The article explores how to deal with uncertainty in risk management and option pricing using a method called optimized certainty equivalent risk measure. By penalizing distributions that are far from a baseline distribution, the computation of this measure can be simplified into a finite dimensional problem. This approach can also be applied to pricing European options and deriving convex dual representations for measurable claims. The study provides conditions under which the robust average value-at-risk can be considered a tail risk measure.