Hanover Special Report #24

Compensation Study - Catastrophe Modelling & Exposure Management

Michael Stefan

2022-08-11

Introduction

This is Hanover’s fifth consecutive annual salary survey for the catastrophe modelling and exposure management community. I am grateful, as always, to all respondents as well as the dozen or so reviewers who have provided excellent feedback over the years. For reference, you can still view the 2021 results online (perma-link, no registration needed). I started the project in 2018 as I wasn’t satisfied with the quality of salary data available and I am very grateful to everyone who has volunteered their time to fill out the survey over the years.

Pay (and in particular pay equality) has grown in importance over the last decade and whilst this survey does not claim to have all the answers, I hope it at least sheds some light on a very opaque area, especially in an area of the market where there is very wide spectrum of skill-sets. As in previous years, we have only surveyed UK based catastrophe modelling and exposure management professionals working for (re) insurers, ILS funds, brokers, insuretechs, consultancies and vendor modelling firms. We have surveyed staff at all levels, although our database is very heavily geared towards experienced practitioners, typically with 5 years experience or more, and often with Master and PhD degrees. We don’t recruit junior analysts, although I am connected to a some via Linkedin, and they were invited to participate too. The majority will have worked with shorter-tail lines, though there are growing numbers of respondents who have also gained experience of longer tailed lines, including cyber.

The first eight questions remained exactly the same as last year. This year, I added an extra question to ascertain the difference in respondents’ base salaries between Apr 2022 and Apr 2021. This difference was expressed as a ratio. The inclusion of the question has been very popular and actually led to an increase in responses (compared to last year).

Uses

I always find there are three types of “user” for my compensation surveys:

My compensation studies have always been designed to serve as reference guides and the idea is to cover both absolute levels of earnings as well as relative changes from year to year. In previous years, when inflation was negligible, relative changes weren’t really requested by the community, but we live in a different world now. Please note that I published some analysis of relative levels in early summer 2022 and the pdf can be downloaded here. The report that you are reading right now will focus mostly on absolute levels.

Last but not least, this guide is best read on a desktop or laptop. It is not designed for small screens. Please remember that this guide is constantly updated, so it may have changed slightly since the last time you viewed it (as new responses and new analysis might have taken place). As of the last update (Aug 11, 2022), the survey is based on 94 responses.

Terminology

Total Earnings

This section will focus on total earnings (ie P60 + LTIPs), adjusted for 100% full time equivalent pay (in other words, absolute levels). I will cover the following:

Earnings are affected by many factors, and considering sector, gender, years experience etc individually in turn is the simplest way to identify any obvious gaps. That being said, analysing each of these factors on it’s own discards the other factors; ie if we just look at years experience, we are ignoring academic achievement, sector etc. I have a model that captures these factors (ie a linear regression model) but have chosen not to present it here as I have done previously and it’s never really seemed to be of interest to the audience.

The overall average for all respondents is £116,792 with a standard deviation of £82,792. The rather large standard deviation is due to the mix of experience levels, ranging from a few junior analysts to some very experienced individuals. Median total earnings for all respondents is £99,000.

Total earnings by sector

The “Other” category comprises of 2 respondents who declared they work in a consultancy, and 3 who declared they work within ILS.

Sector Mean Minimum Median Top Quartile Maximum Mean Yrs Exp Responses
Broker £ 124,643 £ 40,706 £ 100,000 £ 164,750 £ 360,000 11 19
LLM £ 112,467 £ 26,683 £ 98,000 £ 141,000 £ 480,000 10 59
Other £ 100,800 £ 25,000 £ 105,000 £ 105,000 £ 186,000 9 5
Vendor £ 133,701 £ 51,753 £ 80,000 £ 156,500 £ 423,953 9 11
How does this compare with previous years? Looking at previous survey data we have the following table of earnings:
Year Mean Median
2018 £ 89,248 £ 77,686
2019 £ 107,006 £ 96,125
2020 £ 86,292 £ 75,000
2021 £ 106,136 £ 91,244
2022 £ 116,792 £ 99,000

There is some variation in the figures, and to a large extent that’s down to noise (different respondents every year), leading to slightly different experience profiles. The figures are also presented as they were collected, ie not adjusted for inflation.

