As any banker knows, a financial institution’s allowance for loan and lease losses (ALLL) is under a spotlight during federal examinations. While the calculation can be complex and time-consuming, a recent Abrigo poll showed that the majority of banks and credit unions weren’t criticized for their loan loss reserve process in their most recent exam. Only 1 in 6 institutions responded that this area of the exam was troublesome, which is positive sign for the banking industry; doubly so as changes to the calculation are on the horizon with the implementation of CECL (as early as Q1 2020 for SEC registrants).
One critical component of the ALLL is data-gathering and documentation. The reserve is more than simply a calculation of funds, and a lack of or insufficient data and/or documentation is often a sore spot for many banks and credit unions. Whether an institution assesses the ALLL monthly or quarterly, collecting portfolio-level and loan-level data is often the most time-consuming aspect of the process, but a crucial one. The amount of data available in an institution’s loan processing or core system that can be utilized for the allowance is often quite comprehensive. Unfortunately, it can be difficult to extract in a timely manner unless the process is automated.
- Segmenting data into homogeneous pools for reporting and ASC 450-20 (FAS 5) calculations
- Identifying appropriate loan balances for each pool (monthly and quarterly)
- Identifying ASC 310-10-35 (FAS 114) and ASC 450-20 (FAS 5) loans from each pool
- Sub-segmenting data for risk level, risk rating, or delinquency, if appropriate for the portfolio
For each borrower of the financial institution, the allowance may require the following data points applicable to the loan-level bucket:
- Loan number
- Current loan balance
- Loan officer
- Risk rating
- Origination date
- TDR Status
- Nonaccrual status
Other data points may be necessary, but certainly not all of them will be essential for all loans. But a solid best practice is to gather as much data as available, making the reserve easier to calculate and report on.
In terms of data collection and analysis, a significant amount of time and attention are required to classify the institution’s loans into either the ASC 350-10-35 (FAS 114) or ASC 450-20 (FAS 5) pools. When assessing these loan buckets, having access to pertinent loan-level data helps to streamline the process. It’s also imperative at this point to document why certain loans were identified in either bucket, as it will increase the defensibility of the institution’s overall ALLL approach to examiners. In such instances when that explanation is called on, a loan’s risk rating, TDR status, nonaccrual status, payment delinquency, etc. are all measurable and valid objectives to incorporate into the loan classification process. Similarly, ASC 450-20 (FAS 5) calculations will become less burdensome if loan-level data can be aggregated by pool and easily updated.
An accurate and compliant reserve begins and ends with excellent data and documentation. As bankers and credit union professionals look toward the implementation of an expected credit loss model in the coming years, data and documentation will become all the more important for an institution’s success.
For more information on best practices for compiling data for the ALLL, download this complimentary whitepaper.