By Tim McPeak
As loan-loss rates continue to fall from their 2013 levels, financial institutions can be caught in a tough place when it comes to their allowance for loan and lease losses, or ALLL. That’s because regulators protecting the safety and soundness of a bank may advocate for steady allowances to cover credit losses. At the same time, improving credit quality is putting downward pressure on the quantitative, or calculated, portion of reserve levels.
Qualitative or environmental factors, also known as Q factors, are the primary lever for banks to alter their ALLL assumptions beyond the quantitative portion. Q factors allow for adjustments to the historical-loss experience to reflect losses embedded in the portfolio that have not been captured in charge-offs and recoveries.
But because of the recent dynamic in historical losses, some community banks are relying on Q factors for a larger percentage of their reserve.
Here are four tips for justifying Q factors:
Use recommended factors. Consider using the factors already outlined or mentioned in the 2006 Interagency Policy Statement. Recommended factors include underwriting standards and collections, recovery and charge-off practices, as well as experience and ability of lending management. They also include external factors such as regional or local economic conditions, and the effect of competitive, legal or regulatory issues on credit losses. Some institutions also have factors specific to their exposure to a particular industry, collateral or loan type.
Use a qualitative scoring matrix. Quantify how much the factors have changed since the previous calculation. This involves listing the risk factors, noting how each factor has changed and making an adjustment based on that change. It’s helpful to document why the specific adjustments make sense, either from a historical perspective or some other logic.
Use management committees or surveys. Assess how conditions have changed as they relate to qualitative factors through periodic meetings of management across the institution or through surveys that generate a rough scorecard for changes in internal or external factors. These assessments help put numbers to a subjective process and can span credit, financial reporting, risk and accounting, thus helping to align the view across many areas of an institution.
Use statistical analysis. Identify or calculate correlations between external variables, such as Gross Domestic Product or another economic metric, and portfolio losses. This often involves regression analysis or other techniques, and it can be great if correlations are clear. However, don’t chase “a needle in a haystack” if the link is unclear, and understand that using statistical analysis to link losses and factors can limit a bank’s discretion in the future if numbers change.
By following some of these best practices, community banks may find that the inherently subjective Q factors are more defensible with regulators and auditors.
Tim McPeak ([email protected]) is an executive risk management consultant with Sageworks Inc., a financial information company in Raleigh, N.C.