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Compliance

11:25 AM
Tim McPeak and Ed Bayer, Sageworks
Tim McPeak and Ed Bayer, Sageworks
Commentary
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How To Prepare Now for FASB’s CECL Model

The coming implementation of the Financial Accounting Standard Board’s Current Expected Credit Loss model requires banks to think ahead about how they collect and manage data regarding their loan portfolios.

The December 2012 issuance of the Financial Accounting Standard Board’s (FASB) latest proposal brought about the Current Expected Credit Loss (CECL) model. With it came a number of changes and controversies, as institutions recognized the potential of increase in allowance levels as a result of the changes to how losses are estimated. Despite the uncertainty surrounding the final model and associated implementation timeline, there are several steps institutions can take now to prepare for the proposed changes.

One way that institutions can start preparing now is to improve their data collection. No matter the final details of the new guidance, institutions will need more robust data on their loan portfolios, borrowers and external economic factors to make supportable estimates of credit losses going forward. And, institutions can begin gathering that data now to ensure access to the right data and to establish processes to collect information on an ongoing basis.

Specifically, if it isn’t already being captured, loan-level data like historical balances, risk ratings, charge-offs and recoveries should be collected. Additionally, other data that could be correlated to loan losses should be collected as well. Examples include national, regional and local economic data; borrower financial data and real estate metrics such as price indexes. At this stage, it is likely better to err on the side of too much information, as it may prevent hunting down historical data down the road.

As the new model considers the life of a loan in the portfolio, as well as booking a lifetime loss, it is imperative that financial institutions are able to determine—by a historical and data-driven analysis—the average life of a loan in a segment of the portfolio along with the expected loss. The more portfolio data collected, the more precisely institutions can calculate expected losses. More data will also enable institutions to better defend the calculation to examiners and auditors. Therefore, prudent institutions should begin improving data collection immediately.

A common obstacle faced by smaller financial institutions is the ability to improve and collect data in such a robust form. For institutions facing this obstacle, a common solution has been using a third party ALLL solution for assistance with the allowance for loan and lease losses calculation. An ancillary benefit of using software is its integration with the core system, which makes data available for a variety of multi-dimensional reports.

Capital Planning

Most analysts and bankers believe that the CECL model will increase an institution’s allowance reserve. According a poll conducted earlier this year by Sageworks, most bankers expect the increase to be 10–50 percent, requiring a one-time capital adjustment.

Several of the comment letters expressed concerns that this one-time adjustment would be required at the same time as the increases under Basel III. This was a valid concern, as most community banks would be severely strained by such capital adjustments occurring almost simultaneously.

However, the final Basel III guidance released in July 2013 included compromises for community banks, limiting the strain on their capital. Due to these concessions, the focus can be on the one-time adjustment for the ALLL once the new FASB guidance is released. Therefore, institutions should take proactive steps to increase capital in advance of the changes.

Model Flexibility

As current ALLL models are updated each month or quarter, institutions should consider the potential changes and try to make current models flexible enough to adapt. Spreadsheet-based models may need to be significantly reworked to accommodate the new guidance, so limiting hard-coded cells and maintaining clear documentation on the model will be critical. This is especially true when there has been turnover in staff, and the original author of the model is no longer with the institution. It may also be worthwhile to consider an automated ALLL solution ahead of any changes taking effect.

Tim McPeak is a senior risk management consultant and Ed Bayer is the managing director, financial institutions at Sageworks.

[Check out ways companies are Navigating the Big Spectrum of Big Data’s Solutions at Interop, which runs from September 30 through October 4 in NYC.]

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