SBTi-Finance Tool for Temperature Scoring & Portfolio Coverage

Note

This tool implements Version 1.0 (PDF) of the CDP/WWF Temperature Rating Methodology, for setting and reporting on SBTi Financial Institutions Near-Term Targets. For Version 1.5 of the methodology, please refer to the CDP-WWF Temperature Scoring Methodology.

Do you want to understand what drives the temperature score of your portfolio to make better engagement and investment decisions?

Based on Version 1.0 of the temperature scoring method, developed by CDP and WWF, this tool helps companies and financial institutions to assess the temperature alignment of current emission reduction targets, commitments, and investment and lending portfolios. They can for instance use this information to develop their own GHG emission reduction targets for official validation by the Science Based Targets initiative (SBTi), develop engagement strategies and help with strategic security selection and allocation decisions.

This chapter provides a non-technical introduction and overview of what the tool is for, the types of outputs it delivers, what data is required, how it works, and where you can find more information and documentation to start using the tool.

An introduction to the technical documentation

The SBTi-Finance tool has been built as an open-source, data-agnostic tool and works with input data from any data provider and in many different IT infrastructures.

Quickstart

• Python package: Install via pip install sbti-finance-tool and integrate directly into your codebase. See the Getting Started Using Python section.

• Jupyter notebooks: Run the example notebooks on Google Colab or locally. Start with the Analysis example.

• REST API: Deploy the tool as a containerized microservice. See the Getting Started Using REST API section.

Given the open source nature of the tool, the community is encouraged to make contributions (refer to the Contributing section) to further develop and/or update the codebase. Contributions can range from submitting a bug report, to submitting a new feature request, all the way to further enhancing the tool’s functionalities by contributing code.

Contents:

• Introduction to temperature scoring and portfolio coverage methods
  • Why has SBTi built this tool?
  • Why have we built the SBTi-Finance tool in this way?
  • What can I use the SBTi-Finance tool for?
  • What data do I need to use the tool?
  • Where can I find the data?
  • Overview of how the tool works
  • What are the outputs the tool generates?
• Getting Started Using Python
  • Google Colab
  • Jupyter Notebooks
  • Python code
  • Using the SBTi Data Provider
• Getting Started Using REST API
  • Quickstart
  • Endpoints
• Functional Overview
  • Temperature Score
    • Time Frames
    • Scopes
    • Aggregation methods
    • Grouping data
    • Choose fields to show
    • What-If Analyses
  • Portfolio coverage
  • Output options
• Data Requirements
  • Portfolio data
  • Company data
    • Fundamental data
    • Target data
      • By-Target Download Format
  • SBTi CTA File Formats
  • SBTi status
• Data Legends
  • Temperature rating Input Data
    • Portfolio Data
    • Fundamental Data
    • Portfolio Coverage Target data
    • Temperature Rating Target data
  • Output data
• Contributing
  • Submitting a bug report or a feature request
  • Contributing code
    • Getting started
    • Coding guidelines
  • Releasing
    • Generate documentation
  • Code of conduct
• Project Links
• Terms of Use
• API Reference