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Justifying your ALLL in a period of low historical losses

August 20, 2014
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A common concern among banks recently is how to correctly implement loss methodologies in a period of low historical losses. While it’s a relatively good problem to have, it nonetheless imposes challenges in the calculation of the ALLL. If there are few reference points, how then, does a bank go about calculating an accurate measure for loss?

Spoiler alert – there is no one right answer to this question. Rather, there are several measures an institution can take to ensure it remains compliant and has a methodology that’s defensible and justifiable in the eyes of examiners. This article highlights a few of those measures.

The first step an institution should take is to consider their reference points (past loss data) and judge if the bank has enough “substance” to defend their calculation. Despite fewer loan losses, if the methodology is quantifiable and verifiable, that alone should suffice. In other words, if the loan portfolio has experienced a very low level of loss and the ALLL is representative of current conditions, it simply “is what it is.” For smaller portfolios or de novo banks, peer data can bridge the gap. For midsized and larger institutions, however, peer data is almost always considered to be less appropriate.

That said, anomalies (like timeframes of zero losses) do occur, so the bank can look at the parameters of that loss history to see if adjustments are required. One option to mitigate the risk of such anomalies is to examine and potentially expand loss horizons. While an institution may experience little to no losses in a short window, lengthening the timeframe is usually sufficient to eradicate outliers and provide a more accurate measure of loss. Typical timeframes average 2-3 years, but it is not uncommon to go outside of that scope in situations where the bank does not think the horizon is representative of future losses. For example, data from only 2007-2008 would not be appropriate for calculating loan loss reserves for Q1 2009.

Low loan losses pose an interesting challenge for determining the value of qualitative factors in the ALLL calculation. If an institution uses Q factors to maintain a rather high reserve, it may be better prepared to mitigate future losses; however, if credit quality does deteriorate across the board, examiners might argue there should be a rise in Q factor adjustments to reflect the change in economic conditions. If that happened, the Loan Loss Reserve may rise to inefficient levels. This webinar and this whitepaper discuss how to justify Q factors in periods of low loss.

On the opposite end of the spectrum, if an institution releases reserves, any future event causing a provision to the ALLL will force the bank to borrow from shareholders in the form of net income and dividends. This seemingly puts banks in a catch 22 – if they maintain a high reserve, they will have a hard time keeping that figure consistent if a future deterioration were to occur, but if they release reserves in times of economic soundness, they may have to take money back from shareholders when the landscape worsens, which is seldom met with enthusiasm. 

Outside of loss horizons and Q factors, in a period of low losses, or upon the request to release reserves, regulators will undoubtedly examine the credit review process to determine if the request is substantiated and merited. As such, it is imperative to make sure the methodology surrounding this process is sound. If risk ratings have been adjusted correctly, then there should be no need to alter assumptions. An institution may risk a bad exam, however, if it cannot justify that the risk landscape has not changed or does not have quantifiable and verifiable evidence that its end number is sound.

All things considered, banks must walk a fine line when determining their loan loss reserve and the extent to which they will utilize qualitative factor adjustments in the calculation. In times of low losses, institutions may wish to bolster documentation with peer data or expand loss horizons to get a more substantive pool of data. They should examine their credit review process to ensure risk ratings accurately reflect portfolio performance and thoroughly document and justify their methodology. If all of these practices are sound, then the bank should be well-prepared to defend its calculation come exam time.

The above content focused on ways to tweak the historical loss method for calculating the ALLL. Institutions with asset sizes exceeding $350 million that perform migration analysis will be better suited to defend their calculation and will have better insight into the performance of their portfolio. There are pros and cons to this methodology, but as a whole it is a more robust calculation and readies banks for impending changes, such as the FASB’s CECL. For those interested in exploring this methodology, access our whitepaper, Migration Analysis: The Way Forward for an Effective ALLL.

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