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| While the House of Cards metaphor is crude, it gets across the idea of interdependence between risk factors, in contrast to the "risk bricks" of the old methods. |
Here's my main message:
- Existing methods that treat risk as if it were a pile of autonomous "risk bricks" is the wrong direction for risk management. ("Little 'r' risk")
- A better method is to measure and estimate risk as an interdependent system of factors, roughly analogous to a House of Cards. ("Big 'R" Risk")
I call the first "Little 'r' risk" because it attempts to analyze risk at the most granular micro level. I call the second "Big 'R' Risk" because the focus is on risk estimation at an organization level (e.g. business unit), and then to estimate the causal factors that have the most influence on that aggregate risk. With some over-simplification, we can say that Little 'r' risk is bottom-up while Big 'R' Risk is top-down. (In practice, Big 'R' Risk is more "middle-out".)
This new method isn't my idea alone. It comes from many smart folks who have been working on Operational Risk for many years, mainly in Financial Services. For a more complete description of the new approach, I strongly recommend the following tutorial document by the Society of Actuaries: A New Approach for Managing Operational Risk.
For readability and to keep an already-long post from being even longer, I'm going to talk in broad generalities and skip over many details. Also, I'm not going to explain and evaluate each of the existing methods. Finally, I'm not going to argue point-by-point all the folks who assert that probabilistic risk analysis is futile, worthless, or even harmful.

