Parametric insurance is attracting interest as a device to expand coverage for catastrophic events. These policies pay based on a few measurable characteristics (parameters), rather than on the loss incurred. Since these characteristics are usually obtained quickly through a public and reputable technical agency, parametric mechanisms offer more transparency and speed than traditional insurance products. However, these positive features come at the cost of precision. Since there is no adjustment of the policy in the classical sense, the payout produced is commonly calculated using algorithms, models, or equations that aim to approximate the loss suffered by the insured. The insurance industry refers to this potential inaccuracy in recoveries as “basis risk,” intuitively understood as the difference between the payout that one would expect from a traditional indemnity policy and the payout actually received from the parametric coverage. In this paper, we offer a formal description of basis risk using the Loss Capture Ratio (LCR), a metric that we have used successfully at Guy Carpenter to illustrate the performance of the parametric solutions we design for our clients.