  We consider the problem of estimating a spectral risk measure (SRM) from
i.i.d. samples, and propose a novel method that is based on numerical
integration. We show that our SRM estimate concentrates exponentially, when the
underlying distribution has bounded support. Further, we also consider the case
when the underlying distribution is either Gaussian or exponential, and derive
a concentration bound for our estimation scheme. We validate the theoretical
findings on a synthetic setup, and in a vehicular traffic routing application.
