Private market participants on the lending, acquisitions, and advisory sides of the CRE business recently described a harried environment given the impact of coronavirus, with their clients focused on damage control in the nearest term as they seek to reduce their risk exposures.^[1] According to analysis by S&P Global Ratings,^[2] the indirect impact of sharply slower economic growth and financial market volatility could be felt across all property types, as the effects of social distancing, travel restrictions, and lower oil prices deteriorate the financial health of tenants.^[3]

The economic and credit implications of the coronavirus outbreak have already weakened the credit quality of real estate investment companies in Europe, according to S&P Global Ratings,^[4] as tenants' creditworthiness and capacity to pay contracted rents starts to falter. In addition, most governments have announced measures to contain the virus and support corporates in difficulty, some of which are credit negative to landlords, such as stores and hotels.

With these fast changing market conditions, staying on top of the creditworthines of commercial property tenants will become more paramount. Having a baseline understanding of their financial viability and overall credit risk is an important starting point. This can help drive decisions around pricing strategies, deposits requirements, and any potential enhancements/incentives over the life of a lease, plus serve as a benchmark for monitoring changes in a tenant’s ability to pay.   

Figure 1: A Robust Tenant Analysis System Starts with Credit Risk Analysis

Credit risk analysis in the CRE sector can be challenging, however, given that many tenants are smaller and/or unrated companies. S&P Global Market Intelligence Credit Analytics provides a suite of capabilities for tenant and overall Industry/sector assessment, including three quantitative models that generate probabilities of default (PDs) and credit scores for rated, unrated, public, and private companies around the globe. The credit scores are designed to broadly align with credit ratings from S&P Global Ratings.^[5]

Three Quantitative Models to Support Tenant Analysis

Credit risk indicators based on quantitative approaches should incorporate market conditions that reflect the impact of major crises, such as the 2008 recession and the 2011 sovereign crisis, in order to be adequate for use during COVID-19 market shocks. The Credit Analytics models include:

PD Model Fundamentals that looks at financial risk and business risk to measure the likelihood of default for 860,000+ public and private banks, corporations, and REITS over one- to five-year time horizons.^[6]

PD Model Market Signals that provides a point-in-time view of credit risk for public companies based on a sophisticated model that captures equity market sentiment, providing signs of potential default for 71,000+ public companies.^[7]

CreditModel^TM  that is a credit scoring model trained against S&P Global  ratings to produce credit score for 73,000+ larger corporates and financial institutions.^[8]

These models can offer a fundamentals-based or market-driven view of tenants in distress. In particular, equity-based credit indicators can provide some leading indication of credit risk deterioration when other credit metrics may be lagging. In addition, deeper analysis using fundamentals-based indicators that also incorporate early-warning metrics can confirm market-based signals and/or highlight risk factors that could lead to a default.

To complete the picture, Credit Analytics enables scenario analyses to help evaluate how tenants may be impacted by potential future financial, macroeconomic, and business factors. Users can also easily monitor companies in their lease portfolios through dashboards or custom Excel® templates, plus activate alerts to be notified about any changes to a tenant’s creditworthiness.

We looked at the median PD from PDMS for several CRE and real estate investment related sub-industries globally between April 2, 2019 and April 1, 2020 to illustrate some of the market trends mentioned in the introduction to this article and identify any patterns in the evolution of credit risk in these sectors. As seen in Figure 1, there is a clear escalation in credit risk across all these sub-industries. In particular, Hotel and Resort Real Estate Investment Trusts (REIT) experienced the sharpest increase in the PD. This represented more than a 900% increase, from 0.346% to 3.532%, between March 2, 2020 and April 1, 2020 as the restrictions on travel and tourism took their toll on these businesses.

On the other end of the spectrum, the PDs for the Healthcare REITs are showing some resilience to  market conditions. This is partially due to companies having healthy balance sheets with demand for hospitals and testing facilities increasing as a result of the pandemic. The exposure to senior’s housing could see the median PD worsen significantly, however.  Also notable are the Office REITs that have seen a slower increase in the PD over the past month, due to the strength of their financials that have been enhanced, in many cases, with long-term leases. The PD could see some deterioration as market conditions worsen, however.

Figure 2: PDMS Evolution in CRE and Real Estate Investment Sub-industries

^{Source: S&P Global Market Intelligence, PDMS as of April 2, 2020. For Illustrative purposes only,}

Three Steps to Leverage Credit Analytics to Assess and Monitor a Tenant

1. Search, view, and load standardised financials and non-financial inputs for the tenant company with the Credit Analytics ‘Score Company’ interface for PD Model Fundamentals and CreditModel, using data from the S&P Capital IQ platform.

Figure 1: Load Inputs

^{Source: S&P Global Market Intelligence, as of March 2020, for illustrative purposes only.}

The financial and non-financial data are pre-loaded for hundreds of thousands of companies in our database. These can be over-ridden with a user’s own proprietary financials.

2. Generate a PD and credit score for the tenant using Credit Analytics, based on the inputs outlined above. 

Figure 2: Example of Outputs from Credit Analytics for a Specific Company Using PD Model Fundmentals

^{Source: S&P Global Market Intelligence, as of March 2020, for illustrative purposes only.}

The above is a small subset of the information available for a company. A PD percent, corresponding credit score, and other supporting analysis will be automatically generated. This includes a country and industry peer comparison and two critical components that describe the  Business Risk and Financial Risk. Many alternative models only focus on Financial Risk, which was a shortcoming during the past financial crisis.

3. Add to a ‘Watch List’ to establish a monitoring system via the ‘Dashboard’ features .

Figure 3:  Portfolio Surveillance and Monitoring

^{Source: S&P Global Market Intelligence, for illustrative purposes only.}

Upon generating the PD and credit score for a company, users can automatically save the company to a Watch List and use the Dashboard to generate alerts based on a user-defined tolerance level to monitor changes in the creditworthiness of the tenant company. When new financial statements are available for a company, it will be automatically re-scored and users will receive an alert.

Uncertainties around the world continue to rise with the impact of the coronavirus, and the CRE sector is feeling the impact. For more information on how Credit Analytics can help with tenant assessment, please contact us here.

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^{[1]  “Commercial real estate in uncharted territory as market retreat deepens”, S&P Global Market Intelligence, March 17, 2020.
[2] S&P Global Ratings is analytically and editorially independent from any other analytical group at S&P Global.
[3] “REITrends: COVID-19 Could Threaten Rating Stability for North American REITs,” S&P Global Ratings, March 17, 2020.
[4] “COVID-19: Implications For European Real Estate Investment, As Tenants Begin To Suspend Rent Payments,” S&P Global Ratings, March 26, 2020.
[5] S&P Global Ratings does not contribute to or participate in the creation of credit scores generated by S&P Global Market Intelligence. Lowercase nomenclature is used to distinguish the credit scores generated by the model from the actual S&P Global Ratings credit rating.
[6] As of March, 2020.
[7] As of March, 2020.
[8] As of March, 2020.}