Total earnings by gender

All respondents:

Gender Mean Minimum Median Top Quartile Maximum Mean Yrs Exp Median Yrs Exp Responses
Female £ 95,611 £ 30,000 £ 73,000 £ 110,000 £ 231,000 10 8 25
Male £ 124,466 £ 25,000 £ 102,000 £ 160,000 £ 480,000 10 10 69

Respondents with 5 years experience or less:

Gender Mean Minimum Median Top Quartile Maximum Mean Yrs Exp Median Yrs Exp Responses
Female £ 59,571 £ 30,000 £ 54,000 £ 70,500 £ 105,000 3 4 7
Male £ 56,263 £ 26,683 £ 49,750 £ 69,088 £ 120,000 3 3 16

The gap between men and women’s total earnings (whether we consider the average, ie mean, or median) is rather large when you consider all respondents, especially in view that the average number of years experience for both genders is equal (at 10), although the median woman has 8 years experience as opposed to men (10). If we focus in on the “newer” cohorts (ie 5 years experience or less), it appears that the gap has actually reversed slightly (although do note that the median woman has 4 years experience as opposed to the median man with 3).

Earnings by gender per year worked

One way to look at the gender pay gap is to calculate how much each year of experience is worth (in other words, divide someone’s total earnings by the number of years experience they have, and do that for everyone). For our 2021 survey, we found that this “earnings per year worked” ratio was quite similar for men and women, although this year the gap seems to have widened again. While there is some overlap, I would suggest that, consistent with most years, men get rewarded more for each year of experience they bring.

Total earnings by years experience

When looking at the table, please remember that anyone with more than 20 years experience has been “recoded” to 20 (to avoid potential identification of older and well known cat modellers).

Mean Minimum Median Top Quartile Top Decile Max-Min Ratio 90-10 Ratio Respondents
0-2 years £ 47,140 £ 26,683 £ 40,500 £ 51,375 £ 66,600 4.5 2.4 12
3-5 years £ 66,652 £ 37,000 £ 66,000 £ 78,000 £ 98,000 2.8 2.4 21
6-8 years £ 99,617 £ 54,732 £ 82,700 £ 132,500 £ 156,000 3.2 2.7 14
9-11 years £ 129,923 £ 25,000 £ 110,000 £ 134,000 £ 186,600 17.0 2.7 15
12-14 years £ 153,739 £ 94,000 £ 112,944 £ 155,500 £ 183,400 5.1 1.9 12
15-17 years £ 190,060 £ 138,000 £ 190,000 £ 231,000 £ 232,147 1.7 1.6 9
18-20 years £ 192,198 £ 75,000 £ 170,000 £ 204,588 £ 360,000 5.3 3.0 11

What is the “Max-Min Ratio” and the “90-10 Ratio”? Very simply, “Max-Min” is the ratio of the highest pay disclosed by a respondent divided my the lowest disclosed by a respondent (for each respective category) and is a measure of dispersion (or variation, or perhaps you could say inequality). For example, the lowest age bands have relatively narrow ratios (a ratio of 1.6 means the highest respondent earned 1.5 times the lowest respondent). What is very interesting (to me anyway!) about this table is that the ratios (especially the 90-10 one) are very consistent going up to 14 years (after that, the low number of responses makes the ratios inconsistent). The ratios are reasonably similar to the actuarial profession where they are mostly in the 2.5-2.7 range.

Total earnings by gender and number of staff managed

Below we have charted the Total Earnings for every respondent, given how many staff they manage. The size of each bubble is proportional to how many years experience they have (the large the bubble, the more experienced). The overall trend is positive - ie the more staff under management, the higher the total earnings, although earnings seem to plateau around the £275k (it is worth noting we have excluded a few large outliers here to avoid potential identification.)

