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Why use survival models?

We and our clients much prefer to analyse mortality continuously, rather than in yearly intervals like actuaries used to do in previous centuries. Actuaries normally use μx to denote the continuous force of mortality at age x, and qx to denote the yearly rate of mortality. For any statisticians reading this, μx is the continuous-time hazard rate.
Written by: Stephen RichardsTags: Filter information matrix by tag: survival analysis, Filter information matrix by tag: survival models, Filter information matrix by tag: force of mortality, Filter information matrix by tag: hazard rate

Ahead of the curve

In an earlier post we looked at the implications for savers of the historically low interest rates in the UK. Low interest rates are a policy response to the unusual economic conditions in which the developed world currently finds itself.
Written by: Stephen RichardsTags: Filter information matrix by tag: interest, Filter information matrix by tag: yield curve

Survival models for actuarial work

The CMI recently asked for an overview note on survival models.  Since this subject is of wider actuarial interest, we wanted to make this publically available. An electronic copy can be downloaded from the link on the right.

Written by: Stephen RichardsTags: Filter information matrix by tag: CMI, Filter information matrix by tag: survival models, Filter information matrix by tag: mortality

Muddled about middle age

Mortality statistics occasionally make the news, usually with some eye-catching statements.  Here is a recent example from the BBC: "Data from life insurance companies suggests that in the fifth and sixth decades of life you are less likely to die over the coming year than at any other time in your life."
Written by: Stephen RichardsTags: Filter information matrix by tag: mortality

A head for tails

When an insurer or reinsurer takes on a new insurance risk, there are two things of special interest: the best estimate of the risk and the tail risk.
Written by: Stephen RichardsTags: Filter information matrix by tag: tail risk, Filter information matrix by tag: Solvency II, Filter information matrix by tag: ICA

Countdown to unisex pricing

In just over one year's time, insurers throughout the European Union will be prohibited from using a person's gender to price insurance risks.
Written by: Stephen RichardsTags: Filter information matrix by tag: gender, Filter information matrix by tag: annuities

Lost in translation (reprise)

Late last year I drew up a table of actuarial terms and their translation for statisticians.  I had thought that it was a uniquely actuarial trait to use different names compared to other disciplines.  It turns out that statisticians are almost as guilty.
Written by: Stephen RichardsTags: Filter information matrix by tag: hazard function, Filter information matrix by tag: information matrix, Filter information matrix by tag: score function, Filter information matrix by tag: log-likelihood

Dealing with missing data

In an earlier post we looked at how to create a proxy for ill-health early retirements based on age at commencement.  This is an example of dealing with missing data — we infer a useful proxy to replace the lost or missing health status at retirement.
Written by: Stephen RichardsTags: Filter information matrix by tag: missing data

Pension-fund socialism

In an earlier posting we looked at several examples where a pension scheme dominates the picture of the company's finances and value.
Written by: Stephen RichardsTags: Filter information matrix by tag: pension schemes

Special assignment

We talked previously about the use of user-defined validation rules to clean up specific data artefacts you sometimes find in portfolio data. One question came up recently about modelling bespoke benefit bands, and this can also benefit from user-defined rules.
Written by: Gavin RitchieTags: Filter information matrix by tag: technology, Filter information matrix by tag: data validation, Filter information matrix by tag: deduplication