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30
data fields analysed
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10
alternative datasets sourced
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4
NLP engines built
CLIENT PROFILE AND CHALLENGES
- Director of ESG Integration and Research of a global institutional asset management firm
- The client wanted an in-house ESG scoring framework that was fully transparent, able to provide real-time updates and customisable to the current portfolio
- Scope included analysing textual data sourced from news/company publications to create sentiment scores based on UN SDGs
OUR APPROACH
- Deployed a three-member team – 1 lead data scientist, 1 NLP specialist and 1 data engineer – to build, test, deploy and fine-tune the NLP engines
- Built a classification model to identify SDG statements within company reports
- Build a bespoke sentiment analysis model for news data
- Created a bespoke UI for portfolio managers
IMPACT DELIVERED
- A proprietary in-house ESG scoring framework based on NLP engines – transparent, able to provide real-time updates and scalable
- Algorithms to power NLP engines with overall accuracy of 85% and full ownership of intellectual property
- 70%+ operational cost savings by leveraging a skilled data science team working from an offshore delivery centre
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