Can Data Rescue Solar Stocks? Google Is Leading the Way

Published originally on GreenTech Media by Jason Kaminsky

Imagine, for a moment, that you are an investor and somebody is in your office pitching you on magical beanstalks. The magical beanstalk industry is growing, and you have been asked to invest in a plot of land that will be developed into a magical beanstalk farm.

This all sounds great, but you’re new to magical beanstalks, and as an investor you need to weigh risk versus opportunity. How many of the plants die each year? Which species of magical beanstalk is the most reliable? What happens to your investment if the USDA changes its rules? Farmers claim that the investment is safe, but you’re getting spooked, and the important data — the data for your underwriting model, such as annual yields, geographic variance, death rates — just isn’t being shared. You wonder: Are they hiding something?

Solar theories and truisms

Of course, this story is an allegory for the solar industry. To the outside world, we are the growers of magical beanstalks — we literally generate value from the sun — and still the new kid on the block in the finance world. Just look at how we are classified: solar falls within the “esoterics” category for securitizations right next to rail cars, cell towers, and drug royalties.

As an industry, it’s our job to make investors comfortable with solar. There are truisms in the consumer finance market about how different loans perform; for example, even if homeowners default on a mortgage, they may still pay their auto lease because they need the car to get to work. We haven’t developed truisms for solar, so we push a lot of theories on how these investments will perform.

For residential solar, the investment opportunity is a hybrid of consumer finance and project finance. Most of the time, a consumer lender needs to understand consumer behavior, and maybe a bit about the asset they’re financing. Solar investors need to understand not only how the equipment will perform and the regulatory environment in which these projects operate, but also how consumers will behave given different performance and savings profiles. We believe that this savings element is so unique to solar that it may be the most important indicator of delinquencies and default.

When faced with uncertainty, data is a pathway to understanding and acceptance. Without data, we see investors either avoid the market entirely or severely “haircut” the cash flows needed to meet their return. For example, the average advance rate for solar securitizations is 75 percent, compared to 92 percent for autos and 99 percent for mortgages. Data opacity also results in conservative assumptions: Kroll assumes 0.75 percent annual degradation and stress-tests cash flows at a 1.2 percent degradation rate.

To finance the projected addition of 69 gigawatts of solar in the U.S. by 2022, it is our responsibility as an industry to effectively leverage the data that does exist.

Thought leaders at organizations like Google, PNC Bank and Sunlight Financial are working to effectively use their data for risk management and gain competitive knowledge from the industry’s largest independent database of solar data.

Access to metrics

Other industries use data to develop and secure investor confidence. In the home mortgage industry, a firm called CoreLogic retains an industry-wide database covering 99.8 percent of the mortgage market. A variety of industry stakeholders use these databases to better understand how mortgages perform across a broad spectrum of scenarios. In the early 2000s, CoreLogic provided insight into this market when investors were having difficulty understanding the risk of prepayments, and this allowed the mortgage business to grow. After the recent mortgage crisis, investors are today focused on the risk of delinquency and default, and they leverage industry data to inform their credit models. As a result, mortgages remain a trillion-dollar market.

Experian replicated this model for consumer credit. Trepp does this for commercial mortgages. Even the nascent peer-to-peer lending industry has a firm, Orchard Platform. The evolution of an independent, vertical-specific industry database is an inevitable step in the maturation of any asset class.

We see the need for this role in the solar market. To enter the market, investors need to have transparency into how large pools of solar projects are performing under different conditions, and to evaluate the “solar farmer” compared to an industry standard. Importantly, this data can be used without giving up a competitive advantage; once getting comfortable with the market as a whole, investors are still going to seek out the best brands, the most efficient developers, and the highest quality servicers. By way of comparison, Wells Fargo is one of the world’s largest mortgage originators, and it also collaborates closely with CoreLogic in the sharing and use of mortgage data.

But today, the solar industry doesn’t use our data effectively. It’s nearly impossible for an investor to find real industry data to include in underwriting models or to become more comfortable with the market.

With support from the U.S. Department of Energy SunShot Initiative, KWh Analytics created an industry-wide solar project database including nearly 70,000 operating solar projects. The company gathers data on how these assets perform both technically and financially, and quantifies these results on an anonymized basis for the benefit of solar stakeholders.

Data to the rescue

We know from history that independent data aggregation can move an industry forward. It has the power to educate, the credibility of independence, and the benefit of volume. It can allow existing investors to better manage their exposure and bring new investors into the market.

Solar stocks are being hammered in large part due to liquidity challenges, even as the companies in the space are fighting to rebuild our energy infrastructure. We need to use all of the tools at our disposal to increase the availability of capital. A robust and transparent use of data is a necessary solution in our toolkit.