Study finds ESG helps differentiate companies with good and poor credit scores

Christoph Klein

A study has found environmental, social and governance (ESG) factors help distinguish between companies with good and poor credit scores, further highlighting the importance of considering ESG metrics when assessing credit ratings.

The study, entitled Quantitative Credit Rating Models including ESG factors, used a quantitative model to assess the impact of ESG on credit scores.

The issue around how ESG impacts credit scores has received increased attention in recent years driven in part by the UN Principles for Responsible Investing (PRI).

The PRI launched The ESG in Credit Risk and Ratings Initiative in 2016 with a view to seeing credit ratings agencies take into account ESG factors when rating a company’s credit.

Although there has been a significant improvement from the credit rating agencies, PRI’s fixed income head Carmen Nuzzo told ETF Stream more work is needed to be done.

Christoph Klein (pictured), managing partner and portfolio manager at asset manager ESG Portfolio Management and author of the study, commented: “In practice, an increasing number of investment managers and banks are including ESG considerations in their investment and lending process, as models and processes implementing ESG considerations and factors have led to increased risk-adjusted returns.

“In addition, credit rating agencies are increasingly granulating ESG factors in their credit rating process.”

Study finds poor ESG performance leads to increased credit risk

The study by Klein looked at companies in the industrial sector using a quantitative model to assess the impact of ESG on credit scores.

Using Bloomberg and MSCI ESG data, Klein took 21 credit ratios and ESG factors into account such as a company’s ESG environment score, its ESG rating and female directors in percentage and then split the companies between issuers with a good credit score, rated AAA to BBB+, and a poor score, rated BBB to B.

These companies were assessed through Klein’s “discriminant function”, a model which calculates whether an issuer is either solvent with good credit quality or insolvent.

This calculation is done by selecting factors that are relevant to a company’s chances of insolvency such as retained earnings, market cap and carbon emissions.

In the study, the discriminant function delivered a hit ratio of 84.6% meaning it correctly incorrectly classified a company’s credit quality just 15.4% of the time.

When using the same data set without the inclusion of ESG factors, Klein found the discriminant function delivered a hit ratio of 84.2%, 0.4 percentage points lower.

ESG is a data miners’ dream

Klein commented: “Our results suggest that the inclusion of ESG factors does improve the discriminating power of quantitative rating models.

“This statistical outcome increases our conviction that ESG is relevant for credit assessments and motivates us to increase our active engagement to improve the ESG quality…of issuers we invest in.”

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