Reader Response

Jul/Aug 2017 Reader Response

Dear Editor:

I found the article “The Darker Side of Data” (“On the Shelf,” AR November-December 2016) to be very thought provoking, but I found some of the author’s assertions regarding insurance mechanisms to be way off-base and I was surprised to find certain statements in a CAS publication. The author claims that “Insurance is pooled risk … in order for insurance to work, you kind of need to be ignorant in certain kinds of ways. In particular, you don’t know exactly who’s going to need the money.” Really? According to CAS Statement of Principles concerning ratemaking,

Ratemaking should provide for the costs of an individual risk transfer so that equity among insureds is maintained. When the experience of an individual risk does not provide a credible basis for estimating these costs, it is appropriate to consider the aggregate experience of similar risks. A rate estimated from such experience is an estimate of the costs of the risk transfer for each individual in the class.

The goal of ratemaking is to establish the costs associated with individual risks. To that end, big data enhances our ability to identify risk factors and develop prospective loss costs on a more refined basis. Certainly the creation of algorithms and interpretation of data requires a comprehensive understanding of the process, and careful judgment must be exercised in the application of such methods. Yet that doesn’t undermine our attempt to improve upon existing methods for determining exactly who will need the money and how much of it.

—Jonathan Brand

Grover Edie, AR Editor in Chief responds:

Having read Jonathan Brand’s letter and thought about it, I am still inclined to agree with the phrase “you don’t know exactly who’s going to need the money.” The key word in the CAS Statement of Principles is “estimating.” We don’t know the costs beforehand, we only can estimate them. The advent of big data and other tools enable us to do a better job of estimating expected costs, but if we ever get to the point where we can predict, with 100 percent accuracy, the frequency and the ultimate severities of losses for an individual risk, then we move away from an insurance situation and into a different realm.