Postgraduate Scholarship Insurance risk-classification, loss coverage and adverse selection



Supervisor: Pradip Tapadar

Unless the risk in question is similar for all potential customers, an insurer is exposed to the possibility of adverse selection by attracting only high-risk individuals. Insurers have traditionally employed underwriting principles, to identify suitable risk factors to subdivide their potential customer-base into homogeneous risk groups. An appropriate risk premium for each individual risk group can then be charged based on their respective risk profiles.

However, it can be argued that from society’s viewpoint, the high risks are those who most need insurance. That is, if the social purpose of insurance is to compensate the population’s losses, then insuring high risks contributes more to this purpose than insuring low risks. The traditional insurers’ principle of attracting low risks and deterring high risks by charging risk-appropriate premiums can be seen as contrary to this social purpose.

Also, the use of certain risk factors for insurance underwriting has been controversial, in particular, the factors over which an individual has no control. This has a significant bearing on regulatory regimes and public policy development.

There is a significant amount of literature on these issues, see for example, Macdonald and Tapadar (2010).

The proposed PhD project will focus on:

  • Extending the ideas of Macdonald and Tapadar (2010) using prospect theory and allowing individual’s loss coverage decision to vary.
  • Developing flexible models to reproduce, explore and extend the results of Thomas (2008, 2009) and Karagyozova and Siegelman (2012).
  • Developing indices to measure the degree of partial risk classification in a market, and relate this to loss coverage in the market.
  • Developing indices to compare the degree of adverse selection in different markets.

The project will consider the issues from the viewpoint of society as a whole.

The School of Mathematics, Statistics and Actuarial Science

The School offers a lively research culture with a thriving group of around 250 taught postgraduates students and almost 100 postgraduate students, postdoctoral researchers and academic staff. Kent is among the best research-intensive universities in the UK. In the 2008 Research Assessment Exercise (RAE), the university was ranked 24th out of 159 institutions for its world-leading research, with six of our subject areas (including statistics) in the top ten nationwide. Details of the research undertaken by the School can be found at: http://www.kent.ac.uk/smsas/postgraduate/phd-applications.html

The funding

Details on funding can be found at: http://www.kent.ac.uk/smsas/postgraduate/phd-applications.html

Entry Requirements

All candidates must have an excellent academic track record in a first degree in an actuarial, mathematical, statistical or economics-based subject along with a Masters qualification in a related subject.

To apply

To apply complete the online application form available by clicking the ‘Apply’ button below or by visiting: http://www.kent.ac.uk/studying/postgrad/apply/index.html and select School research Scholarship under `How are you intending to fund your studies?’.

Closing dates

A studentship will be offered as and when a suitable candidate is found.

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