Information Matrix

We've created a short graphical summary of the application of postcode-driven lifestyle within actuarial mortality models.

We have written previously about the importance of the independence assumption when modelling mortality for annuities and pensions. In a recent presentation to the Royal Statistical Society I showed the audience how life insurers deduplicate their annuity data and how they use postcodes to identify socio-economic status.

Scientists strongly prefer ideas and processes which have undergone anonymous peer review in published, refereed journals.

The Bank of England has reduced its current bank rate to 1.5%, the lowest since it was founded in 1694.  Whilst this is good news for borrowers, it is bad news for those in retirement who are living off the interest on their savings.

Another week, another giant financial institution comes crashing down.  This time it is the turn of HBOS, a large UK mortgage provider.  The problem was not one of leverage as such, since all banks are highly leveraged.

The recent bankruptcy filing for Lehman Brothers follows hard on the heels of the forced takeover of Bear Stearns earlier this year. Debt played a role in the demise of both: as with many banks and other businesses, they used borrowed money to enhance shareholder returns, a phenomenon known as leverage.

During an analysis of a large annuity portfolio we took some time out to look at the pattern of mortality by season as well as the overall time trend. We fitted a model for age, gender and season, where the definition of season is that used by the ONS: each season covers three months, and where winter covers December, January and February.

Deduplication is an important step in data preparation for mortality modelling (or any other kind of modelling for that matter). If people in your data set have multiple benefit records, then the crucial independence assumption for statistical modelling in invalidated.