Modern banking institutions frequently rely on likelihood-and-impact heat maps, a methodology derived from a 1984 Department of Defense framework designed for weapons systems. Dr. Edwards contends that these static tools fail to account for how separate exposures, such as liquidity stress and declining public confidence, interact. When these variables compound, a manageable issue can rapidly escalate into a systemic failure, a phenomenon he describes as one plus one equaling thirteen rather than two.
To address these limitations, FFERM Technologies proposes a four-factor methodology that incorporates predictability and compounding alongside traditional likelihood and severity metrics. By integrating leading indicators, this approach moves beyond assigning a single score to identifying risk behavior. The goal is not to replace existing data processes, but to provide community banks and credit unions with a more granular view of emerging threats before they materialize into crises.

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