Downwards counterfactual analysis

Stress and scenario testing are important risk assessment tools.  They also provide useful ways to prepare in advance for adverse scenarios so that management doesn’t have to create everything from first principles when something similar occurs.

But trying to imagine scenarios, particularly very severe scenarios, isn’t straightforward. We don’t have many examples of very extreme events.

Some insurers will dream up scenarios from scratch. It’s also common to refer to prior events and run the current business through those dark days. The Global Financial Crisis is a favourite – how would our business manage under credit spread spikes, drying up of liquidity, equity fall markets, higher lapses, lower sales, higher retrenchment claims, higher individual and corporate defaults, switches of funds out of equities, early withdrawals and surrenders and increased call centre volumes?

Downwards counterfactual analysis is the: Continue reading “Downwards counterfactual analysis”

Alternatives to uncanny

This is a rant about people who are wrong on the internet.  Also, why Huffington Post is a platform for big bad wolves. And why the asymmetric information and importance of financial advice means it’s not okay. Maybe this is just part of Cunningham’s Law.

Clickbait headline? Check.

3 Smart Alternatives to Life Insurance

Numbered list (the second one will surprise you…)? Check

Also, another numbered article by the same author “5 Viable Uses For A Reverse Mortgage”. No, I’m deliberately not linking. Then, without irony, another article, “The Death Of Click Bait Is Finally Here”.

Okay, but back to the actual topic. The first sentence in the article:

The simplest alternatives to life insurance include investing money and or saving it. If you are able to set aside enough funds each year, you can very well never have to worry about holding a life insurance policy.

So, in other words, a smart alternative to life insurance is just not having insurance at all.

The other two “smart alternatives” are, actually, life insurance. So the sum total of smart alternatives offered are “no insurance” and “life insurance”.

Maybe it’s fitting that the author describes himself:

Lazar is pronounced in his uncanny but effective content…

uncanny: strange or mysterious, especially in an unsettling way.  Check.

 

Do Data Lakes hide Loch Ness Monsters?

I had a discussion with a client recently about the virtues of ensuring data written into a data warehouse is rock solid and understood and well defined.

My training and experience has given me high confidence that this is the right way forward for typical actuarial data.  Here I’m talking in force policy data files, movements, transactions, and so on.  This is really well structured data that will be used many times by different people and can easily be processed once, “on write”, stored in the data warehouse to be reliably and simply retrieved whenever necessary. Continue reading “Do Data Lakes hide Loch Ness Monsters?”

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”

Board game recommendations (and reasons to use them)

I’ve played plenty of board games in my life. I’m not (only) talking about Monopoly.

I went to Cambridge (to visit, very sadly, not to study) in 2003. I found an awesome board game store and tried to buy Diplomacy.  The incredibly wise assistant basically forced me to buy Settlers of Catan before he would allow me to buy Diplomacy.

About Settlers of Catan

I have played hundreds of hours of Settlers, and recently gave Diplomacy away never having played it. I still believe it’s an awesome game.  (Strategy, relationships, IQ and EQ, competition and a little backstabbing. What’s not to like?) However, it  requires having enough people, the right sort of people. enough time (a weekend apparently is ideal) and ideally a couple people who have played before because it is complicated.

Now, Settlers has plenty of scope for tension as it is.  I kicked my best friend out of my flat once after a kingmaking incident. I’ve had arguments with significant others over games. And this is Settlers, not Diplomacy.

Do I recommend Settlers? Continue reading “Board game recommendations (and reasons to use them)”

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”