Solution

OS-Climate Solution

OS-Climate will use the open source approach that has enabled breakthrough innovation in life sciences and tech by companies including Red Hat, Microsoft, Google, etc.  Through a non-profit business association enabling stakeholders to share cost, intellectual property, and effort, OS-Climate will develop:

OPEN SOURCE COMMUNITY & MODELING PLATFORM

  • Governance, licensing, and collaboration structures.
  • Interconnect existing models and data.
  • Jointly undertake new data collection, modeling, software engineering.

GLOBAL DATA COMPENDIUM & DATA COMMONS

  • Corporate metrics as a free public good.
  • Curated library of public and private data sources for financially material factors.

SCENARIO-BASED PREDICTIVE ANALYTICS

  • Simple, actionable visualizations to make complexity understandable.
  • Only offer advanced tools in cases where 3rd Parties cannot meet User needs and ability to pay.

OS-Climate Year 1-2 Focus

OS-Climate Use Cases – Years 2-3+

Platform Development Roadmap

OS-C will use a contract developer for Version 1.0; transitioning thereafter to a community-driven development approach as used to develop the Linux Operating System, blockchain, etc..

Sequencing and scope of subsequent projects – including decision on sequence of asset class and factor coverage — will be set by OS-Climate Foundation Governing Board with input from Technical Advisory Council and other advisory bodies (see pages 33-34)

Overall Platform Architecture, Uses, and Example of Possible Future Inputs

Version 1.0 Functional Schematic

Version 1.0 Functional Schematic – with 3rd Party Linkages Illustration

Version 1.0 Guiding Principles

  • Build a “kernel” of the data and modeling platform that is sufficient to begin adding functionality through a community-based open source development process.
  • Start simple, with the Data Commons backbone and initial datasets and one top-down Scenario Simulation as a Minimum Viable Product (MVP).
  • Extend from MVP to include additional top-down and bottom-up scenarios and models, contributed to the Platform through open source license by best-in-class commercial, NGO, academic, and governmental organizations.
  • Minimize technology risk and development timeline by only including existing, proven technologies already in use by asset owners and asset managers.

Climate scenario selection

Connecting Macro- & Micro-level Analytics

  • ‘Connecting’ the two levels of analysis highly valuable because it enables a holistic picture of potential impacts and thus allowing for development of a meaningful climate strategy
  • Interconnecting bottom up deterministic models and top down stochastic models is extremely challenging, especially in ways that are automated and scalable
  • No “right” way to do this sort of integration; it is in the still in realm of experimentation in modeling techniques

Illustrative Portfolio-Level Risk-Return Insights: from climate-uninformed to climate risk-aware

Example Sectoral Insights from Cambridge Econometrics

Illustrative Use Case: Country & Industry Insight

For example, users can vary policy and technology variables to see how they affect deployment of renewable energy in India

— Wireframe of planned interface

Use Case: Factor Attribution

Here, the portfolio manager utilizes a bar chart to compare individual factor relative performance contribution of factors by sector holdings across scenarios.

— Wireframe of planned interface

Example Third Party Tools Enabled by Platform

Managing Physical Risk

— Wireframe of planned interface

CLIMATE-RELATED RISK AND OPPORTUNITY FOR COMPANIES IS DRIVEN BY MANY FACTORS

EACH FACTOR “BUCKET” INCLUDES MANY VARIABLES THAT MATERIALLY IMPACT PERFORMANCE AND PRICES OF COMPANIES, ASSETS, AND PROJECTS

EXAMPLE OPPORTUNITY INDUSTRIES & TECHNOLOGIES

OPPORTUNITY – TRANSPORT VALUE CHAIN EXAMPLE