I find it interesting that exposures are the most fundamental part of ECRG, yet they’re the piece organizations get wrong most often. We naturally jump to causes, controls, or who made the mistake but exposures are just the types of losses we signed up for by choosing that activity. If we mis-scope the exposure, everything else such as controls, resilience, and governance becomes reactive instead of strategic.
When we talk about Exposure we tend to list events like fraud, outages, cyber breaches, or model errors, but what really matters is whether we are able to see the exposure before it hits us. The hard part is not naming risks, it is recognizing how easily we underestimate them or ignore them. Exposure is fundamentally a human problem because people normalize small issues, overlook weak signals, and assume it will not happen to us. The biggest risk is not the event itself but the blind spot that stops us from seeing the event as possible.
What stood out most to me is how exposure becomes a much more useful organizing concept once we stop treating it as “what could go wrong” and start treating it as the specific loss outcome the business is actually on the hook for. That shift feels small, but it changes the entire conversation: instead of debating symptoms, teams have to agree on the real end-state they are exposed to, and only then look backward at causes, controls, and resilience.
It also makes me think about consistency. If exposure is outcome-based while controls, resilience, and governance are cause- and process-based, then different teams could easily drift in how they classify things—especially in large organizations with legacy Basel categories baked into reporting. So…
Really interesting how causes are separated from exposures. Most banks still treat ‘what can go wrong’ as a category system, which is exactly why their maps blow up into spaghetti. Exposure = outcome is such a simple but clarifying reframing. In addition to this, if exposures are outcome-based, not cause-based, what’s the best way for a bank to validate that its exposure hierarchy is actually MECE? Especially when internal data sets are messy and Basel categories are already baked into reporting systems?
I find it interesting that exposures are the most fundamental part of ECRG, yet they’re the piece organizations get wrong most often. We naturally jump to causes, controls, or who made the mistake but exposures are just the types of losses we signed up for by choosing that activity. If we mis-scope the exposure, everything else such as controls, resilience, and governance becomes reactive instead of strategic.
When we talk about Exposure we tend to list events like fraud, outages, cyber breaches, or model errors, but what really matters is whether we are able to see the exposure before it hits us. The hard part is not naming risks, it is recognizing how easily we underestimate them or ignore them. Exposure is fundamentally a human problem because people normalize small issues, overlook weak signals, and assume it will not happen to us. The biggest risk is not the event itself but the blind spot that stops us from seeing the event as possible.
What stood out most to me is how exposure becomes a much more useful organizing concept once we stop treating it as “what could go wrong” and start treating it as the specific loss outcome the business is actually on the hook for. That shift feels small, but it changes the entire conversation: instead of debating symptoms, teams have to agree on the real end-state they are exposed to, and only then look backward at causes, controls, and resilience.
It also makes me think about consistency. If exposure is outcome-based while controls, resilience, and governance are cause- and process-based, then different teams could easily drift in how they classify things—especially in large organizations with legacy Basel categories baked into reporting. So…
Great summary, makes me clearer of what's included in Exposures
Really interesting how causes are separated from exposures. Most banks still treat ‘what can go wrong’ as a category system, which is exactly why their maps blow up into spaghetti. Exposure = outcome is such a simple but clarifying reframing. In addition to this, if exposures are outcome-based, not cause-based, what’s the best way for a bank to validate that its exposure hierarchy is actually MECE? Especially when internal data sets are messy and Basel categories are already baked into reporting systems?