New Energy and Loan Performance Data Project Uses Latest in Data Science to Help Capital Markets Engage in Efficiency Lending
Environmental Defense Fund’s Investor Confidence Project (ICP) and the Clean Energy Finance Center (CEFC), in partnership with state and local lending programs, financial organizations and a range of additional stakeholders, are collecting, aggregating and analyzing loan performance and energy savings data from energy efficiency upgrades in residential and commercial buildings.
The Energy and Loan Performance Data Project represents the first concerted effort to combine data from some of the largest US energy efficiency programs in an attempt to develop an actuarially significant dataset to help engage the capital markets.
Nearly 40% of US energy is consumed by both residential and commercial buildings. Realizing all of the available cost-effective energy efficiency savings would require roughly $279 billion of investment, resulting in more than $1 trillion in energy savings over ten years. However, currently, only 1% of all US investments are made in energy efficiency projects. Our goal for this project is to help lay the foundation that will enable organizations to tap into this vast potential market.
Currently energy efficiency investors of all types, including building owners, energy service companies, insurance providers and even utilities, are hampered by an inability to easily and accurately predict loan performance. This results in high transaction costs, as well as risk premiums, that increase the cost of capital. One of the main challenges is the small quantity and low quality of data that investors can utilize when evaluating investments in energy efficiency assets. This lack of data standards and access to large datasets has been cited by a broad range of stakeholders, including capital providers, policy makers, building owners and contractors, as impeding large-scale investment in building retrofits.
In collaboration with the University of Chicago's new Data Science for Social Good fellowship program, EDF and CEFC will identify how stakeholders use loan and project performance data, determine gaps that may exist in the current datasets and deliver high-quality analytics to support the advancement of energy efficiency finance and investment through actuarial data.
Many key stakeholders in the energy efficiency sector support this new project, including the New York State Energy Research and Development Authority (NYSERDA). NYSERDA’s Treasurer, Jeff Pitken, stated that “making our program loan performance history publicly available and aggregated with history from other programs will lower the cost of capital for these programs and allow more favorable financing terms to be offered to participating consumers.”
Beyond loan performance, the project also seeks to provide the ability to analyze performance risks. This will allow investors to realize more predictable returns, which will lead to more lending at better rates. Performance prediction is especially important for innovative energy financing models, such as On-Bill Repayment and Energy Service Agreements, and better analysis will enable the widespread adoption of these structures. From an operations perspective, better data analysis offers the ability to continuously improve project commissioning – thus leading to increased energy savings.
The Energy and Loan Performance Data Project will be collecting data sets from some of the largest residential and commercial programs across the country. We will be combining these sources with public sources, such as census data, to provide publicly-available data that we hope will accelerate investments in energy efficiency. Data will be anonymized and modified to protect privacy, but will include the following elements:
Please help us make this project a success. If you have a use for this type of data and analytics, or if you have data to contribute, please take a few moments to let us know how we can help by filling out this brief survey.
The Energy and Loan Performance Data Project represents the first concerted effort to combine data from some of the largest US energy efficiency programs in an attempt to develop an actuarially significant dataset to help engage the capital markets.
Nearly 40% of US energy is consumed by both residential and commercial buildings. Realizing all of the available cost-effective energy efficiency savings would require roughly $279 billion of investment, resulting in more than $1 trillion in energy savings over ten years. However, currently, only 1% of all US investments are made in energy efficiency projects. Our goal for this project is to help lay the foundation that will enable organizations to tap into this vast potential market.
Currently energy efficiency investors of all types, including building owners, energy service companies, insurance providers and even utilities, are hampered by an inability to easily and accurately predict loan performance. This results in high transaction costs, as well as risk premiums, that increase the cost of capital. One of the main challenges is the small quantity and low quality of data that investors can utilize when evaluating investments in energy efficiency assets. This lack of data standards and access to large datasets has been cited by a broad range of stakeholders, including capital providers, policy makers, building owners and contractors, as impeding large-scale investment in building retrofits.
In collaboration with the University of Chicago's new Data Science for Social Good fellowship program, EDF and CEFC will identify how stakeholders use loan and project performance data, determine gaps that may exist in the current datasets and deliver high-quality analytics to support the advancement of energy efficiency finance and investment through actuarial data.
Many key stakeholders in the energy efficiency sector support this new project, including the New York State Energy Research and Development Authority (NYSERDA). NYSERDA’s Treasurer, Jeff Pitken, stated that “making our program loan performance history publicly available and aggregated with history from other programs will lower the cost of capital for these programs and allow more favorable financing terms to be offered to participating consumers.”
Beyond loan performance, the project also seeks to provide the ability to analyze performance risks. This will allow investors to realize more predictable returns, which will lead to more lending at better rates. Performance prediction is especially important for innovative energy financing models, such as On-Bill Repayment and Energy Service Agreements, and better analysis will enable the widespread adoption of these structures. From an operations perspective, better data analysis offers the ability to continuously improve project commissioning – thus leading to increased energy savings.
The Energy and Loan Performance Data Project will be collecting data sets from some of the largest residential and commercial programs across the country. We will be combining these sources with public sources, such as census data, to provide publicly-available data that we hope will accelerate investments in energy efficiency. Data will be anonymized and modified to protect privacy, but will include the following elements:
- Loan Repayment Performance
- Underwriting Criteria and Deal Structure
- Project Attributes, Energy Conservation Measures and Predicted Performance
- Energy Performance Data (Realization Rate)
Please help us make this project a success. If you have a use for this type of data and analytics, or if you have data to contribute, please take a few moments to let us know how we can help by filling out this brief survey.
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