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An Investment Manager Streamlines the Evaluation of Credit Risk

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An Investment Manager Streamlines the Evaluation of Credit Risk

Highlights

The investment team’s risk management processes lacked depth and consistency. New data and analytical tools were needed to effectively address today’s market uncertainties.

Global inflation, continued supply chain issues and a war between Russia and the Ukraine are just a few of the issues challenging investment managers in APAC and around the world. Commercial real estate (CRE) is particularly vulnerable coming off the negative impacts of the COVID-19 pandemic. On the office side alone, a new equilibrium has yet to emerge given the adoption of the hybrid work model. Landlords are contending with higher vacancy rates, lower rent and lower values over the next few years - and the growing chance of recession adds to the downside risk.[1] Having a rigorous system in place to assess risks to CRE assets is more important than ever before.

This firm is a leading private markets finance and investment house providing capital solutions for property owners and developers, plus investment opportunities for co-investors. The firm has the majority of its funds in a property portfolio, and a smaller portion in a corporate lending portfolio. For property, members of the investment team are charged with evaluating the possibility that borrowers could fail to pay the interest and/or principal on their CRE loans. For corporate lending, they need to evaluate the possibility that a company could default. The team's current risk management practices lacked depth and consistency and needed to be substantially enhanced given today's uncertain market conditions.

Pain Points

The firm's current approach to risk management needed to be upgraded with data and analytical tools that would enable members of the investment team to obtain:

  • A granular, consistent and transparent framework for the measurement and assessment of loan credit risk.
  • A quantitative approach to evaluate the probability of default (PD) for rated and unrated, public and private companies in the corporate lending portfolio.
  • An early-warning system to quickly see any deterioration in a company's credit quality.
  • The ability to streamline workflows to increase efficiencies.
  • Flexible delivery options to easily integrate data with internal applications.

A relatively new member of the team had been using credit risk management solutions from S&P Global Market Intelligence (“Market Intelligence”) at his previous position and encouraged other members to learn more.  

The Solution

Specialists from Market Intelligence first suggested that the investment team use the proprietary CRE Scoring Tool (CREST) that leverages a scorecard approach to measure and assess loan credit risk. Scorecards provide an easy-to-use, logical quantitative and qualitative rules-based approach, with 75% of outputs being within one notch of public credit ratings. The approach is especially useful for low-default portfolios that, by definition, lack the extensive internal default data necessary for the construction of statistical models.

This could then be complemented with the proprietary Credit Analytics solution that blends cutting-edge models with robust data to help users easily monitor the creditworthiness of companies in their portfolios. The Credit Analytics suite of models includes Probability of Default Fundamental Model (PDFN), CreditModelTM and PD Market 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.

The combined solutions would also enable members of the investment team to assess the credit quality of the builders themselves and any follow-on impact on the property construction risk for the project that the team is financing. The scorecard provides the ability to assess property-related creditworthiness that includes the roles and responsibilities of the builder in the construction phase, while Credit Analytics provides the ability to form a view of the default risk of builders. This links the impact of builder default risk to the real estate asset analysis.

This combined solution set would provide the data and analytical tools needed to quickly identify any emerging problems within the property and corporate lending portfolios. It would also help the investment team better understand the various factors that contribute to increased risks and a change in creditworthiness. The team would be well positioned to:

Stay on top of CRE portfolio risk

CREST provides a granular, objective, consistent and transparent framework for the measurement and assessment of loan credit risk, helping to meet risk management objectives. It facilitates multiple business applications, including loan origination and surveillance, credit pricing and portfolio management.

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 REITS. PDs can be mapped to quantitatively derived credit scores[2] (i.e., ‘bbb’) for increased comparability. Workflows are optimized by accessing a pre-scored database leveraging comprehensive and timely data on 50+ million[3] 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, 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 58,000+ pre-scored entities, going back more than 15 years.

Create an early warning system

PDMS is a statistical model that evaluates credit default swap spreads to provide an early warning of potential credit changes, capturing the market’s daily view about a company’s perceived risk.

Streamline workflows

Solutions are available on the S&P Capital IQ Pro platform, a one-stop solution for essential intelligence, offering unrivaled data, tech-forward productivity tools, news and research. An Excel Add-in and suite of office tools seamlessly powers proprietary models and streamlines presentations. Users can access a library of hundreds of ready-to-use models and templates, or partner with Market Intelligence’s support analysts to build their own. It is possible to integrate data from Excel into PowerPoint or Word with fewer errors and refresh formulas in Excel with just one click.

Choose from multiple data delivery options

Flexible access via an API efficiently delivers data to internal systems. Data feeds and access via a cloud-based solution are also available.

Key Benefits

Members of the credit risk team subscribed to these offerings and were able to leverage Market Intelligence’s subject matter expertise in credit risk assessment, time-tested models, sector-specific experience and technological innovation to improve the firm's credit risk assessment process. The solution set provides the automated monitoring and alerting system team members need to help minimize any negative impacts to their portfolios, and they value having:

  • An objective and consistent framework for the measurement and assessment of loan credit risk.
  • A scorecard that links empirical default and recovery rates to key explanatory variables at both the property/loan level and market level.
  • Analytical transparency of the methodology that is supported by granular scoring criteria and extensive user and technical documentation.
  • Outputs (credit scores) that are mapped to S&P Global Market Intelligence's PDs and broadly align with credit ratings issued by S&P Global Ratings.
  • The ability to make adjustments to the financial and macroeconomic inputs according to their own perceptions of risk.
  • Product training to help support the successful adoption of Credit Analytics and provide insight on the model methodology, features, functionality and how to interpret the results.
  • An efficient and easy-to-use approach with broad coverage of companies and geographies, given the exposure to multiple countries and industries.
  • Flexible product delivery channels supporting automation and the quick integration of credit risk models into their risk management framework.
  • Additional time for customer-facing activities because the maintenance of the Credit Analytics models is managed by Market Intelligence.

Click here to learn more about S&P Global Market Intelligence's Credit Analytics solution, and click here to learn more about Credit Assessments Scorecards.

 


[1] "Property In Transition: Slowing Economies and Shrinking Demand Pressure the Credit Outlook for Office Landlords", S&P Global Ratings, September 12, 2022, www.spglobal.com/ratings/en/research/articles/220912-property-in-transition-slowing-economies-and-shrinking-demand-pressure-the-credit-outlook-for-office-landlor-12494303.

[2] S&P Global Ratings does not contribute to or participate in the creation of credit scores generated by Market Intelligence. Lowercase nomenclature is used to differentiate S&P Global Market Intelligence credit model scores from the credit ratings issued by S&P Global Ratings.

[3] All coverage numbers as of January 2022.

Learn more about Credit Analytics
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Learn more about Credit Assessment Scorecards
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