Accountants serving U.S. banks and credit unions are bracing for the impact that the current expected credit loss model may have on the institutions’ allowance for loan and lease losses and capital levels, and these institutions are enacting transition plans now.
There are several imperative areas through which an accountant can guide the institution, and the first area is typically data. Specifically, a primary step includes making sure the institution is clear on what types of data will be needed, what systems will be required and how much of that data needs to be collected and analyzed. Loan-level information will be necessary for CECL — a big change for many financial institutions, who may only archive pool-level data in current practices.
Interagency guidance on CECL that was issued Dec. 19, 2016, described the requirements this way: "Specifically with regard to data, to implement CECL, an institution should collect and maintain relevant data to support its estimates of lifetime expected credit losses in a way that aligns with the method or methods it will use to estimate its allowances for credit losses. As such, the agencies encourage institutions to discuss the availability of historical loss data internally and with their core loan service providers because system changes related to the collection and retention of data may be warranted. Depending on the estimation method or methods selected, institutions may need to capture additional data and retain data longer than they have in the past on loans that have been paid off or charged off to implement CECL."
With this in mind, three data quality considerations that management at your client institutions will need to understand are:
The CECL guidance is intentionally non-prescriptive, meaning institutions will have some flexibility in deciding which methodology or methodologies work best for their portfolio or segments of their portfolio. However, to ensure flexibility in selecting appropriate methodologies, it is important for banks to capture a wide range of data points. Certain data points might be useful for utilizing one methodology but not another. For example, individual loan origination amounts might be useful when applying vintage analysis, while individual loan risk classification would be needed for migration analysis. Some data points, such as individual loan charge-offs, individual loan recoveries and individual loan duration, could be used for multiple methodologies. If data is inadequate at present, identify a timeframe required for collecting sufficient data to be able to defend the election of a specific methodology.
It is possible the bank stores loan data in different places — mortgages in one system, auto loans in another, etc. What data has been tested or historically reconciled to make sure that inconsistencies across the systems do not cause problems? Is there a report writer in place to draw this loan-level data into a single calculation?
What controls are in place to ensure the data can be relied upon, is updated frequently enough to accommodate bank needs, and is secure? Data should be backed up frequently and have redundancy to minimize risk. While most institutions, when asked, say their data is in good shape for CECL, according to a poll by Sageworks, which is offering a CECL Prep Kit, changes to data collection and storage are needed on a go forward basis.
In order to have sufficient data to produce lifetime estimates under certain methodologies, more historical data will be needed, so the sooner the data is identified and collected, the more complete it will be.