How to prepare now for FASB’s CECL model: Part I
**Please check our most recent blog post regarding the latest changes to the FASB deadlines.**
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 controversy, as institutions recognized the potential of an 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.
Improving Data Collection
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.
