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by Lara Hartin, Ardmore Board Member & Executive VP of Standards & QC

Leveraging credit data analytics when creating portfolio samples for loan review and further portfolio analysis is a growing trend in the industry today. Banks of all sizes are adopting the use of credit analytics to create risk-based loan review exams to maximize the value of loan review for their institution. The process typically involves using relatively standard credit metrics and data management techniques to pinpoint areas of growing and emerging risk in the bank’s portfolios.

It is common today for banks to use report writing software to “slice and dice” borrower and loan credit data for management and board reporting. Concentrations are identified and tracked based on common credit risk identifiers such as CRE property type, or loan type (C&I or Mortgage, for example). Within these areas credit risk analysts look at trends for loan growth, deterioration of key ratios including LTV and DSCR, interest rates, and risk rating changes. This type of analysis informs the credit risk analyst important information about the state of the portfolio today as well as trends relating to what may be happening over time.

Typically, when Loan Review Department managers pull a sample for an exam, they look at creating a sample across multiple categories of loans that appear to represent the riskiest and largest loans in the portfolio (or of the segment of the portfolio being reviewed). Typical loan review sample categories include largest relationships, watch and worse risk ratings, insider borrowing (“Reg O”) and loans booked recently. An unintended result of this type of exam is that scoping and sampling very often produces many of the same loans repeatedly in multiple reviews. While this has merit for following credit monitoring, the sample could be improved with analytical risk-based analysis. The traditional method of sampling does not necessarily highlight emerging risks, or the impact on the portfolio of changes in lending practices or current economic conditions.

By employing common credit risk analytic techniques for concentration management, portfolio stress testing and analysis of key financial ratios when creating the loan review sample, bank loan review departments can bring more value to bank management and more advanced control of emerging risks. For example, shocking the portfolio interest rates or appraisal values can identify specific concentration segments that are more vulnerable to risk. Similarly by analyzing portfolio trends for segment growth or even the increasing number of policy exceptions, loan review teams can act proactively to identify possible pockets of emerging risk.

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