Starring Into The Cost of Funding Debate – DDA, Betas and Duration

Interest Rate Risk

We need your help on this one.  If you have a pen and paper, keep it handy as we will ask you to write down one number related to your bank.  First, let’s define the concept.  In statistics, the correlation coefficient is a measure of the linear dependence between two variables X and Y, with a value that ranges between +1 and −1 inclusive.  A correlation of 1 is perfect positive correlation, 0 is no correlation, and −1 is a perfect negative correlation.  This concept is widely used as a measure of the degree of linear dependence between two variables.  A correlation above 0.90 or below -0.90 is considered very strong and is very rarely observed unless the two variables are causally connected.

 

Our Question

 

This is the interactive part - please write down what you believe to be your bank’s cost of funds correlation to short-term interest rates (think Fed Funds, LIBOR or Prime). This is to say, if rates go up to 1%, will your cost of funds go up 1%, or will it go up 50%, 20% or something less?  Keep this number for the end.

 

Observation

 

Generally, small banks have been increasing the duration of their loans (and also their securities).  The graph below shows the repricing of loans from December 2011 to March 2015 for three groups of banks (under $1B in assets, $1-3B in assets, and over $25B in assets).  The bottom bucket of the stack graph shows variable loans.  Each progressive bucket in the stack shows a longer term loan and the top stack is showing loans with over 15-years in repricing.  The graph clearly demonstrates that banks under $3B in assets have been extending the duration of their loan portfolio.  Banks over $25B in assets have actually been decreasing their loan duration.  Here is a quick way to interpret the graph:  the top three buckets show longer-term fixed rate loans, where net interest margin (NIM) will decrease when rates rise. The bottom three buckets show variable rate loans where NIM will stay constant when rates rise.  This graph shows that larger banks are positioned for rising rates.  Smaller banks are better positioned for declining rates – not a great strategic position for the expected interest rate environment.

 

Interest Rate Risk

 

How do bankers justify their extended loan durations? Some bankers defend their position by believing that their cost of funds will remain stable. The primary argument rests on the construct that they have plenty of duration in their core deposits.  Other bankers argue that their liability duration is already sufficiently long and their layering of DDAs, certificates of deposits and Home Loan advances will protect them in a rising rate environment. These bankers even support their position by showing around their asset-liability report that show the rate shock analysis barely move earnings and the economic value of equity.

 

Correlation between COF and Short Term Rates

 

For the reality of the situation, we, of course, turn to the data in order to gather quantifiable evidence.  We ran the correlation numbers for all banks in the country using two variables: 1) cost of funds (COF) of a specific bank with a 6 month lag, and 2) 1-month LIBOR (proxy for short-term rates, although the results are almost identical when we used Prime or Fed Funds).   We excluded banks with only a short history and we also excluded certain specialty banks with unusual cost structures (such as foreign banks with domestic lending, or specialty finance banks).  We ran the numbers for remaining banks ranging in size from $50mm in assets to $300Bn in assets. We considered rates from 1990 (where that information was unavailable for banks, we used at least the last 10 years of rate information).

 

The results may be surprising to many.  The average correlation between COF and LIBOR for all banks is very high at 0.908.  This tells us that if rates rise/fall the average bank’s cost of funding will rise/fall almost in lock step (with a 6-month lag).  The smaller the bank, the higher the correlation appears to be.  Banks below $100mm in assets have a 0.92 correlation between COF and short-term interest rates.  Banks between $100mm and $250mm in assets have a 0.91 correlation, and banks between $10B and $300B in assets have a 0.87 correlation.  The numbers show that all banks have a high correlation between their COF and interest rates, but smaller banks exhibit a higher correlation.  We postulate that this relationship holds because of the higher DDA balances at larger banks.

 

Below is a graph showing the historical relationship between short-term interest and COF for a typical bank (with a 0.94 correlation).  

 

Bank Interest Rate Risk

 

 

Conclusion

 

Despite the arguments we hear from bankers and at ALCOs that a bank’s cost of funding is stable and will move little with rising rates, the data shows otherwise. Interest rate hungry customers, the media effect and “surge balances” will also exacerbate this problem and make almost every bank’s liabilities more sensitive than estimated.

 

We believe that bankers are justifying their longer loan duration in an attempt to appease the board with a targeted NIM.  When rates rise, the bank’s COF increases and NIM will fall.  How will banks manage NIM in a rising rate environment if cost of funding will rise?  Growing loan portfolios in a rising rate environment has never been easy and may be a challenge for many banks in this coming rate cycle.  Our recommendation is simple:  banks (of all sizes) need to consider how to shorten loan duration and reduce interest rate risk. At CenterState, we use our ARC program to help manage interest rate risk. This very same program is available to all community banks.

 

Whether it is our hedging program or another interest rate risk management solution, the important point is that banks need a tool to drive quality loan growth while mitigating a potential interest rate increase.

  

If you want to see your bank’s interest rate correlation, please click HERE if you would like to receive a free report and graph for your bank.