Non-Maturity Deposit Analysis
Overview
Non-Maturity Deposit Analysis is the review of regular savings, money market, and checking accounts of a credit union to estimate the price sensitivity and expected life of those accounts. Understanding the past behavior of members and their deposits gives a credit union insight into the likelihood of these accounts in the future.
The Money Came, Now What?
Modeling non-maturing deposits has been a conundrum since the advent of financial modeling. The modeling exercise requires that we assign a contractual like assumption to deposits that have no contractual end-date, only a presumed end-date for the deposits to remain with the credit union. QuantyPhi gives a quick explanation for how this modeling helps mitigate financial risks in their whitepaper, The Money Came. Now What?
Key Benefits
The information gained from Non-Maturity Deposit Analysis allows credit unions to determine whether their less expensive funding is likely to remain available. Income simulation, or A-L modeling, requires that assumptions are made on these deposits. A proper analysis gives a sound basis for these assumptions in many interest rate environments.
Non-Maturity Deposit Analysis allows CEOs, CFOs, regulators, and other credit union leaders to better understand their credit union’s interest rate risk exposure. It enables them to identify and act upon performance opportunities and potential risk threats in both the short- and long-term. Discovering the price sensitivity and the deposits that may leave in an increasing rate environment helps managers plan the balance sheet strategy more effectively.
QuantyPhi's experts do the groundwork and present the most relevant, accurate, and actionable data. We will gather the data, apply the statistical analysis, compare the balance sheet makeup, and explain the results to you so you can manage your credit union’s balance sheet more effectively. We know how to analyze previous pricing and balance information and calculate the relevant statistical review. Separating and properly modeling sticky and non-sticky deposits will help avoid inferior modeling assumptions.
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