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?”

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The worst insurance policy in the world

Aviva in France is still dealing with having written the worst insurance policy in the world. From the sounds of things, they weren’t alone in this foible. It’s also hard to say as an outsider what the right or reasonable resolution to their current problem is, but here is the policy that they wrote.

  • Buy a policy
  • Choose what funds you want to invest in
  • Unit prices calculated each Friday
  • Allow policyholders to switch funds on old prices until the next week
  • Hope like hell policyholders don’t switch out of poorly performing funds into well performing funds with perfect information based on backwards, stale prices.

Inconceivable – and since I don’t know more than I read on this blog post, maybe the reality and liability is really quite different.

See the FT on the man who could sink Aiva

Open mortality data

The Continuous Statistical Investment Committee of the Actuarial Society does fabulous work at gathering industry data and analysing it for broad use and consumption by actuaries and others.

I can only begin to imagine the data horrors of dealing with multiple insurers, multiple sources, multiple different data problems. The analysis they do is critically useful and, in technical terms, helluva interesting. I enjoyed the presentation at both the Cape Town and Johannesburg #LACseminar2013 just because there is such a rich data set and the analysis is fascinating.

I do hope they agree to my suggestion to put the entire, cleaned, anonymised data set available on the web. Different parties will want to analyse the data in different ways; there is simply no way the CSI Committee can perform every analysis and every piece of investigation that everyone might want. Making the data publicly available gives actuaries, students, academics and more the ability to perform their own analysis. And at basically no cost.

The other, slightly more defensive reason, is that mistakes do happen from time to time. I’m very aware of the topical R-R paper that was based on flawed analysis of underlying data. Mistakes happen all the time, and allowing anyone who wants to have access to the data to repeat or disprove calculations and analysis only makes the results more robust.

So, here’s hoping for open access mortality investigation data for all! And here’s thanking the CSI committee (past and current) for everything they have already done.

Just make up the numbers

There is a serious problem with journalism. Throughout the Lonmin strike, local and international news repeated the R4,000 per month current wage for miners as fact. One or two people pointed out that this wasn’t in fact the case, but that shortly disappeared from the stories and the amounts all over the media (and in the mouths of miners) was R4,000 per month.

Which of course was never the total value of the package and was highly misleading.

The following two quotes from the news24 article reflect the truth.

Striking miners had accepted a pay rise of up to 22% and would return to work on Thursday, worker leader Zolisa Bodlani said earlier.


Rock drill operators would now get R11 078 a month before deductions, production team leaders R13 022, and operators R9 883.

In my world, R4,000 plus a 22% increase does not get to R11,078. The numbers quoted before were made up, irrelevant, hyperbole, misleading, just plain wrong.

Why don’t journalists rather just make up the numbers they want to use to make the story appealing. They’re as good quality as numbers that are accepted without challenge from certain-to-be-biaed sources.