Faculty of Actuarial Science and Insurance Seminar with Maria Caranante (University of Salerno)

Abstract
Discrepancies due to the misspecification of the mortality model are known as model risk. Model risk includes shocks caused by period effects that temporarily change the mortality behaviours. Period effects could fit the definition of frailty as the set of unobservable factors that determines the heterogeneity in mortality. In actuarial literature, the concept of frailty is often associated with a state of health-related vulnerability to mortality.
The heterogeneity of mortality caused by frailty is identified as a determinant of adverse selection for annuity contracts and the phenomenon changes according to the characteristics of the population.
We propose the use of the Age-specific and Temporal Frailty Lee Carter (ATFLCA) model, to estimate the differences in mortality forecasts between the general population and the annuity population. The underlying idea is that using frailty parameters in LC models, identified as the co-morbidity status of the individuals, can detect the differences in adverse selection in the annuity market since people with a lower risk of death are more likely to own annuities. In addition, we compare the explainability of the model, in terms of differences between the two populations, with a standard LC model, as a proxy measure of the adverse selection.


Biography
Maria Carannante is a Ph.D. in Social Statistics and is currently a post-doc research fellow at the University of Salerno in actuarial mathematics. Her main research interests concern big data management and processing methods, tree-based machine learning algorithms applied to data with spatial and/or temporal dependence, and stochastic mortality models, with particular reference to the study of asymmetric shocks in longevity trends and population ageing processes.

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