ENID not Blyton

ENID is a term widely used, just generally not in South Africa. For some reason we didn’t import the term along with most of Solvency II.

This has nothing to do with the Famous Five. While it is most common in the general insurance space, it is relevant across the spectrum of risk management and assumption setting.

Events Not In Data or “ENID” is the forgotten cousin of “what to do with outliers in your data”.

Outliers and where to find them

Outliers are observed values substantially different from others in a sample. Some more formal definitions include:

“An outlier is an observation that lies an abnormal distance from other values in a random sample from a population”

“an outlier is an observation point that is distant from other observations”

Not these sort of outliers. Entertaining book though.


How to deal with outliers?

Simple question, complex answer. It depends a great deal on the context.

Ultimately you need to make the judgement call “are these outliers under- or over-represented in the data”. Continue reading “ENID not Blyton”

Book Review: Loss Coverage – Why Insurance Works Betters with Some Adverse Selection

In their book, Loss Coverage: Why Insurance Works Better with Some Adverse Selection, Pradip Tapadar and Guy Thomas propose an interesting point that adverse selection may not be as harmful as many actuaries believe. They actually go further and suggest that, at least from a policy perspective, adverse selection may be a good thing.

This is particularly relevant given the ambition of some InsurTech players to hyper select risks or price on many more factors than are traditionally used in order to gain a competitive advantage.  Tapadar and Thomas don’t argue that it will be individual insurers’ interests to allow adverse selection, but if these companies are successful it may then have implications for policy makers.

Incidentally, there are some interesting reasons for insurers themselves (with commercial interests) to be wary of selecting too well, counterintuitive as that may seem, but more on that for another time. Continue reading “Book Review: Loss Coverage – Why Insurance Works Betters with Some Adverse Selection”

Modelling one side of a two-sided problem

Ah models, my old friends. You’re always wrong, but sometimes helpful. Often dangerous too.

A recent article in The Actuary magazine addressed whether “de-risking in members’ best interests?”  I say “recent” even though it’s from August because I am a little behind on my The Actuary reading.

In the article, the authors demonstrate that by modelling the impact of covenant risk, optimal investment portfolios for Defined Benefit (DB) pensions actually have more risky assets than if this covenant risk is ignored.

The covenant they refer to is the obligation of the sponsor to make good deficits within the pension fund. Covenant risk then is the risk that the sponsor is unable (typically through its own insolvency) to make good on this promise.

On the surface it should seem counterintuitive that by modelling an additional risk to pensioners, the answer is to invest in riskier assets, thus increasing risk.

The explanation proffered by the authors is that the higher expected returns from riskier assets allow the fund to potentially build up surplus, thus reducing the risks of covenant failure.

I can follow that logic, particularly in the case where the dependence between DB fund insolvency and sponsor default is week. It doesn’t mean it’s a useful result. Continue reading “Modelling one side of a two-sided problem”

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Behavioural economics and XKCD

This is premature for a book review as I’m only on page 3 or something. The book:Insurance and Behavioral Economics: Improving Decisions in the Most Misunderstood Industry has been recommended to me a few times. (Okay, twice by the same person, but that also actually says something.) I’ll work my way through it and give you my views.

But this XKCD reminded me of the ubiquity of behavioural economics everywhere in life.

Claims analysis, inflation and discounting (part 2)

This is part 2 of a 3 part series. Part 1 is here.

Non-life claims reserves are regularly not discounted, for bad reasons and good. This part of the series looks at the related issue of inflation in claims reserving. (You’ll have to wait for part 3 for me to talk about the analysis that prompted this lengthy series.)

In many markets, inflation is low and stable. Until a decade ago, talk of inflation wouldn’t have raised much in the way of deflation either. That’s still sufficiently unusual to put to one side.

Low, stable inflation means that past claims development patterns are mostly about, in approximate descending order of importance (naturally depending on class and peril) Continue reading “Claims analysis, inflation and discounting (part 2)”

Claims analysis, inflation and discounting (part 1)

I’ve had the privilege to straddle life insurance and non-life insurance (P&C, general, short term insurance, take your pick of terms) in my career.  On balance, I think having significant exposure to both has increased my knowledge in each rather than lessened the depth of my knowledge in either.  I’ve been able to transport concepts and take learnings from one side to the other.

A recent example relates to the common non-life practice of not discounting claims reserves.  Solvency II, SAM and IFRS17 moves to require discounting aside, it is still more a common GAAP approach to not discount than to discount claims reserves.

Discounting or fiddling with inflation has some obvious implications for analysing actual vs expected analysis, reserve run offs, and reserve adequacy analysis. That some non-life reserving actuaries trip over because it’s more natural in the life space.

But, first, why are non-life reserves so often not discounted? There are several reasons typically given: Continue reading “Claims analysis, inflation and discounting (part 1)”

Life in our time of cholera?

I love to read, so I’m not proud to admit right upfront that everything I know about “Love in the time of cholera” I learnt in 3 minutes from wikipedia starting about 3 minutes ago. Seems like a book I should read.

But another than playing on the well known book and movie title, this post has nothing to do with the book.

It has everything to do with cholera. And the very real possibility of a cholera or similar disease outbreak in Cape Town in the next year. Here is a little superficial analysis of the numbers.

The City of Cape Town now expects us to run out of municipal water

The City of Cape Town has gone from claiming unequivocally:

“we want to give the people of Cape Town an assurance that this well-run city will not run out of water.”

on the 17th of August 107 to 4 October 2017’s:

If consumption is not reduced to the required levels of 500-million litres of collective usage per day, we are looking at about March 2018 when supply of municipal water would not be available.

How are dam levels and consumption point away from achieving these targets

CT has been stuck persistently above 600Ml (million litres) per day for an extended period and this is down from a peak of 1,200Ml per day in January 2015. The low hanging fruit are long gone. I do not see how we will decrease consumption by another 20% (since we’re over 600Ml at the moment) and this therefore suggests we will run out of water.

Consumption has reduced significantly, but shows no signs of decreasing below 600Ml per day

Continue reading “Life in our time of cholera?”