Author's profile

Jens Nielsen
Cass Business School


Professor of Actuarial Science. Faculty of Actuarial Science and Insurance.

Author articles

  • Once widely used in construction, asbestos is known to cause several deadly diseases including the rare form of cancer known as Mesothelioma. Due to its long latency period and poor records of exposure, the number of cases of this disease is difficult to predict. This research compares two established methods of projection in order to determine which is more effective.

    12/11/2015 | 246
  • Mortality models are increasingly used to answer a number of pension related questions. This executive summary describes the development of a visualisation technique useful for the individual assessment of the quality of a mortality model.

    03/01/2014 | 3,201
  • Why should those at the top end of the salary scale be the only ones getting high quality financial advice on their savings and pensions? How can digital technology deliver this advice at low cost to everyone?

    03/10/2013 | 2,708
  • 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.

    13/05/2013 | 3,610
  • 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.

    02/05/2013 | 4,676
  • 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.

    08/07/2015 | 9,910
  • 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.

    10/06/2013 | 7,335
  • Banking

    Is it possible to predict equity returns and premiums with the use of empirical models? This is one of the most frequently pondered and studied questions in finance. In this research we examine the predictability of returns, taking the actuarial long term view and basing predictions on yearly data.

    25/06/2013 | 2,859
  • 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.

    29/10/2012 | 3,541
  • Financial services companies wishing to increase their sales may look to their existing customer base for cross-selling opportunities. Information on customer behaviour can be analysed to assess whether or not more products should be offered. In particular, data on past claiming history and information on payment defaulting can be useful in determining how an individual customer is likely to act with another type of product. This study demonstrates a method for using historical information to both identify potential customers for cross-selling and assess their 'risk profile'. It may help companies improve their marketing to existing customers, and ultimately lead to higher profits.

    22/10/2012 | 8,253