Non-Maturity Deposit Modeling: Balance Sheet Management Considerations

Numerous risk and profitability management exercises have a common challenge which derives from the need to understand and predict the behavior of non-maturity deposits (NMDs); various risk measures, product management and performance management processes require an explicit assumption about repricing and liquidity cash flow dynamics which must be robust to a wide-variety of possible business environments. The challenge relates directly to the absence of contracts or rules which dictate the level and timing of principal and interest cash flows. Assumptions, therefore, must be developed through some sort of empirical modeling process, but while historical analysis is a useful starting point, it is insufficient for most risk and profitability management purposes. This is especially true today given the very low interest rates and excess liquidity that characterized many economies for the better part of the last decade; the observed "stickiness" and low rate-sensitivity of deposits are not likely robust to rising rates. The assumption setting process is also complicated by the impact of other dynamics, such as the institutions’s balance sheet growth objectives, the structure of performance incentives, governance processes as well as changing customer preferences. Material differences in actual behaviors relative to expected behaviors are always possible. Because NMDs are the primary funding source for most depository institutions, any errors in behavioral assumptions can lead to risk and profitability measures that are incorrect and misleading.

Delegates to the workshop will come to understand the various risk and profitability management contexts that give rise to the need for models of NMD behavior as Dr. Green walks through his experience in past cycles building and managing such models. Whether tasked with building a model, validating or auditing one, or simply relying upon the output of one, it is imperative to understand the strengths and weaknesses of chosen modeling approaches and the extent to which they acknowledge specific risk and profitability management requirements. To this end, Dr. Green will demonstrate his NMD Model, which is unique in its ability to speak simultaneously to a broad range of balance sheet management problems. In addition to quantifying the salient characteristics of rate elasticity, balance decay, and balance volatility, the model contains its own FTP engine, which is used to produce historical, current, and pro forma FTP rates. The FTP rates are used to ensure that key behavioral assumptions feeding risk and profitability management processes are and remain fully aligned.