For individuals who do not manage others (call them “Individual Contributors” or “Non-Managers”), there is a wide variation in pay between men and women, even with similar number of years experience. Female individual contributors are also found clustered in large numbers at the lower end of the earnings scale. Once we move into management (ie at least one staff member under management), it is harder to state that women are paid less than men, as there is significant variation (at some staff levels women are paid the highest, at others they are not, and this compounded by the relatively few responses).

Total earnings by academic level

HighestQual Mean Min Median Top Quartile Max Mean Yrs Exp Median Yrs Exp Responses
Pre-Bachelor £ 147,200 £ 49,000 £ 170,000 £ 170,001 £ 202,000 15 18 5
Bachelor £ 132,704 £ 25,000 £ 87,500 £ 140,000 £ 480,000 10 10 20
PGD&C and Master £ 112,224 £ 26,683 £ 105,000 £ 154,000 £ 360,000 10 10 49
PhD £ 104,471 £ 37,000 £ 87,000 £ 108,754 £ 423,953 8 6 20

Due to the low number of responses for A-level and GCSE holders, we have consolidated them into a category called “Pre-Bachelor”. We have also consolidated the responses for “Master” and “Post Graduate Diploma & Certificate”.

Comparing pairs of qualification levels in turn, we notice first of all that there isn’t a premium for having a PhD (versus a master’s, or post-grad studies) - in fact quite the opposite at all levels, with the exception of the very highest earners. In fact the highest salary came from a respond with just a bachelor’s. In fact, other than entry levels (where we would often find respondents with the “minimum” salaries), you get better pay as a bachelor degree holder (and often even more if you “just” have some post-grad studies or a masters) than you do as a PhD. I believe this is likely due to the high number of PhDs working in individual contributor roles, perhaps focused on research and/or model development.

Total earnings by academic level (part 2)

One way to look at the academic pay differential is to calculate how much each year of experience is worth (in other words, divide someone’s total earnings by the number of years experience they have, and do that for everyone, segmenting by their highest qualification). It appears that regardless of qualification level, the most the market is willing to pay for a year of experience is around £14k.

Concluding comments

First of all, thank you for taking the time to read this report. The last year has been unusual in the sense that remote working has completely dominated although I feel it is still too early to really assess the pandemic’s long term impact on earnings. Many people are returning to the office, albeit on a part time basis, and brokers seem especially keen to have their staff members back full time or close to it.

That being said, what have we from this year’s survey and how has it differed from last year?

Finally, I will repeat my appeal from earlier: if you have filled out this year’s survey already, thank you. If you haven’t, I would urge you to complete it; here’s the link again. Better still, if you can forward this on to others, it will help spread the word.

About me

I have spent the last 18 years recruiting for senior actuarial, catastrophe modelling and analytical positions in the UK and abroad (including Bermuda and Continental Europe). My client base ranges from consumer insurance, commercial lines and Lloyds of London to more unusual operations involved in insurance linked securities, private equity and broking. I also research and write virtually all of our research reports, including compensation surveys.

Prior to joining Hanover Search in 2010, I spent 6 years working as lead consultant for the insurance and financial services division of Hays, a global FTSE-250 listed recruitment group.

Prior to university I spent 2 years working in sales for Churchill Insurance, one of the legacy companies of Direct Line Group.

I have a degree in Economics and Mathematics from York University and have completed a number of development courses, including a Strategy and Finance module with INSEAD and a psychometrics certificate with Cambridge University. In the summer of 2020 I completed two R-based courses with Essex University’s Summer School in Quantitative Social Science.

I have 2 young children under 7 so I don’t really have any spare time, but when I get a moment, I usually spend it reading.

Get in touch

Other than my research work (eg salary surveys), I am an active member of Hanover’s search and selection team. I have significant experience of completing difficult searches, especially where the “candidate pool” is very small. My track record includes:

My recruiting philosophy can be summarised as very simply:

I am always happy to:

For all queries, please email me: