Last month, Boulder Colorado-based climate risk data provider, Entelligent was issued a U.S. patent around the methodology and prediction system associated with their proprietary climate risk measure called T-Risk.
Entelligent’s Recent Patent
The recently issued T-Risk patent covers systems and methodologies that generate climate transition risk metrics by applying defined energy factors to historical financial information for securities; performs statistical analyses using those factors to project securities’ performance across selected climate scenarios; and calculates the spread between the two projections to provide a risk metric.
Entelligent’s latest achievement, U.S. Patent No. 11,694,269 builds on and strengthens the protections of the company’s 2019 patent, U.S. Patent No. 10,521,863, for its Smart Climate® methodology, the platform underlying much of the intellectual property developed since the firm’s founding.
The following profile provides details about Entelligent, its founders, the firm’s mission, its various climate risk products, and its unique approach to measuring climate risk.
Entelligent Profile
Provide general background on your firm. When were you founded, who founded the firm, and what was the primary business problem you were trying to solve?
Entelligent, based in Boulder, Colo., was founded in 2017 by Thomas H. Stoner, Jr., CEO, and Dr. David Schimel, Chairman. Mr. Stoner is a CleanTech entrepreneur who co-founded three companies in the field of renewable energy and served as CEO of two public companies. He also led the London IPO of Econergy International. Dr. Schimel is a Nobel laureate and Senior Research Scientist at NASA Jet Propulsion Lab. He is also a member of the Entelligent science committee and a lead author of several UN IPCC reports.
Entelligent was founded to address the lack of climate risk data for private businesses and investors. What one cannot measure, one cannot manage. Governments had not progressed in addressing the risks of climate change, and the founding of Entelligent was mostly motivated by the belief that private businesses can better address the upcoming challenges of climate risk.
The firm’s mission is to provide best-in-class climate risk metrics to investors to allow them to improve their risk-adjusted performance or risk management. This will in turn pass on climate risk information into markets as premium for companies doing a good job transitioning and as a discount for companies not transitioning to a lower carbon economy. In fine, this will incentivize companies to transition.
What type of data, services and related technology does your firm provide? Outline the unique data elements an asset manager can receive from you that are not generally available from others?
Entelligent is a pure-play, climate data and analytics company with a patented approach to measuring climate risk. They provide security-level data for use in opportunity identification, risk management and climate and ESG compliance. Entelligent’s products include:
- T-Risk — Measures transition and physical risk by estimating return spread between BAU and an alternative scenario. (Two additional scores — T-Risk Carbon-Adjusted and Smart Climate VaR — are derived from T-Risk.)
- E-Score — Measures price return volatility for near-term climate transition risk (climate resiliency).
- Smart Climate Carbon Sensitivity — Measures carbon-pricing risk, to assess and track environmental impact of holdings
- Smart Climate Carbon Accounting — A bolt-on data set for carbon disclosure and reporting.
- Smart Climate Loan Book — Measures climate risk for commercial bank obligors.
What differentiates Entelligent’s data:
Where most data providers focus on how companies impact climate, Entelligent analyzes how climate change impacts companies’ investor returns. The firm’s model predicts investment securities’ performance in a range of future climate scenarios to enable risk management and opportunity identification.
Entelligent’s approach makes its data more accurate and timelier than competitors. Many climate risk data providers are aggregators, which gather as much company-reported data as they can and then add value if and as necessary. Entelligent begins with climate science, then applies proprietary analytics – and only adds entity-reported data downstream, in a controlled and visible way.
Explain the basic process you use to collect and/or create the data you produce? Is any of the data you collect considered PII? Do you have all the necessary consents to collect and store the data you sell?
Climate-science and energy-based, Entelligent scores begin with IAMs (Integrated Assessment Models) to forecast energy mix, prices, supply, demand, etc., across one or more scenarios. Entelligent then applies machine learning-driven statistical analysis to identify the most useful energy data. Finally, Entelligent determines the impact of climate change at the security level. (Entelligent’s scores do not rely on self-reported or third-party company carbon data as its primary input, which (although useful and necessary) are imperfect and incomplete sources.)
Entelligent holds two U.S. patents on its process. The first (2019) — for its foundational Smart Climate® model — covers systems and methodologies that use climate and energy scenarios to simulate energy sources’ impact on securities and generate return data for a security or portfolio. The second (2023) covers the T-Risk methodology specifically. Additional patents are pending in EU and Hong Kong.
None of Entelligent’s data includes PII (personally identifiable information). Entelligent has all the necessary consents to collect and store the data they sell.
How much history can a client obtain from you? How frequently is this data updated?
- E-Score: 15+ years (2007).
- T-Risk: 13+ years (2010).
- T-Risk Carbon-Adjusted: 10+ years (2013)
- Entelligent’s data is updated quarterly within a few business days of EOQ. (By comparison, carbon data is generated yearly and most often on a one-year lag).
- T-Risk coverage: ~40,000 global listed equities; emerging and developing markets; small, mid and large cap. With 2-year and 10-year projections.
- E-Score coverage: ~10,000 global listed equities; emerging and developing markets; small, mid and large cap. With 2-year projections.
Describe at least one “case study” of where your firm’s data, services or technology has proven to be predictive.
Energy Sector Case Study. For more information, contact Pooja Khosla, PhD, Chief Innovation Officer
- The objective of this case study is to show how climate risk data that adds security-level analysis to sector-level analysis can be vital to investors who want exposure to the Energy sector while minimizing transition risk to a lower-carbon future.
- The case study posits an equity index that invests in the top 25% of S&P 500 Energy sector companies ranked by T-Risk Carbon-Adjusted scores over the prior two quarters.
- Comparing two Energy sector stocks, we see that PG&E (a T-Risk “leader”) is screened into the index while Phillips 66 (a T-Risk “laggard”) is typically screened out. The table below shows the factors driving the two companies’ respective T-Risk scores; farther down, the stock chart shows PG&E’s consistent superior returns versus Philips 66.
- Thus, T-Risk enables both consistent financial and consistent environmental performance.
| Factors | PG&E | Phillips 66 |
| Renewable Energy Integration | Actively transitioning towards renewable energy sources and setting goals to increase renewable capacity | Primarily focused on fossil fuels and refining petroleum products, with limited involvement in renewable energy |
| Energy Transition Planning | Developing plans and strategies for clean energy initiatives, grid resilience, and energy efficiency measures. | Limited involvement in the energy transition beyond compliance with emissions regulations. The company historically had significant business operations in Texas, California, and Oklahoma. |
| Regulatory Environment | Operating within a heavily regulated industry pushing for cleaner energy and reduced emissions. | Facing emissions regulations mainly for refining operations rather than a shift to renewable energy |
| Community Engagement and Resilience | Strong emphasis on community engagement, disaster preparedness, and resilience in the face of climate-related risks | May have disaster preparedness measures but not tied to community services like electricity and natural gas |
| Sustainability Commitments | Demonstrating commitment to reducing greenhouse gas emissions and promoting sustainable practices | Focused on meeting emissions standards and reducing environmental impacts but with less emphasis on renewable energy |
Who is your firm’s target market in the financial services vertical? What other types of consumers purchase your data?
Institutional investors (such as pension funds, asset managers and hedge funds) and banks.
Who are some of your firm’s chief data competitors in the financial services market?
MSCI Climate VaR, S&P TruCost, Sustainalytics, etc.
What makes your firm different from other firms providing similar types of data, services, & technology?
See above and also —
- Rooted in climate science: Begins with top-down data, adding entity-reported data (such as carbon emissions) downstream in a controlled and visible way.
- Comparable and scalable: Smart Climate® scores are standard — consistent across assets, regions and sectors.
- Transparent: U.S. patent-protected “white-box” solution set.
- Financially material: Climate risk metrics are forward-looking and projectable, and expressed in terms of asset price and return.
- Compliance-relevant: Meets most-current requirements for disclosure, scenario analysis and stress-testing.
- Performance conscious: Smart Climate® transition risk and resilience metrics consistently improve risk-adjusted returns versus benchmarks.
Who are a few cornerstone clients in the financial services market that use you? How do they generally use your platform?
- Bank of America to build climate change resilient indices.
- Société Générale to build climate change resilient indices.
- United Nations Joint Staff Pension Fund to produce their first-ever TCFD report: https://www.unjspf.org/wp-content/uploads/2022/06/UNJSPF_Report_March8.pdf
What is your firm’s commercial model? What is the price range for your service?
- Data Subscriptions (Between $50K and $150K / year, depending on data set, client and use case)
- Entelligent’s data is delivered via several platforms, including the FactSet Workstation.
- Index Licensing (Fee is based on bps / AUM)
- Consulting Services when creating new custom products (price varies)
What are a few of your firm’s next major targets/milestones?
- Entelligent is planning to complete before year-end a UNEP-FI project to build new climate risk-adjusted inputs for banks’ credit models with our partner, PwC.
- Entelligent is also in the process of launching up to four new climate risk indices by October with TPEX (the Taipei exchange) in partnership with FactSet indices.
Contact information
Pooja Khosla, Ph.D., Chief Innovation Officer pkhosla@entelligent.com
Hadrien Mouliner, Chief Revenue Officer hmouliner@entelligent.com