What does GeoPhy offer on data?
We live in a world of data and, as consumers, it drives the decisions we make. The real estate sector model remains traditional, however, and we, for example, still base valuations on four or five variables and comps, where small adjustments can have a big effect.
What GeoPhy wants to change is the way we use data to evaluate investment opportunities and their pricing. GeoPhy has developed a data platform to map and assess the quality of assets and quality of locations in a standardised way, leading to distinct evaluations that are comparable across property types and regions.
This gives investors the metrics to benchmark investments in real estate.
In addition to assessing quality of assets and locations, we have developed an automated valuation model, with Fannie Mae, which has a significant portfolio in the single and multi-family spaces, as an early user.
We can now predict the value of a multi-family asset more accurately than a traditional appraisal. We can also use the model for office buildings in the UK, or retail assets in Germany, as an alternative to traditional valuations.
My personal goal is to educate real estate investors on the use of big data until they realise the possibilities of having hyperlocal, high-frequency information on assets. For partners such as pension funds and insurance companies, we’ve built the GeoPhy Alpha platform.
It allows these investors have a look-through from the overall portfolio all the way to tenants in individual buildings, enabling a deep understanding of their risk exposure to property types, regions, tenants, and more.
How could better use of data affect the real estate industry in the future?
Traditional valuation models are based on data, but the small number of observations tends to miss small adjustments in cap rates and other variables. I don’t think a human being can take hundreds of different variables into account when valuing a property, so automated valuations are the only way forward to achieve a more frequent and precise estimation of value.
Institutional investors need tools and innovations to make data useful. We can now exploit massive amounts of data on much more actual, local indicators of economic activity.
Data on restaurants, bars, events and art galleries, in combination with traditional indicators, such as public transport and catchment areas, can be used to come up with precise models for site selection and due diligence purposes.
Generally, institutional investors are excited but cautious about how we fit this into the traditional processes of due diligence, investment decisions and management and monitoring of assets. From excitement to implementation, there is one step that is the most important, and that is education.
This is where investors will start to realise the implications of data, particularly how it can be translated into information, and how it can be utilised in the traditional investment process.
What kinds of trends are you seeing in the institutional real estate sector in North America?
The biggest trend, not surprisingly, is the current uncertainty around real estate prices. These prices are now fairly rich, so we will need significant rental growth in order to meet the market’s expectations.
There is also uncertainty about whether the optimism in the economy and the stock market will really materialise over the next six to 24 months. We also don’t know if the (very) optimistic predictions of 4 percent economic growth are really going to happen. The economy can easily be derailed, due to, for example, a geopolitical event.
The market is thus in a waiting mode with lower transaction volumes, meaning outflows from the large open-ended funds rather than in-flows. In terms of leverage, we luckily don’t see what we saw in 2007, and although the market is expensive, there remains a lot of capital to be deployed. Transactions are still taking place but not with the exuberant optimism of two to three years ago.
Foreign buyers continue to invest for a large share in the US real estate market. Following uncertainty around Brexit and the low European Central Bank rates, which means negative yields in real terms in Germany and the Netherlands, the US doesn’t seem a bad place to invest, after all.
How can real estate be convinced to do more with the data available?
We can learn a lot from other industries that take a much more quantitative approach. The data is there, it just needs to be made available. If you are a real estate investor, you can’t afford to not start using data or change your investment processes.
It could mean the difference between winning business and decreasing the chances of risks.
This sector is very simple. Once something is seen to be working, wider adoption ensues. We need another six to 12 months for the real estate sector to come to the realisation and then we then need 24 months for the sector to start adopting it.
Do you expect any pushback?
Everything that’s different will face pushback. Uber and Airbnb are interesting examples. Funds that use our data for a bottom-up analysis valuation can make better investments, which means they perhaps need fewer analysts for due diligence and underwriting.
More data and more transparency may also imply lower fees. If you take all the buildings globally, real estate is the largest asset class, but if you look at institutional real estate, it’s 7 percent of the average institutional portfolio compared to equities that are on average 50 percent.
Fixed income and equity are high in transparency and very liquid, and a lot of money is still being made.
I am convinced that the efficient use of data will lead to more capital inflows and more accurate pricing. More data means more money being made by asset managers and pension funds, but in the short term, it is very scary for investors.
A bank may think that its margins will come under pressure and an investment manager may think it no longer gets business, so there will be plenty of resistance, but a sector that is going to be more transparent and more liquid is ultimately going to be a better sector.