An English actuary can tell you how many people will die in the next year; the Sicilian one gives you their names and addresses. – thanks Alan Chaplin.

So why do we need artificial intelligence when this is common sense? It turns out that there are algorithms being invented in northern Europe that can tell by the things you say , when you are likely to die. This may sound challenging in my case as I say quite a lot, but it turns out, the more of your stuff can be tracked down , the more you give away about yourself the more we understand your propensity to snuff it

By using Denmark’s registry data, which contains a wealth of day-to-day information on education, salary, job, working hours, housing and doctor visits, academics have developed an algorithm that can predict a person’s life course, including premature death, in much the same way that large language models (LLMs) such as ChatGPT can predict sentences. The algorithm outperformed other predictive models, including actuarial tables used by the insurance industry.

Right now, it is possible to tell people tasked with insuring against you living too long, all about your health and lifestyle using a 100 page form which is shared around life insurers.

If you look less than 100% healthy, the chances are you will be bumped up a couple of years. I was told by my nurse that I was 6 years older than I am – in terms of life expectancy. This was not a compliment, it meant I had 6 years less to live than the average 62 year old.

That’s what happens with these 100 page long forms. The problem is that do the form, you need a medical expert or at least someone who knows how to navigate a digital document, to get to the end.

We’re looking into making this process a little more friendly , so that most of us can tell our insurers – or indeed pension schemes, what kind of a risk we are. It’s called “getting underwritten” and it takes me back to the parlours of West Ham when I would have to stare at the packet of fags, the pint of beer and the large belly of my prospective client and say something crass like “we all could drop dead tomorrow, how would the missus feel about that”. My attempts at Cockney cheeriness were about as authentic as Dick Van Dyke’s.

I’d like to think that some of the people I would have been selling insurance to in the 1980s are my age now and thinking about how to turn their workplace pot into a wage for life pension. Help is on its way and the intelligence behind the process may be artificial but it’s a little more authentic than my sales efforts back in the day!