Assessing and incorporating credit default risk analytics into investment analysis

By David Croen, Enterprise Data, Risk and Entities, Bloomberg L.P.

Since the financial crisis of 2008, financial services firms have advanced their internal credit risk management capabilities as part of a substantial evolution in risk management among regulators, accountants and asset managers, whose views on risk management approaches have converged over time. Regulators and accounting standard bodies expect that asset managers have controls and processes in place to identify, assess, monitor, and control risks – particularly credit risks.

Worldwide, regulators have significantly increased risk management needs and capital requirements for regulated financial services entities. For example, the Basel Committee on Banking Supervision made sweeping changes to capital requirements with the issuance of Basel III in late 2010, to strengthen microprudential regulation and supervision, and add a macroprudential overlay that included additional capital buffers. EU and U.S. regulators have also strengthened their oversight of asset managers (e.g. European Securities and Markets Authority’s Regulation 462/2013 on Credit Rating Agencies).

Accounting standards have also adapted to incorporate quantitative credit analytics into accounting requirements and disclosures (e.g. the International Accounting Standards Board’s Financial Instruments standard (IFRS 9) and the Financial Accounting Standards Board’s Current Expected Credit Loss standard (CECL)).  In an effort to meet the needs of investors, accountants and regulators, and to move beyond the use of credit agencies’ ratings, asset managers have developed industry-wide best practices (e.g. President’s Working Group on Financial Markets – Asset Managers’ Committee), with a focus on credit and counterparty risk management.

Asset managers have felt compelled not only by regulators, but by investors and internal risk management imperatives to evolve credit management policies and practices beyond the use of credit agencies’ ratings. However, while regulators have moved asset managers toward enhanced risk management capabilities, regulators have not been as prescriptive about implementation. As asset managers have developed comprehensive frameworks addressing risk management, they have filled the implementation void by developing and employing market-based credit analytics.

Why use market-based credit analytics?

Market-based credit analytics incorporate current market and financial information about an issuer that enables forward-looking analysis of an entity’s probability of default over various timeframes, and the potential expected loss in case of default, as well as analysis of various credit metrics that can be used to evaluate the issuer’s credit quality and make comparisons to other entities. By comparison, a ratings agency credit rating evaluates the relative creditworthiness of an entity, using historical information, which is updated periodically, and which does not indicate either the probability of default or the expected loss in case of default.

There are many advantages to using market-based credit analytics over ratings agency measures, including transparency (for methodologies, inputs and assumptions), flexibility (in changing inputs and assumptions), and reporting and disclosure (automation, daily reporting and aggregation for stakeholder disclosures). The upcoming need to comply with accounting requirements such as IASB IFRS 9 and FASB CECL means the use of combined metrics with transparency becomes imperative as asset managers and others will be required to account for the deterioration of the credit strength of issuers of securities held.  These organizations will have to realize credit impairments on their balance sheets, and regularly update these reports (with the expectation that many firms will move to daily updates).

These new accounting standards will lead to important new insights into credit risk and performance; not only will that increased transparency lead to greater risk management demands, but the potential for ‘write downs’ of investment value and the need for greater provisions could have a direct impact on the organization’s capital requirements and funding strategy. Therefore, the CFO and CEO are becoming more sensitive to the overall effectiveness of trading and risk management strategies.

For a real-life example, during 2017, U.S. retail firms experienced among the highest level of default and store closings (7,795 retail stores closed; 50% of these were from six chains, including Radio Shack, Payless, Rite Aid, Ascena, rue21 and Sears) since the financial crisis.

In addition, a growing amount of retail debt matures over the next few years (a substantial amount of which is high yield), so it will continue to be important to carefully monitor and risk manage retail investments. Using market-based credit analytics can help illuminate and quantify the risks, enabling better analytics and risk management.

How can firms effectively and efficiently use market-based credit analytics?

To meet these complex needs, many investors are using objective, market-based analytics that aid assessment, and also provide pricing and risk insights.

Bloomberg’s credit risk function, DRSK, analyzes the credit health of a company by estimating the default probabilities over the next year, as well as other key tenors, so you can quickly determine the credit health of a given company. DRSK provides timely information that reflects current market realities, transparency into the drivers of default probability. Currently, DRSK covers over 40,000 public companies and around 300,000 private companies globally, and new ones continue to be added.