The research team was led by Andrew Cairns, Professor of Actuarial Mathematics at Heriot-Watt University. 

Highlights of the research programme include:

• Sourcing of new datasets subdivided by socio-economic group. This work was key to addressing the main objectives of modelling and measuring socioeconomic differences in mortality. With the help of external collaborators, the Research Team developed or obtained datasets for England, Denmark, the US and Canada, helping researchers to gain considerable country-specific insights, as well as facilitating comparison of inequalities and dynamics in different countries. For example, the Danish data led to the conclusion that affluence was a better predictor of high or low mortality than education level.
   
• A significant bonus arising from these datasets was the development of the new Longevity Index for England (LIFE). This improves substantially on the alternative Index of Multiple Deprivation. The team developed a simple open access application which is being used to reach out to external stakeholders, as well as to provide a basic tool for actuaries. Over 50 actuaries volunteered to test the app, of which 30% provided feedback to the team. Actuaries and others can contact the team to access the full LIFE index. 
  
  
• Using these varied datasets, the Research Team was able to develop a new generation of multiple population mortality models, with a detailed comparison of alternative models covering the advantages and disadvantages of each. The team finally settled on a new version of the common age effect model (CAE) that has the flexibility to cover a wide range of potential populations. This analysis will become important to actuaries, with the increasing desire to measure longevity risk at the portfolio or pension-fund level accounting for differences between the specific population and the national population. 
  
  
• Considerable effort has also gone into developing datasets for the US and England by cause of death at the socio-economic level. This has led to new insights into the drivers of mortality improvements (or reversals) over the last 20-30 years. A specific element of this work is the link between specific causes of death and so-called controllable risk factors, such as smoking. Analysis leads to crucial but indirect inferences about differences, e.g. in smoking prevalence, over time and by socio-economic group. 
  
  
• The team published a key work on how to handle index-based longevity transactions in a Solvency-II-type setting. 
  
  
• Finally, the team has developed new models for analysing cancer morbidity and mortality with links to critical illness insurance (CII). CII claim rates have been rising but it has been found that they still fall below national cancer morbidity rates.

Professor Cairns describes some of the research highlights in this short video below