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A Marketing Audit of the Actuarial Profession

  • Ray J. H. Milne (a1), Gordon M. Bagot (a1), Alasdair C. Buchanan (a1), Alan R. Goodman (a1), Ashok K. Gupta (a1), Iain G. Horn (a1), Stewart F. Lee (a1), Bob Porch (a1) and Ian J. Thomson (a1)...


1.1.1 The Faculty of Actuaries' Marketing Research Group was set up in May 1988 to research areas of interest to that new breed of Fellow, the “Marketing Actuary”.

In the initial meetings two general areas of interest were identified—namely the marketing of the actuarial profession, and the marketing of financial services products.

Whilst the group has spent time on both subjects this first paper is concerned with the marketing of the actuarial profession.

1.1.2 We felt that the starting point for a marketing audit of the profession was to conduct research amongst the members. In addition we have investigated the coverage achieved by the profession in the media, and looked into developments in North America, including a survey which ranked the actuarial profession against other forms of employment.



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page 25 note * A chi-squared test is used here to determine whether two factors are independent of each other by investigating how close the actual value in each cell of the cross tabulation is to the value expected if independence exists. A “Probability Value” is the probability of achieving a result or response as significant as that actually obtained, if the two factors were truly independent.

page 34 note * A Rank Correlation Co-efficient shows the correlation between the relative orders of a set of data pairs. It can have a value between -1 and +1, +1 indicating perfect agreement between the two rankings. It has been used in this paper to show the degree of correlation between the rankings of the various Strengths, Weaknesses etc. produced by the survey and those predicted by the Faculty and Institute Councils.

page 37 note * In the context of this section t-tests were used in each case to calculate the probability (i.e. probability value) of achieving a result as significant as that actually obtained, if the true population percentage is equal to the average of the predictor questionnaire percentages.


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