As noted throughout this “Introduction to ALM” blog series, a key aspect of asset/liability management (ALM) is managing assets and liabilities appropriately to generate and sustain margin. A lot of the time, this means securing funding through defined deposits and borrowings at prices and durations we can measure and predict. However, many institutions have available a natural hedge to changing interest rates: the non-maturity deposits (NMDs) they collect. These are the checking, savings, and money market accounts borrowers deposit into the institution.
ALM 101: Intro to Asset/Liability Management-Part 5: Non-Maturity Deposits
ALM & Non-Maturity Deposit Modeling: Assumptions on Key Funding Sources
Accurate assumptions are vital in non-maturity deposit modeling when using the funding source as a natural hedge to changing interest rates. This is the fifth post in a series.
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What makes these deposits different from other sources of funding is that there is no way to know for sure how long non-maturity deposits will be on the books or how the prices on these deposits will respond to market rates. As a result, it can be difficult to model the assumptions accurately on these sources of funding.
However, the assumptions tied to these deposits are vitally important, particularly for institutions for which these deposits are a core source of funding. If these products have no defined maturity, and the price can fluctuate on them, what do financial institutions model?
Modeling Non-Maturity Deposits Begins with Segmentation
The first thing ALM modelers should do is segment NMDs appropriately. Appropriate segmentation of NMDs includes the obvious breakouts of checking vs. savings vs. money market accounts, etc. But beyond that, it’s best to group products in each of those sectors into “premium” vs. “regular,” with the idea that products deemed premium will react more strongly to changes in market rates than the “regular” products.
Additionally, it is important to consider differences in depositor types such as consumer, business, or public funds, as they will often behave differently even at the same terms and pricing. Blending these products together may not give modelers an accurate picture of the impact of changing rates in the environment. Once that’s completed for each sector, the next step is to quantify:
- the expected lives of NMDs
- how reactive each sector is to changing market rates, and
- the core vs. surge balances in each sector.
The first challenge of non-maturity deposit modeling is defining how long these will be on the books for the institution. Borrowers can add to or take away any amount of money from these accounts at any time, introducing liquidity risk if there is a sudden outflux of these deposits and repricing risk if the institution suddenly must replace that lost funding with other sources.
Since there is no way to define an actual maturity, studies can be performed to determine the decay rate, or attrition, of non-maturity deposit accounts. We can take historical information and determine how much, on average, runs off our different accounts and apply that information to our ALM modeling to get an accurate look at the impact on liquidity and market value at risk. A good core deposit analysis can also delineate between balance decay (the rate of balance runoff) and account decay (the rate of accounts closing or becoming dormant).
The second challenge of non-maturity deposit modeling is understanding how reactive the pricing on deposits is to changes in market rates. A standard measure for this is the beta of an account. The beta is essentially the coefficient of how much rates on an account will move compared to how much market rates move. For example, if an account has a calculated beta of 0.25, then for every change in the market of +/- 100 bps, we can expect the account to move +/- 25 bps. Finding this beta allows ALM modelers to apply this assumption in income simulations to get an accurate look at how changes in interest rates affect the cost of funding on these accounts and, ultimately, the margin.
These betas can be derived in a number of ways but deriving from historical data is the preferred approach. At Abrigo, we correlate an institution’s actual change in price historically on each account and correlate those changes against changes in multiple different market rates to determine which market rate each account is tied closest to. From there, we determine how much the change in price has moved compared to the change in the market rate to determine the beta of the account.
The last, and perhaps the most challenging aspect of modeling non-maturity deposits is quantifying core vs. surge balances in non-maturity accounts.
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Core deposits refer to the deposits in the institution that are long-term and are not overly volatile to changes in market rates or economic activity. Essentially, these are the deposits that institutions can expect will stick around for a long time and not reprice too drastically.
On the other hand, surge balances are the balances that move in and out of non-maturity accounts at higher-than-predicted rates for some specific reason. While changes in rates could be one reason these balances move, other reasons could include the reversal of an event that caused the surge, a natural disaster, or economic reasons such as a decline in the stock market.
Some core deposit studies do not consider surge balances in their analysis. The danger of this is it causes institutions to consider all of the balance in their non-maturity deposit accounts as core money that’s less reactive to rate changes and will stick around for a while. If that incorrect assumption is applied in the model, the interest rate and liquidity risk analyses will not be accurate and will not reflect what could happen in actuality during changing rate environments.
If an institution is expecting a change of pricing of 5 bps in an account based on their model assumptions, but the surge balances in the account actually require a greater change in price, then that can have a significant impact on margin, return on equity, and return on assets.
Single pool vs. vintage core deposit studies
As referenced earlier, a common study performed on NMDs is a core deposit study. However, there are different types of core deposit studies. The more traditional method is what’s called a single pool study. This approach tracks changes in an initial study group over time. It calculates changes in accounts and balances over time, as well as price sensitivity to determine decay rates and betas. There are some glaring flaws to this approach. The biggest weakness is that this initial study group is typically from a different time period, and the study group does not represent the majority of today’s balances.
For example, if we were doing a core deposit analysis today and our initial study group was from 2011, how much of our current balance comprises balances from that initial 2011 group? It’s likely it doesn’t make up much. Does it make sense to calculate our assumptions from that initial study group alone?
The second flaw of a single pool study is that it applies the behaviors of a single group to all different groups when we know that:
- each group is made up of depositors with different demographics, and
- behaviors change across demographics.
The superior method for performing a core deposit analysis is what’s called a vintage method. This type of core deposit study tracks an initial study group but also subsequent groups of new accounts over time. This deposit analytics approach allows institutions to track behaviors of newer accounts vs. older accounts. It doesn’t ignore sectors of those pools that generate the majority of the balance within the pool, and it allows for easier identification of core vs. surge balances within each sector.
The information derived from core deposit studies is valuable to institutions because it allows management to fund assets appropriately with non-maturity deposits.
Before we discuss how to leverage the results of a core deposit study, let’s first explore the concept of effective duration. Although expressed as a number of “years” for comparability to other metrics, effective duration is not a length of time. Instead, effective duration is the amount of price sensitivity in a deposit category. A higher duration reflects a better hedge against market rate changes because the sector’s value is less affected by rate changes.
The calculation is simple:
Effective Duration = — Change in Market Value / Change in Market Rate
This measure is preferred over a typical weighted average life calculation because weighted average life only takes into account the decrease in principal balance. On the other hand, effective duration considers decay rates, surge balances, and sensitivity to changes in interest rates (betas). A longer effective duration represents that it holds more value to the institution (because the sector is longer-term and is less volatile), and a shorter effective duration represents that it’s less valuable to the institution.
By being able to determine the decay rates, betas, and surge percentages of each sector, an accurate effective duration for each can be calculated. Management can then use the sectors with higher effective durations to fund longer-term fixed assets without fear of significant interest rate risk because the sector does not decay quickly and is not sensitive to changes in interest rate.
Financial institutions would generally want to use the sectors with shorter durations to fund shorter-term assets such as auto loans. Additionally, identifying surge balances and calculating effective durations would inform management of the amount of deposits that should only be used to fund volatile and adjustable-rate assets such as credit cards.
Non-maturity deposits can be used as a natural hedge for the rest of the portfolio when treated correctly. Experienced advisors and an updated core deposit analysis can help financial institutions ensure they are developing key assumptions correctly by segmenting NMDs effectively, tracking them, and leveraging their hedging power in a rising-rate environment.