Stephen Richards

I'm not a fan of the hyperbolic use of military metaphors in civilian life.  However, in rare cases they do seem appropriate, and the ongoing SAR-Cov-2 pandemic provides an example.  After all, describing a worker as "front-line" seems justified when the occupation carries a materially increased risk of infection and death (SAGE, 2021).

The ongoing coronavirus pandemic has so far produced two mortality shocks in the UK and many other countries.  Unsurprisingly, the extra mortality is also visible in annuity portfolios.  Such mortality spikes create a c

If you are in the business of pricing and managing longevity risk, you need software to help you perform your analysis. You have two choices:

In a previous blog I outlined my six-month rule of thumb for discarding mortality experience affected by reporting delays. However, this can be awkward where there is a hard limit on how far back the experience data goes. For example, when a pension scheme switches administrator, or an insurer migrates business from one system to another, past mortality data is usually the first casualty.

When performing a mortality analysis, it is my practice to disregard the most recent six months or so of experience data. The reason is delays in the reporting and recording of deaths, i.e. occurred-but-not-reported (OBNR) to use the terminology of Lawless (1994). We use the term OBNR, rather than the more familiar term IBNR (incurred-but-not-reported); IBNR is associated with "cost-orientated" delay distributions of insurance claims (Jewell, 1989), whereas we are focused on just the delay itself.

As 2020 edges to a close, life-office actuaries need to set mortality bases for year-end valuations. An obvious question is what impact the covid-19 pandemic has had on the mortality experience of their portfolio? One problem is that traditional actuarial analysis was often done on the basis of annual rates, whereas the initial covid-19 shock was delivered over a period of a couple of months in early 2020 in Europe.