What are the benefits of developing a data management framework that reviews internal and external data holistically?

• • It’s important that data and underlying models are scrutinized and the uncertainties and assumptions behind the data are well understood. Otherwise, you can end up with data that doesn’t properly represent the actual impact to your business; data analytics for the most part is very much a “garbage in, garbage out” process.
  • A lot of our customers integrate our climate risk analysis with their internal data to gain a comprehensive understanding of what their risk looks like from an overall ESG perspective.
  • Also, from our perspective, we believe that all companies should aspire to integrate climate data into ERM processes and other decision-making tools, for processes such as supporting due diligence that a financial services company might perform before investing in a new asset. Some firms actually are already here; they’re on the forefront of climate resilience and preparing for the future.

What are the difficulties with collecting useable data for modelling?

• The underlying global climate models are open source data, but the ability to downscale the data to asset-level information involves an interactive process with a significant amount of verification and validation, as well as cloud computing resources.

• You can model temperature data relatively easily – the models provide min/max temperatures, and you can do a lot with that. But perils like fire, hail, flood, and tropical cyclones need more complex models and processing. This requires people with sophisticated skill sets in climate modeling, meteorology, machine learning, and other disciplines.

1. • A full understanding of climate risk demands the consistency of global climate models, rather than regional climate models (RCMs), which may not be suited to global financial and policy decisions, or offer only a piecemeal solution.

• The superiority of GCMs over RCMs is especially important, given likely SEC requirements that reporting companies consider physical risk to both their own assets (which might be concentrated in one region) AND  their value chain of suppliers and distributors (which may be spread across the world).

What is the importance of collecting data to satisfy investor appetite?

• • Building out additional metrics with the input of investors and customers is an important part of Jupiter’s R&D process. Without that feedback, it’s not always clear what is most important internally to specific companies.

How do you ensure data is consistent across jurisdictions?

• Jupiter uses the most up-to-date, scientifically backed and vetted global climate models (GCMs)
• Our quality control and de-bias modeling processes use a consistent approach, including global in situand satellite observation networks

How are metrics standardized across financial services?

• • The lack of standardization remains a known challenge for financial services firms across the world, although the TCFD offers guidelines that a lot of companies are choosing to follow.
  • The SEC (and, currently, the EU Taxonomy) has proposed additional requirements that are more specific.

Why is it important to develop standardized metrics across financial services?

• • • It’s increasingly crucial that firms have a consistent means of assessing the risk that they face across geographies and their supply chains; without a standardized set of metrics, it’s difficult to understand what the relative risks are.
    • Cross-industry metric standardization is important in risk assessment for financial services companies. This year, Jupiter strongly recommended to the SEC that a common, agreed-upon set of time horizons, scenarios, acceptable risk levels, and metrics should be among the criteria included in climate-risk reporting regulations. All would enable companies to better assess and manage changes in risk exposure over time. Having a common set of criteria also would facilitate and accelerate more consistent and meaningful disclosure reporting comparisons. Today, climate risk analytics are sufficiently mature to support comparisons among companies within a given industry or sector. However, more needs to be done to be able to accurately make comparisons across sectors.
    • Also, consistency in metrics is helpful to provide third parties like investors with common data for comparisons and decision-making.
• In ESG reporting, development of taxonomies, such as the one currently in effect in the European Union, along with international frameworks such as TCFD, will lead to greater consistency and comparability of criteria. These taxonomies are, in effect, dictionaries that establish a common language designed to give investors guidance on what constitutes “sustainable investment” in companies and sectors.

Why is having the right data important to measure and report on climate exposure

• • If you lack the right data from the start, you’ll end up with an inaccurate assessment of  climate exposure; that can be incredibly harmful to your business.
  • Jupiter’s team includes climate, Earth, and data scientists, technologists, and business professionals. Our solutions architects spend hours working closely with customers translating their needs into technology architectures. We also partner with top-tier consulting and engineering firms. Yet we focus largely on climate and data science – that’s where people need us the most. Companies can have a deep bench of economists at their own firms, but if their first step – understanding the climate – is a misstep, that won’t matter.