Finance & Fintech
ESG Diversity & Sentiment Solution - CFA Poland Hackathon
An ESG prototype scoring gender diversity and news sentiment - 2nd place among 44 teams from 28 universities.
2nd / 44 · Teams
The challenge
Investors increasingly want ESG signals that go beyond self-reported corporate disclosures - but measuring something like gender diversity or public sentiment about a company objectively, and at speed, is hard. The CFA Poland 'AI in Investing' hackathon set exactly this kind of challenge, under tight time pressure and against a strong field of competitors.
The task was to build a working ESG solution that turned messy, public, real-world data into usable investment signals.
The approach
My team built an ESG solution that measures gender diversity and analyses news sentiment, combining web scraping, computer vision and NLP into a single pipeline. Web scraping gathered the raw public data, computer vision contributed to the diversity analysis, and NLP handled sentiment on news coverage.
The result was an end-to-end prototype that converted scattered public information into structured ESG signals. It placed 2nd among 44 teams drawn from 28 universities - a strong result in a competitive, finance-focused field.
The outcome
Results that moved the needle.
- 2nd / 44
-
Teams
Second place at the CFA Poland 'AI in Investing' hackathon
- 28
-
Universities
The field of competing teams
- ESG
-
Diversity + sentiment
Gender-diversity scoring and news-sentiment analysis combined
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