Professor of Actuarial Statistics, Faculty of Actuarial Science and Insurance.Richard Verrall has been at City University since 1987. He is an Honorary Fellow of the Institute of Actuaries (1999), an Associate Editor of the British Actuarial Journal, the North American Actuarial Journal and Insurance: Mathematics and Economics, and a Principle Examiner for the Actuarial Profession.
A novel statistical methodology created by academics at Cass Business School has led to improved data about deaths and life expectancy.
Research undertaken at Cass Business School has helped courts better assess the loss of earnings suffered by people who have had accidents.
Our previous academic research into Double Chain Ladder demonstrated how the classical chain ladder technique can be broken down into separate components. In this paper, we continue our investigation of the double chain ladder, and illustrate a simple way to include prior knowledge of severity inflation and future zero claims into the framework of the model.
This paper proposes a stochastic model for loss reserving based on incremental reported claim numbers and paid amounts, and which serves to predict Reported But Not Settled (RBNS) and Incurred But Not Reported (IBNR) claims separately. The paper takes the approach of building a model for aggregate paid claims from basic principles at the level of individual data. The research suggests that the use of the aggregated counts data can improve reserving accuracy.
This paper presents an extension to the model for forecasting outstanding claims liabilities, formulated by Verrall et al. (2010). The resulting model is closely related to the chain ladder method. So close in fact, it is possible to produce exactly the same results, if a particular choice is made about the way the estimates are obtained. This raises the question of why a new method is necessary. This research puts forward several answers.