Compliance

02:41 PM
Regan Camp and Ed Bayer, Sageworks
Regan Camp and Ed Bayer, Sageworks
Commentary
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The Pros and Cons of Migration Analysis

Migration analysis is a rigorous analytical process recommended by the regulatory agencies; yet it is underutilized

Since January 2009, a total of 427 banks have failed in the U.S. As the global economic crisis drug on, these institutions were ill-prepared to absorb the volume of loan and lease losses they were forced to recognize. Consequently, regulatory agencies have increased pressure on the surviving institutions to appropriately calculate adequate Allowances for Loan and Lease Losses (ALLL).

Specifically, determining the most appropriate ALLL methodology is a significant challenge institutions face in calculating an adequate allowance. While regulatory guidance is scarce, latitude is given to each institution to select the valuation methodology best suited for its own unique characteristics and complexities. According to the Office of the Comptroller of the Currency (OCC), many methodologies, including both historical loss and migration analysis techniques, are accepted.

Migration analysis is a rigorous analytical process recommended by the regulatory agencies to determine financial institutions’ ALLL; yet it is underutilized. This type of analysis uses loan level attributes to track the movement of loans through the various loan classifications in order to estimate the percentage of losses likely to be incurred in a financial institution’s current portfolio. The purpose of migration analysis is to determine what rate of loss an institution has incurred on similarly criticized or past due loans. This purpose is the same as that of historical loss rate analysis, but it is more granular and therefore can give a truer reflection of the losses inherent in the current portfolio. For proper application, migration analysis requires extensive data collection and consistent, prudent risk rating methodology.

Over time, information systems have changed exponentially due to numerous advancements in technology. Cloud computing, dynamic coding, and web-based platforms are just a few examples that have had a profound impact on information systems. Yet, despite these advancements, the movement towards more sophisticated calculations of ALLL provisions has actually diminished due to heavy reliance on Microsoft Excel, a relatively weak and error-prone platform that is less conducive to the complex nature of migration analysis. Whether through lack of knowledge or fear of change, many financial institutions have not taken advantage of evolving information systems’ capabilities that make it possible for mid-sized and large banks to use migration analysis to determine their ALLL provisions.

Migration analysis is not a process that fits for all institutions. There are several elements involved in a true migration analysis, and they typically require a considerable amount of personnel, IT, and data resources. If institutions don’t have the resources available, they may not be able to accurately execute this more complex approach.

Additionally, for proper loan portfolio analysis using the migration technique, loan portfolios should be first broken down into homogenous pools by similar attributes (Federal Call Codes, geographic similarities, loan types, etc.) and then further broken down by risk classification (Pass, Special Mention, Substandard, Doubtful) or delinquency ranges (0-29, 30-59, 60-89, 90+). When broken down to this extent, an institution with a smaller loan portfolio may have inadequate sample sizes to average out any anomalies that may be in each loan bucket. That can distort calculated rates, thus failing to provide a proper ALLL provision. Often, it may be more appropriate for these smaller institutions to use the more common historical loss rate method.

Access to historical data often presents barriers to the migration analysis method. The results of a migration analysis rely heavily on high-quality historical data, an accurate historical loan risk rating system, and other sound internal practices.

If a bank has the available resources, migration analysis provides a more accurate picture of how an existing portfolio would migrate to loss. Furthermore, as Neal Brauner of Financial Services Advisory Partners, LLC notes, “Loan migrations across risk grades give insight into portfolio loss characteristics and can drive pro forma projections.”

Though some financial institutions are fearful that migration analysis will increase a bank’s current ALLL provisions, a proper analysis helps ensure adequate reserves. The OCC stated in March 1997, “An understated ALLL expense will overstate the bank’s earnings and can result in the violation of law.” If falsely calculated, whether through mal intent, negligence, or error, the ALLL provision can have profound implications upon the bank’s good standing and reputation in the eyes of public opinion and the law.

On the other hand, when circumstances dictate a decrease in provisions, migration analysis is the most quantitatively rigorous and accurate method to justify such a decrease. The migration method accounts for changes in composition of the credit portfolio and credit quality deterioration. Its sophistication and accuracy reduces the risk of regulatory criticism following a decrease in provisions.

Migration analysis adjusts the ALLL provision to reflect the conditions of the current portfolio, while the historical loss rate method has no impact and ignores the new circumstances of our loan portfolio.

With the advancements in cloud computing and the continual development of web-based platforms, secure Software as a Service (SaaS) applications allow financial institutions to perform migration analysis accurately without the limitations of a bank’s information system, the previous high labor requirement, and the potential for user error tied to manual entry. Migration analysis is a technique that institutions should consider integrating into their ALLL methodology to provide the most accurate ALLL provision calculations.

Ed Bayer and Regan Camp are Risk Management Consultants at Sageworks, a financial information company that provides risk management solutions to banks and financial institutions.

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