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Case Study

A Commercial Real Estate Firm Zeros In On Tenant Credit Risk


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A Commercial Real Estate Firm Zeros In On Tenant Credit Risk


The credit team needed a straightforward approach to assess the creditworthiness of tenants, many being smaller-sized private firms, to stay on top of the volume of work and help the company avoid losses.

Pain Points

Members of the credit team were tasked with pinpointing cases where the probability was high that tenants would default on their leases. As a small group, they needed a better way to identify potential problems and create succinct reports for senior management to review different situations. To support this, the team wanted to have:

  • A quantitative approach to evaluate the probability of default (PD) for a wide range of rated and unrated, public and private companies.
  • An early-warning system to quickly see any deterioration in a tenant’s credit quality.
  • The ability to streamline workflows to increase efficiencies.
  • Access to research on industries and companies to quickly pull background information into management reports.

The team reached out to S&P Global Market Intelligence (“Market Intelligence”) to discuss the firm’s offering and how processes could be more automated.

The Solution

Market Intelligence discussed its Credit Analytics solution that blends cutting-edge models with robust data to help users easily monitor their tenant portfolios. The models include: Probability of Default Fundamental Model (PDFN), CreditModel™, and PD Market Signals Signals Model (PDMS). Together, they provide the ability to assess companies of any size and put in place an early-warning system to detect possible defaults. Market Intelligence also described its extensive database of public and private company financials, plus a time saving tool for uploading proprietary financials to its desktop solution for further analysis. These capabilities would enable the credit department to:

Easily assess the creditworthiness of smaller-sized companies

PDFN enables users to evaluate the one- to five-year default risk of public and private banks, corporations, and Real Estate Investment Trusts. PDs can be mapped to quantitatively-derived credit scores (i.e., ‘bbb’) for increased comparability.[1] Workflows are optimized by accessing a pre-scored database leveraging comprehensive and timely data on over 50 million[2] companies globally. Users may also determine the default risk of a single company or a portfolio of companies.

Easily assess the creditworthiness of mid- and large-cap companies

CreditModel’s suite of statistical models, trained on credit ratings from S&P Global Ratings,[3] enables users to quickly evaluate the long-term creditworthiness of mid- and large-cap, public and private banks, insurance companies, and corporations globally. The models utilize financial statement and macroeconomic data to generate a quantitative credit score that statistically matches a credit rating from S&P Global Ratings. These scores can be mapped to observed default rates to quantify risk. Analysis can be streamlined by accessing a database of over 58,000 pre-scored entities, going back more than 15 years.

Create an early-warning system

PDMS is a statistical model that provides a point-in-time view by evaluating credit default swap spreads to provide an early warning of potential credit changes and captures the market’s daily view about a company’s perceived risk.

Evaluate public company financials

S&P Capital IQ Premium Financials provides standardized data for over 5,000 financial, supplemental, and industry-specific data items for over 150,000 companies globally, including over 95,000 active and inactive companies across multiple industries. Data is available at numerous frequencies and point-in-time representations of a financial period include press releases, original filings, and restatements.

Investigate private companies

Private Company Data covers 16 million private companies around the globe, 10 million private with financial statements, and 500,000+ early stage companies supported by data from Crunchbase.

Streamline the uploading of proprietary financials

ProSpread™ automatically extracts and spreads relevant data from PDF financial statements by leveraging Natural Language Processing combined with Optical Character Recognition.

Create segment and company profiles for customized tear sheets

RatingsDirect® is the official source for S&P Global Ratings’ credit ratings and research, and provides overviews of sector, industry, and company performance, along with market data, credit risk indicators, and dynamic visualization tools.

Key Benefits

The Market Intelligence offering resonated well with the credit team that saw the opportunity to be both more efficient and more accurate by utilizing:

  • A straightforward approach for calculating the PDs for public and private firms of different sizes.
  • Batch scoring to easily generate a list of credit scores that broadly align with ratings from S&P Global Ratings to quickly screen tenants.
  • An early-warning system with PDMS to react to changing market sentiment regarding different entities.
  • Transparency to understand where the risk lies in a company’s fundamentals and where to focus attention for analysis.
  • The Capital IQ platform to quickly retrieve data and do analysis with a wide array of advanced tools.
  • Detailed user guides and technical documentation for the models, plus access to a 24x7 support group.

Click here for more information on some of data and tools discussed in this Case Study.

[1]“Commercial Real Estate | Is The U.S. Out Of Office For Good?”, S&P Global Ratings, December 3, 2020.

[2] & [4] 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 differentiate S&P Global Market Intelligence PD credit model scores from the credit ratings issued by S&P Global Ratings.

[3] All coverage numbers as of March 2021.

For more information on some of data and tools discussed in this Case Study.

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