Author(s): Paula Jarzabkowski et al.
At the end of 2009 the reinsurance industry was a confident and optimistic
one. A succession of major natural disasters during 2010, however, rocked the
industry and since then both competition and regulation have intensified. In
this first masterclass of a series of seven, we analyse the current state of
the reinsurance industry and suggest strategic responses to the current
Author(s): Les Mayhew
Longevity risk posed by an ageing population is one of the greatest challenges facing the financial services sector in the UK. In the fifth of the 2013 series of The Nicholas Barbon Insurance Lectures, Cass Business School Professor Les Mayhew addressed this issue.
Author(s): Maria Dolores Martinez Miranda et al.
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.
Author(s): Richard Verrall et al.
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.
Author(s): María Miranda et al.
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.
Author(s): Jens Nielsen et al.
The estimate of outstanding liabilities is of immense importance to non-life insurance companies. The task of estimating this number is frequently left to actuaries. This paper introduces a number of new methodologies and approaches to estimating outstanding liabilities in non-life insurance, and invites greater participation from operational research statisticians in improving research into the matter.
Author(s): Andrew Clare et al.
A research collaboration between Aon Hewitt and Cass Business School has shown that alternative weighted indices offer better investment strategies than those of the market capitalisation index. Indeed, a computer simulation of random stock-picking, likened to the decision making of a monkey, outperformed a traditional market capitalisation weighted index every time.
Author(s): Iqbal Owadally
In response to continuing deficits in UK defined pension benefit schemes since the start of the millennium, various parties have asked the UK Government to allow pensions schemes to calculate liabilities using a smoothed average of bond yields over several years. This paper explores the reasons for this request, and looks at multiple evidence of what impact, both beneficial and potentially risky, such a move could have.
Author(s): Andrew Clare
What are the similarities between a defined benefit pension plan and a football team? On the face of it there may not seem to be many. After all, the football world is populated by overpaid, badly behaved, play acting prima donnas. A far cry from the sober and serious world of defined benefit pensions, where trustees devote huge amounts of their time in the interests of others, for little of no financial reward. However, Professor Andrew Clare draws some interesting analogies between the two.
Author(s): Jens Nielsen et al.
In this research a new methodology for optimal customer selection in cross-selling of financial services products, such as mortgage loans and non life insurance contracts, is presented. Financial services companies tend to possess significant databases and a long relationship with each customer. In this situation the challenge becomes to use the database in general and specific knowledge of the individual target to estimate the probability of a cross-sale, the cost of a cross-sale attempt, the average discounted future profit and the uncertainty of the profit of the entire cross-sale attempt for that individual. Once reliable estimates for the stochastics of the cross-sale process have been established, one can optimise the cross-sale profit according to a variety of criteria including return and risk. In this paper, we first consider the simple question of optimising the average profit, but we also consider one version of adjusting for risk when optimising cross-sale profits. Our extensive case study is taken from non-life insurance, where our sales probability model is provided to us by the company that also provided us with the data.