{"id":4663,"date":"2013-07-30T19:25:41","date_gmt":"2013-07-30T19:25:41","guid":{"rendered":"http:\/\/blogs.edf.org\/energyexchange\/?p=4663"},"modified":"2013-07-31T14:34:37","modified_gmt":"2013-07-31T14:34:37","slug":"pushing-energy-efficiency-finance-beyond-theory-to-practice","status":"publish","type":"post","link":"https:\/\/blogs.edf.org\/energyexchange\/2013\/07\/30\/pushing-energy-efficiency-finance-beyond-theory-to-practice\/","title":{"rendered":"Pushing Energy Efficiency Finance Beyond Theory To Practice"},"content":{"rendered":"

By: Matt Golden, Senior Energy Finance Consultant, Environmental Defense Fund<\/p>\n

New Energy and Loan Performance Data Project Uses Latest in Data Science to Help Capital Markets Engage in Efficiency Lending<\/em><\/strong><\/p>\n

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Environmental Defense Fund\u2019s Investor Confidence Project<\/a> (ICP) and the Clean Energy Finance Center<\/a> (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.<\/p>\n

The Energy and Loan Performance Data Project<\/a> 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.<\/p>\n

Nearly 40%<\/a> of US energy is consumed by both residential and commercial buildings. \u00a0Realizing all of the available cost-effective energy efficiency savings would require roughly $279 billion of investment<\/a>, resulting in more than $1 trillion in energy savings over ten years. \u00a0However, currently, only 1% of all US investments are made in energy efficiency projects. \u00a0Our goal for this project is to help lay the foundation that will enable organizations to tap into this vast potential market.<\/p>\n

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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. \u00a0This results in high transaction costs, as well as risk premiums, that increase the cost of capital. \u00a0One of the main challenges is the small quantity and low quality of data that investors can utilize when evaluating investments in energy efficiency assets. \u00a0This 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.<\/p>\n

In collaboration with the University of Chicago’s new Data Science for Social Good fellowship<\/a> 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.<\/p>\n

Many key stakeholders in the energy efficiency sector support this new project, including the New York State Energy Research and Development Authority<\/a> (NYSERDA) and Citigroup<\/a> (Citi).\u00a0 NYSERDA\u2019s Treasurer, Jeff Pitken, stated that \u201cmaking 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.\u201d\u00a0 And Pam Flaherty, President & CEO of the Citi Foundation, which supports ICP and ICP participants like CNT Energy, said that \u201cpayment performance data is key to helping connect energy efficiency finance with capital markets activity in order to bring retrofit activity to scale and provide greater evidence to reach a wider variety of property asset classes.”<\/p>\n

Beyond loan performance, the project also seeks to provide the ability to analyze performance risks.\u00a0 This will allow investors to realize more predictable returns, which will lead to more lending at better rates. \u00a0Performance prediction is especially important for innovative energy financing models, such as On-Bill Repayment<\/a> and Energy Service Agreements<\/a>, and better analysis will enable the widespread adoption of these structures. \u00a0From an operations perspective, better data analysis offers the ability to continuously improve project commissioning \u2013 thus leading to increased energy savings.<\/p>\n

The Energy and Loan Performance Data Project<\/a> will be collecting data sets from some of the largest residential and commercial programs across the country. \u00a0We 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. \u00a0Data will be anonymized and modified to protect privacy, but will include the following elements:<\/p>\n