Featured Product

    Case Study: Allowance Impact of COVID-19 on C&I, CRE, and Retail Portfolios under CECL

    April 2020

    Case Study: Allowance Impact of COVID-19 on C&I, CRE, and Retail Portfolios under CECL

    COVID-19 has caused unprecedented economic disruption across all sectors. Many people have lost their jobs, and institutions of all sizes are running into liquidity constraints. Small businesses and commercial real estate have been hit hard; sheltering-in-place has kept these firms from operating unless they are classified as essential business. Various economic outlooks are projecting a fast track into a recession despite the Federal Reserve committing to provide all the support and tools at its disposal to stabilize the market. On March 25, the Senate and the Trump administration agreed on a historic $2.2 trillion stimulus package that offers both businesses and individuals tangible financial support to prevent credit and liquidity events. The package may not slow the spread of COVID-19 but is expected to help alleviate this unique financial situation.

    With this unprecedented event, the biggest question is the impact of COVID-19 on the allowance level under CECL. How does the pandemic affect CECL estimates, and what is the impact? How do businesses account for rapidly changing economic conditions and financial assistance? Is the impact different across asset classes and regions?

    In this paper, we discuss our impact analysis performed on the CECL estimate of C&I, CRE, and retail portfolios due to COVID-19 through the latest economic scenarios. The focus of the discussion for each asset class will be around:

    » Key economic variables for each asset class
    » The overall impact of COVID-19 compared with the loss level expected before the pandemic on January 1, 2020
    » Specific sectors, loan types, or product types more greatly affected within the asset class

    Given that market conditions and the economic outlook are changing constantly, it is also important to examine how to appropriately interpret quantitative results based on the best available scenarios and account for any gaps in the qualitative process to arrive at the final estimate.

    Related Solutions

    Moody’s Analytics provides tools for the most crucial aspects of the expected loss impairment model, with robust solutions to aggregate data, calculate expected credit losses, and derive and report provisions.

    Moody’s Analytics helps financial institutions develop collaborative, auditable, repeatable, and transparent stress testing programs to meet regulatory demands.