A new mortality model using science and the views of medical experts will help to improve life expectancy predictions, Willis Towers Watson claims.

The PulseModel, incorporates the impact of medical conditions, such as diabetes, to inform future mortality patterns and is designed to help insurance companies and pension funds accurately price insurance cover, calculate liabilities and manage risk.

According to Willis Towers Watson, PulseModel can be used by insurers to consider future longevity trends more scientifically and set assumptions accordingly. Outputs from the model indicate that longevity improvements will be lower in future, averaging of the order of 1% annually, in contrast to typical current assumptions of over 1.5% per cent improvements annually.

The model is based around seven main disease groups: heart disease, diabetes, cancer, stroke, respiratory, digestive/renal, and neurological (plus common comorbidities).

Matthew Edwards, head of mortality and longevity in Willis Towers Watson’s life insurance practice, said: “We have been concerned for some time that the mortality models in common use do not properly incorporate medical information – such as whether people are healthy or have some disease history – quite apart from lifestyle information such as smoking status or basic medical markers.”

The aim is to quantify the scale of the diabetes epidemic facing the UK while highlighting how lifestyle and medical markers will influence its spread.

Dr. James Brown, lecturer in ageing metabolism, Aston Research Centre For Healthy Ageing, Aston University, said: “Type 2 diabetes is indisputably one of the gravest health issues facing us in the 21st century. Prediction of the future burden of diabetes has previously been poor, with trend-based analysis providing predictions that frequently underestimate disease burden.

“This model represents a potential step-change in our ability to accurately predict outcomes based upon the likely future trends in diabetes incidence and more importantly it provides quantifiable predictions of the potentially dramatic implications that diabetes might have on mortality and life expectancy.”

The company suggested that elevated improvement assumptions have been largely due to regulatory pressure which - in conjunction with the current structure of UK annuities – has been effectively forcing insurers to overprice. It asserted that the effect of this forced overpricing could reduce by around 2% the annual amount received by a 60-year-old on a typical annuity.

Mr Edwards said: “What is clear from our research and the development of this new model is that we can no longer rely only on an extrapolative approach to setting longevity improvement assumptions which ignores medical views. Such approaches can give results detached from medical and biological reality and add a layer of cost which the man on the street ends up paying.”