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Covers: theory of ML in Climate Change Finance
Estimated time needed to finish: 20 minutes
Questions this item addresses:
  • How to use word embedding and cosine similarity to analyze climate change disclosures?
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Author(s) / creator(s) / reference(s)
Alexandra Luccioni, Hector Palacios
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An Introduction To ML In Climate Change-Related Finance

Contributors
Total time needed: ~2 hours
Objectives
Provide an introduction to using natural language processing and other methods for climate-related financial problems
Potential Use Cases
Creating a question-answering system for sustainability disclosures
Who is This For ?
BEGINNERESG analysts or data scientists interested in finance and climate change
Click on each of the following annotated items to see details.
Resources6/6
PAPER 1. Integrating Climate Risks into Credit Risk Assessment - Current Methodologies and the Case of Central Banks Corporate Bond Purchases
  • How do climate risks impact companies' credit?
10 minutes
PAPER 2. FinBERT: A Pretrained Language Model for Financial Communications
  • How to finetune BERT for financial applications?
20 minutes
PAPER 3. Using Natural Language Processing to Analyze Financial Climate Disclosures
  • How to use word embedding and cosine similarity to analyze climate change disclosures?
20 minutes
PAPER 4. Analyzing Sustainability Reports Using Natural Language Processing
  • How to create question-answering system for sustainability reports?
20 minutes
OTHER 5. CDP Technical Note on the TCFD
  • How should companies prepare for climate change?
5 minutes
OTHER 6. Sustainability Disclosure Database
  • How do I find sustainability disclosures for companies?
5 minutes

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