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Obtaining loan portfolio information for ALLL calculations

October 9, 2013
Read Time: 0 min

Obtaining loan portfolio information and keeping this data updated can be both time consuming and difficult, but the information is very important to a bank’s Allowance for Loan and Lease Losses (ALLL) calculation. The amount of data available in an institution’s loan processing or core system that can be utilized for the allowance can be quite comprehensive; however, it can be difficult to extract the data for the allowance unless the process is automated. 

Loan portfolio data needed for the ALLL can be categorized as either portfolio-level or loan-level information. 

Types of portfolio-level data needed: 

Data segmented into homogeneous pools – for reporting and FAS 5 calculations

Appropriate loan balances identified for each pool (monthly and quarterly)

FAS 114 and FAS 5 loans identified from each pool

Data sub-segmented for risk level, risk rating, or delinquency, if appropriate for the portfolio 

Having access to this data from the institution’s loan processing system helps streamline and reduce error in many processes of the ALLL calculation. For example, guidance requires a bank to reconcile to the general ledger before performing and documenting the reserve calculation. In the following example, each portfolio concentration (defined by product code) shows the respective loan balance and reserve amounts. 

Loan-level data needed: For each borrower of the bank, the ALLL may require the following data points: 

Loan number Payment Type Payment delinquencies
Amortization days LTV percentage Accrued interest
Current loan balance Monthly payment Unamortized premiums 
Origination date Interest rate Net deferred fees/costs
Loan officer Remaining term Government guarantees
Maturity date TDR Status  Guaranteed percentage
Risk Rating Nonaccrual Status Guaranteed Amount

Not all of these data points will be essential for all loans, but the more data available, the easier it will be to calculate the reserve and to report on it. Other data items besides those listed above can also be utilized in effective reporting on the allowance to various constituencies.

In terms of data collection and analysis, a significant amount of time and attention are required to classify the bank’s loans into ether the FAS 114 or FAS 5 buckets. Having access to pertinent loan-level data and documenting why certain loans were identified in either bucket will increase the defensibility of the institution’s overall ALLL approach. 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, FAS 5 calculations will become less burdensome if loan-level data can be aggregated by pool and easily updated.

Learn more about how to best collect the data that drives the ALLL by downloading the whitepaper, Compiling the best data for the reserve calculation.  

About the Author


Raleigh, N.C.-based Sageworks, a leading provider of lending, credit risk, and portfolio risk software that enables banks and credit unions to efficiently grow and improve the borrower experience, was founded in 1998. Using its platform, Sageworks analyzed over 11.5 million loans, aggregated the corresponding loan data, and created the largest

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