In light of the recent Epsilon data breach, it seems appropriate to chat briefly about the realities of balancing information risk. First and foremost, we need to make sure that we understand this thing called “risk.” In our context, risk is defined as “the probable frequency and probable magnitude of future loss” (based on Jack Jones’ FAIR definition). Put into practical terms, risk is the likelihood that we’ll experience a negative event. We then balance that out against the cost of defending against various scenarios (i.e., trying to reduce or transfer that risk), with the goal being to optimize cost vs. benefit. Let’s look at a couple practical examples.