Bayesian estimates, stable with respect to the choice of the loss function

A family of distributions is defined for which the generalized Bayesian estimate of a real parameter $\theta$, constructed according to the repeated choice, does not depend on the choice of the even convex loss function from a sufficiently wide class. It is shown that these families are a subclass of the exponential families with a sufficient statistic for the parameter $\theta$ of rank two.