How Big Data & Advanced Analytics can help Real Estate Investment Trusts (REITS)

                                                         Image Credit – Kiplinger’s

Introduction…

Real Estate Investment Trust’s (REITS) are financial companies that own various forms of commercial and residential real estate. These assets include office buildings, retail shopping centers, hospitals, warehouses, timberland and hotels etc. Real estate is growing quite nicely as a component of the global financial business. Given their focus on real estate investments, REITS have always occupied a specialized position in global finance.

Fundamentally, there are three types of REITS –

  1. Equity REITS which exclusively deal in acquiring, improving and selling properties with the aim of higher returns for their investors
  2. Mortgage REITS only buy and sell mortgages
  3. Hybrid REITS which do both #1 and #2 above

REITS have a reasonably straightforward business model – you take the yields from the properties you own and reinvest the funds to be able to pay your investors (a mandated 95% of dividends). Most of the traditional REIT business processes are well handled by conventional types of technology. However more and more REITs are being challenged to develop a compelling Big Data strategy that leverages their tremendous data assets. 

The Five Key Big Data Applications for REITS… 

Let us consider at the five key areas where advanced analytics built on a Big Data foundation can immensely help REITS.

#1 Property Acquisition Modeling 

REITS owners can leverage the rich datasets available around renters demographics, preferences, seasonality, economic conditions in specific markets to better guide capital decisions on acquiring property. This modeling needs to take into account land costs, development costs, fixture costs & any other sales and marketing costs to appeal to tenants. I’d like to call this macro business perspective. Also from a micro business perspective, being able to better study individual properties using a variety of widely available data – MLS listings for similar properties, foreclosures, closeness to retail establishments, work sites, building profiles, parking spaces, energy footprint etc can help them match tenants to their property holdings. All this is critical to getting their investment mix right to meet profitability targets.

                                  Click on the Image for a blogpost discussing Predictive Analytics in Capital Markets

#2 Portfolio Modeling 

REITS can leverage Big Data to perform more granular modeling of their MBS portfolios. As an example, they can feed in a lot more data into their existing models as discussed above. E.g.  Demographic data, macroeconomic factors et al.  

A simple scenario would be if Interest Rates go up by X basis points – what does that mean for my portfolio exposure, Default Rate, Cost Picture, Optimal times to buy certain MBS’s etc ?  REITS can then use that info to enter hedges etc to protect against any downside. Big Data can also help with a range of predictive modeling across all of the above areas as discussed below.  An example is to build a 360 degree view of a given investment portfolio.

                                                         Click on Image for a Customer 360 discussion 

#3 Risk Data Aggregation & Calculations 

The instruments underlying the portfolios themselves carry large amounts of credit & interest rate risk. Big Data is a fantastic platform for aggregating and calculating many kinds of risk exposures as the below link discuss in detail. 

  

                                            Click on Image for a discussion of Risk Data Aggregation and Measurement 

 

#4 Detect and Prevent Money Laundering (AML)

Due to the global nature of investment funds flowing into real estate, REITS are highly exposed to money laundering and sanctions risks. Whether or not REITS operate in high risk geographies (India,China, South America, Russia etc) or have complex holding structures – they need to file SAR (Suspicious Activity Reports) with the FinCEN.  There has always been a strong case to be made that shady foreign entities and individuals were laundering ill gotten proceeds to buy US real estate. In early 2016, the FinCEN began implementing Geographic Targeting Orders (GTOs). Title companies based in the United States are now required to clearly identify the real owners of either limited liability companies (LLCs) or any other partnerships, and other legal entities being used to purchase high end residential real estate using cash.

AML as a topic is covered exhaustively in the below series of blogposts (please click on image to open the first one).

                                                         Click on Image for a Deepdive on AML

#5 Smart Cities, Net New Investments and Property Management

In the future, REITS would want to invest in Smart Cities which are positioned to be leading urban centers offering mobility, green technology, personalized medicine, safe services, clean water, traffic management and other forward looking urban amenities. These Smart Cities target a new kind of client- upwardly mobile, technologically savvy, environment conscious millenials. According to RBC Capital Markets, Smart Cities presents a massive investment opportunity for REITS. Such investments could provide REITS offering income yields of around 10-20%. (Source – Ben Forster @ Schroeders).

Smart Cities will be created using a number of high end technologies such as IoT, AI, Virtual Reality, Device Meshes etc. By 2020, it is estimated that these buildings will be generating an enormous amount of data that needs to be stored and analyzed by landlords.

As the below graphic from Cisco attests, the ability to work with IoT data to analyze a range of these micro investment opportunities is a Big Data challenge.

The ongoing maintenance and continuous refurbishment of rental properties is a large portion of the business operation of a REIT. The availability of smart sensors and such IoT devices that can track air quality, home appliance malfunction etc can help greatly with preventive maintenance.

Conclusion..

As can be seen from some of the above business areas, most REITS data needs require a holistic approach across the value chain (capital sourcing, investment decisions, portfolio management & operations). This approach spans various horizontal functions like Customer Segmentation, Property Acquisition, Risk, Finance and Business Operations.
The need of the hour for larger REITS is to move to a common model for data storage, model building and testing.  It is becoming increasingly obvious that Big Data can provide massive business opportunities for REITS.