His expertise lies in the analysis and development of statistical models for the analysis of complex actuarial datasets involving, among other things, cases of corrupted data, such as missing data for some lives, or the combined use of different datasets in order to return more robust estimates of mortality rates. Another key research theme is the analysis and the development of stochastic mortality models for the analysis of single and multiple populations, with a closer, albeit nonexclusive, focus on continuous time affine mortality models. The particular application lies within the analysis of individual savings and retirement decision making with emphasis on the development of innovative product solutions using LTC, health, annuities and life insurance.
My Research Activities
I am currently involved in a project aimed at the development of affine mortality models, their estimation and application within the analysis of individual savings and retirement decision making with emphasis on the development of innovative product solutions using LTC, health, annuities and life insurance.
Another key theme of my research is the development of statistical models for the joint analysis of dependent events.
My Research Supervision
Areas of supervision
- Stochastic mortality modelling
- Annuity portfolio hedging strategies
- Mixture models
- Statistical methods for the analysis of actuarial datasets:
- Address the problem of missing data
- Joint modelling of dependent outcomes, e.g. husband-wife lifetimes, frequency-severity of non-life insurance claims, competing risks, multiple decrement tables
- Dealing with the impossibility of using protected individual characteristics (e.g. gender, ethnicity, medical history) in pricing insurance policies
- Bayesian methods for the analysis of large dimensional datasets (e.g. using telematics data)
- Computational methods for asset-liability management of insurance companies
- Causal methods for policyholder decision making