The liquidity and interest rate risk (IRR) related behaviors of deposits and loans are complex and ever evolving. But they must be understood and accurately forecast in financial models to attain regulatory compliance with respect to liquidity, IRR, and general balance sheet management.
Now Available! The new regulatory Advisory on Interest Rate Risk (2010-A) recommends testing earnings at risk and equity at risk in +400 bp and +500 bp rate shock scenarios. To support these tests, special add-on forecasts to recently provided MPS loan and core deposit behavior analyses are available on an as requested basis.
All new MPS core deposit and loan behavior forecasts now include +400 bp and +500 bp forecasts as a part of all standard deliverables.
Compliance Inputs: Core Deposit and CD Behaviors
Best practice measures of core deposit and CD behaviors, supporting high levels of defensible liquidity and IRR compliance, are based on advanced statistical analysis of your institution’s recent data. Forecasts define financial model inputs that are institution specific, reset to current interest rate conditions in each model run, and vary across rate scenarios as applicable.
Four areas of deposit behavior need to be comprehensively quantified.
(1) What are the expected near term supply paths of deposit categories if interest rates remain constant? This momentum projection establishes the fundamental liquidity dimensions of deposit funding.
(2) What are the expected near term sensitivities of deposit supply by category if interest rates rise or decline? These sensitivity projections establish the stability of supply (or lack of) across a crucial liquidity and IRR test parameter.
(3) What is the repricing expected for each deposit category when interest rates change? This include both the overall magnitude of repricing and any lags. The beta estimates indicate the sensitivity of interest expense to changes in interest rates, a key element defining Earnings at Risk hedging.
(4) What is the expected decay in the institution’s deposits? These are used to calculate baseline average lives and their changes as interest rates change. Present values calculated using the runoff data depict the effective duration of each deposit category, a key element defining Equity at Risk hedging.
Compliance Inputs: Loan Prepayment and Paydown Behaviors
Best practice measures of loan behaviors, supporting high levels of defensible liquidity and IRR compliance, are likewise based on advanced statistical analysis of your institution’s recent data. Forecasts define financial model inputs for all loan types that are institution specific, reset to current interest rate conditions in each model run, and vary across rate scenarios as applicable.
Four areas of loan behavior need to be comprehensively quantified.
(1) For loans with contractual maturities, what are prepayments given current interest rates and what are the sensitivities of prepayments to interest rate changes?
(2) For loans with indeterminate maturities (e.g. credit cards and lines of credit), what are paydowns (runoff) given current interest rates and what are the sensitivities of paydowns to interest rate changes?
(3) Are there echo effects among loans by category? For example, a 1-4 family first mortgage prepayment will also cause home equity balances to prepay, and it may trigger consumer loan payoffs also. Because prepayments are estimated in a simultaneous equations model, such cross-category influence are quantified.
(4) What are the liquidity dimensions of loans in the balance sheet? Quantified loan behavior modeling inputs empower you to precisely anticipate loan related sources of liquidity.