This Is The Biggest Risk That You Are Likely Missing At Your Bank

Managing Unexpected Losses

Risk managers get in trouble when they start measuring risk based on the expectation of loss or exposure. Expected loss is just part of the risk story.  Be it credit risk, liquidity risk, interest rate risk or operational risk, exposure for a bank must include the unexpected exposure, not solely the expected loss. Expected losses are priced into a contract and banks are typically compensated upfront for these risks. It is the unexpected loss that must be protected by capital and causes the most amount of damage and bank failure. We would like to demonstrate this phenomenon by using credit and interest rate risks.

 

Unexpected Loss in Credit Risk

 

Our Loan Command relationship pricing screen below shows the calculations and output from a five-year, fixed rate CRE loan.  The loan prices out to a robust 25% return on equity (ROE).  Most bank risk managers focus on the probability of default (PD) and loss given default (LGD) of the loan (which translates to an expected loss of 0.2% per year in this example).  However, this analysis isn’t the full picture because it considers the expected credit risk and does not include the unexpected credit risk. 

Unexpected Losses

 

The expected loss on the loan is not the true risk to the bank.  The bank will allocate their reserve or allowance for loan and lease loss (ALLL) for the loan to offset the expected loss.  In fact, in a well-designed loan pricing model, the bank will align its expected future loss on the loan with its ALLL methodology and new CECL accounting standards.  The end result is that the expected economic loss, and the expected loss based on accounting standards will be offset with ALLL.  The ALLL will reduce the profitability of the loan to the bank and all this will be reflected in the ROE figure.  That ROE is, therefore, based on the expected performance of the loan. 

 

The real risk to the bank is the unexpected loss and this is measured by the volatility around both the probability of default (shown as 0.23% in the output above) and the volatility around the loss given default (which is approximately 9.0%, or one standard deviation of LGD movement for senior secured credits).  The credit risk that the bank wants to proactively manage is the variability around the expected loss – this is a risk that most models do not capture and the risk that most banks forget about.  It is this volatility that represents the risk to the bank that is offset by the bank’s capital base. 

 

Put simply, the expected losses on loans are offset by a decrease in revenue through ALLL and the unexpected losses are the extreme events that are offset through the bank’s capital.    

 

Unexpected Loss in Interest Rate Risk

 

The same concept of unexpected results also plays out for banks with interest rate risk.  The yield curve is currently relatively flat and some bankers assume that this represents a lack of risk.  The market does not expect interest rates to be much higher in ten years versus in five years.  However, the expectation of interest rates is not a measure of risk for banks or borrowers.  A flat, forward sloping or inverted yield curves say nothing about interest rate risk.  The risk lies not in the expectation but variability around that expectation.

 

The graph below shows where the market expects short-term interest rates to be from now through 2021 in the white line.  The green lines above and below the white futures line is the distribution in decile around the expectation.  It is this distribution that represents the risk to the bank or borrower.  If the future always reflected the market’s expectation, there would be no risk to the bank or borrower regardless of the shape of the yield curve.  However, the interest rate risk is how rates move away from what is expected by the market. 

 

Potential path of risk  

Implication for Banks

 

Regardless of the type of risk (credit, interest rate, liquidity, or operational), banks need to measure the variability around the outcome and not simply the expected outcome.  To do so, banks either need a loan pricing model that takes this into account or need to access probability of various outcomes and then sum the product of the loss times the probability of that loss.  The easiest way to do this is measuring the standard deviation or volatility around expected future outcomes.  This is relatively easy to do for interest rate risk, slightly more challenging for credit risk (but still manageable using loan pricing models) and much more difficult for liquidity and operational risk (because of the rarity of an event and lack of observable volatilities). 

 

Conclusion

 

The risk that bankers should pay particular attention to is the unexpected result and not the expected.  During the last recession, unexpected losses were five times or more of a bank’s ALLL in many cases. That is a huge difference. While the next recession may not be as severe, it will likely be in excess of three times the then current reserve levels.

 

It is likely that ALLL levels will continue to drop pushing more risk to the unexpected category. This is something that banks must be vigilant of and proactively manage their credit and investment portfolios in addition to their capital levels.  

The expected risk to the bank can always be offset through revenue adjustment and may not result in variability of return.  It is the unexpected risk that takes down banks and creates profoundly negative returns in economic downturns.