Liquidity Risk Modeling

Liquidity risk is another "hot button" topic of examiners these days. In particular, there is strong interest in how banks of all sizes perceive their liquidity changing when interest rates rise. This question is not so much about any immediate expectations, but, as in the case of Interest Rate Risk analyses, examiners seem to want to make sure that bankers are aware of possible events that could easily occur, and have gone through the "what if" thought exercises so they are more prepared to react when significant events do occur.

Our model for simply getting an initial understanding of a bank's liquidity risk is a simple and well known one: since understanding liquidity risk revolves around the case of "something bad" occurring that motivates a bank to conserve capital and ride out a (proverbial) storm, we analyze the case for a bank's portfolio in which no new investments are made over a relatively long period of time. As new instruments mature, they are not renewed. This policy builds a war chest of immediately available capital which, in conjunction with a bank's lines of credit, is the theoretical best situation that a bank can be in when preserving its solvency.

This provides a "snapshot" of what might happen to a bank under undesirable circumstances. But while a picture may be worth a thousand words, it is only part of the story. The problem comes in understanding how the results that are captured in this picture can be leveraged in a real-world situation when absolute policies cannot always be adhered to. To survive an actual crisis, understanding the sensitivity of (in this case) the bank's liquidity to each of the key factors involved will provide extremely useful guidance in how to make day-to-day decisions in the real world.

Based on this understanding, Capitalytics provides several other similar scenarios that you can use to help your bank capture its sensitivity to different factors when stressed. For instance, not only do we provide a "one click" option to model new investments at 0% of their forecast levels, we also allow you to see how your bank's liquidity changes as new investments are stepped down from 100% to 90%, 75%, 50%, and 25% (and ultimately 0%) of forecast values.

This, however, is still not the entire story. From the point of view of a liquidity risk model, there are two factors that can affect a bank's liquidity: the bank's outflow of funds to investments, and its (difficult-to-control) outflow of deposit funds. To allow you to understand your bank's sensitivity to these withdrawals, Capitalytics has implemented additional scenarios to model increased withdrawal rates (where our deposit & withdrawal policies are discussed here). We have preconfigured simulations that increase withdrawals by 25%, 50%, 75%, 100%, 200%, and 300%. Furthermore, in a time of crisis, uninsured deposits will likely be withdrawn faster than insured deposits; as a result, we have provided the parameters for scaling both total withdrawals and uninsured withdrawals separately.

While we have gone to great lengths to provide a robust set of tools to help you understand your bank's liquidity, we realize that every case is different and we are glad to help with your bank's specific needs. Contact us today to discuss how Capitalytics can help your bank.