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Automated ESG Scoring System - HackBogazici

An automated ESG scoring engine built from four scraped data sources - 2nd place among 14 hackathon teams.

2nd / 14 · Teams

Boğaziçi University IT Club (hackathon) Machine Learning & Data Science
ESG Web Scraping NLP Computer Vision Data Fusion Scoring
Automated ESG Scoring - HackBogazici

The challenge

ESG scores are only as good as the data behind them, and useful signals are spread across many public sources in incompatible formats - some text, some images. At HackBogazici, the challenge was to pull those fragments together into a coherent, automated ESG score within the constraints of a hackathon.

Doing this well meant handling both text and image data and fusing them into a single scoring pipeline, not just analysing one source in isolation.

The approach

My team developed an automated ESG scoring system that analyses text and image data scraped from four different sources. The pipeline collects the raw data, processes each modality, and fuses the signals into an overall ESG score - turning scattered public information into a single, comparable measure.

The end-to-end system, built under hackathon time pressure, placed 2nd among 14 teams, demonstrating both the technical approach and its practical value.

The outcome

Results that moved the needle.

2nd / 14

Teams

Second place at HackBogazici

4

Data sources

Text and image data scraped and fused into scores

Automated

ESG scoring

End-to-end scoring pipeline from raw scraped data

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