Actuaries are guesers. They are systemic guessers, but they make guesses none the less. The larger the population and the richer the data history, the closer to reality their guesses tend to be as long as we can assume no massive step functions in the input-outcome matrixes. Actuaries really don’t like making guesses when they are working with mostly unknowns or at best extraordinarily wide parameters of plausible values as they know that their error bars will be significant.
The Exchange has been a source of night terrors for actuaries for eighteen months now. It was the ultimate in vaguely defined parameters. No single company knew what other companies were doing, no one knew exactly how people would choose plans, no one knew who exactly was in the eligible population and more importantly who would be in the sign-up generation. No one had a representative claims history.
Companies made massive efforts to get some structure to their guesses. For instance, my company participated in a consortium that interviewed 100,000 people with in-depth focus on several thousand people in order to get a feel for what potential Exchange customers wanted and what types of medical needs they would have. My company had a role play team that attempted to game out various strategies we could use as well as our competitors. Another company conducted over a hundred focus groups in a single market. Data miners created proxy consumers from claims data. But the actuaries and finance people priced 2014 Exchange products with at least severe glaucoma in their eyes.
Vision is improving now as the unknowns are shrinking and the known knowledge space is increasing. The 2015 product development round should see significant mistake correction on pricing. But let’s review a few common sources of error.