CECL-ALM
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Wilary Winn offers Concentration Risk Analyses.

Excessive concentrations in type of assets or liabilities can lead to credit, interest rate and liquidity risk. We believe that of the three, credit risk is the most critical because losses incurred on loans and investments have been key factors in banking crises and failures. As we analyze loan portfolios, we are not addressing the traditional concentration risk arising from large loans to a few borrowers. We are instead addressing the risk that “pools of individual transactions could perform similarly because of a common characteristic or common sensitivity to economic, financial or business developments.”[1]

We first perform data mining to identify concentrations in investments, loans, and deposits, recognizing that the risk can arise from different areas and can be interrelated. For example, if a financial institution had an indirect auto loan portfolio sourced from a limited number of dealers, understanding the percentage of the portfolio arising from each dealer and their relative credit performance (FICO and delinquency) would be important in understanding and managing credit risk. As another example, if a financial institution had a concentration of residential real estate loans, it would be vulnerable to a downturn in real estate prices in a specific geographic area. Interrelated risks are exemplified in an institution with a concentration of long-term residential real estate loans and a relatively large portfolio of agency mortgage-backed securities. It would incur credit risk from the loans and heightened interest rate risk from the combination of the loans and the securities. 

We collaborate with our clients to identify concentrations, then develop critical input assumptions. This includes determining base case prepayment or conditional repayment rate (CRR), conditional default rate (CDR), and loss severity assumptions. We note that our base case results are fully compliant with the current expected credit loss (CECL) model.

After this, we work with our clients to develop stress test inputs tailored to their specific situation. Examples include an unemployment rate increase with a resulting increase in defaults on auto loans, or an increase in long-term interest rates, slowing expected repayment rates in the financial institution’s real estate portfolio.

We then perform stress testing on the financial institution’s level of capital. Our stress tests address credit, interest rate, and liquidity risks separately and on an integrated basis. Based on the stress test findings, we work with our client to refine their concentration risk limits. This could, for example, involve creating sub-limits based upon credit attributes for certain loan categories.

Sources:

[1] OCC Comptrollers Handbook – Concentration Risks