Our work

Innovation in Over 50 Marketing

The Brief

More Metrics teamed up with REaD Group , one of the UK's leading data providers, to address a number of long established issues with this particular type of insurance plan.

Over 50 insurance plans as they are generally known by, provide modest levels of life assurance cover for people over aged50 but more typically in their 60s and 70s. The plans are designed to provide a lump sum, which can be used to meet funeral expenses, pay off any outstanding debts or simply leave a small legacy to the next generation. One of the major selling points of these plans is that they offer guaranteed acceptance with no medical questions asked or examinations required.

The key issue facing many insurers, and the one which REaD and More Mertics had been tasked to address was that because the plans guarantee to accept all applicants there was little scope to provide enhanced benefits, improved pricing or more targeted communications because so little information was known about the applicants. Simply asking questions was not an option because it would destroy the fundamental attraction of the product to consumers who might otherwise be put off applying.

The Output

More Metrics built sophisticated data models using freely available "open source" data. Most of the data is provided by the Government's Office for National Statistics and is derived typically from Census data and Government collected data on local area characteristics.

Because the data is open source, it is non personalized and therefore is not subject to the many restrictions in using personalized data and consequently much faster to implement. The models provide differentiated mortality scores for particular geographical areas, typically a group of post codes. With the addition of individual level data from REaD a more granular "individual" mortality score.

The scores can be represented as an adjusted mortality score (from standard assumptions used by insurers) or as a refined life expectancy.

The deployment of the models therefore addressed the principle issue facing insurers - how do I understand more about the types of lives they have already insured or accepting through their marketing programmes - but without adding in medical questions which would impact on the simplicity of the purchasing proposition.
And the model outcomes are significant. Typical differentiation in mortality of up to 3:1 ie a spread of adjusted mortality from 50% below to 50% above expected mortality has a material impact on pricing and profitability.

Actuarial analysis indicates that by deselecting the bottom 10% in terms of mortality from contact programmes can increase profitability by 15%. Similarly, identifying and selling to the best lives can enable premiums to be reduced by up to 20% without impacting on profitability.

Mortality scores can also be converted to estimates of "Biological age" which can be used for a wide range of purposes - from estimating likely long-term cash flow for a product to helping frame the communication strategy. For example, a 64 with the worst mortality is being undercharged and effectively paying the premium of a 60 year old.

This joint development has produced an innovative and easy to implement data solution across a wide range of life assurance and pension opportunities. Following the successful testing and application of the mortality model, REaD and More Metrics have developed a suite of lifestyle models and associated datasets and variables covering Smoking incidence, alcohol use, obesity and health estimates.