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Algorithms to power NLP engines with overall accuracy of 85% and full ownership of intellectual property
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70%+ operational cost savings
Client challenge
- Needed to create an in-house scoring framework that is fully transparent, able to provide real-time updates and customisable to the current portfolio
- Preliminary scope included analysing textual data sourced from news and company publications to create sentiment scores based on UN SDGs
Our approach
- Deployed a three-member team: 1 lead data scientist, 1 data scientist (NLP specialist) and 1 data engineer to build, test, deploy and fine-tune the NLP engines
Impact delivered
- A proprietary in-house ESG scoring framework based on NLP engines that is transparent, functions in real-time and is 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 based in an offshore delivery centre
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