero touch
Table Extraction Accuracy
DATA_POINT: alignment accuracy
Math Validation Error Rate
DATA_POINT: across thousands of rows
Analyst Research Time
DATA_POINT: review only
ML Pipeline Readiness
DATA_POINT: time-series output
Conflict_Resolution
Implemented sophisticated headless browser automation with randomized user-agent rotation, request throttling, and human-behavior simulation — achieving consistent document retrieval.
Integrated OpenCV computer vision to detect table boundaries before OCR execution, ensuring 98% data alignment accuracy across merged cells and vertical text.
Built a Python mapping layer that normalizes diverse terms (e.g. 'Revenue' vs 'Turnover') into a unified database schema, enabling cross-company analysis.
Built an asynchronous processing queue using FastAPI background workers, enabling hundreds of pages to be processed in parallel without system degradation.