The School of Humanities and Social Sciences at the University of Cambridge worked with Aviva UK to explore how artificial intelligence could be used to predict life expectancy and future mortality trends, and discover innovation opportunities for insurance products and services.
The company
Aviva works with millions of customers and offers a range of insurance and savings products – from car, home and health insurance to pensions and investments. They are also the founding partner of the Cambridge Centre for Data-Driven Discovery (C2D3), a new interdisciplinary research centre at the University of Cambridge.
The challenge
C2D3 aims to bring together expertise from across academic departments and industry to drive research into the analysis, understanding and use of big data. This collaborative relationship with the university has been set up in order to help solve the big customer and business problems that the company faces now, or will face in the future.
Aviva is focussing on four main challenges, ethics, health including ageing, savings, and product innovations for specific social groups. They are looking to utilise principles and methodologies of data science and artificial intelligence to understand these areas better and ideally capture the maximum value for the business. They hope to identify opportunities to develop suitable, innovative offerings for their customers based on future trends.
The process
A one-day workshop was organised involving a team from Aviva, a team from Cambridge ESRC DTP-IAA, and the lead academics from different departments of the University of Cambridge, as well as from RAND Europe and Alan Turing Institute. The workshop participants explored one main question:
“How can artificial intelligence and data help to understand which factors are predictive of a persons’ health and longevity, and help with exploring the overall levels, trends and differences for discrete groups of the population?”
This contribution by Konstantina Stamati, Cambridge Grand Challenges Director, supported the group’s objective of gaining insights into the relevant problems in the areas of predicting life expectancy and future mortality trends as well as identifying new trends and drivers for health services in the UK.
An exchange between the academic and industrial participants was tasked with identifying potential R&D collaboration opportunities between the company and the University of Cambridge Grand Challenges team. Prioritization and exploration of the identified opportunities were in the focus of the second part of the workshop.
The results
Outputs from the workshop included a clarified and agreed view on the priorities across different trends and drivers that emphasise the need for action from Aviva. Based on the long list of the trends and drivers participants selected eight trends and drivers which are feasible to evaluate and to monitor.
Such trends and drivers are for example digital health records, diet, data from smart devices like walking speed, and sleep patterns. Therefore, these trends and drivers could be used as input data in simulation models.
Three research and development projects for the topic were elaborated. These projects address the priority trends and drivers and lead to gaining insights towards an answer of the overall question. A scoping activity helped to specify the project objectives and outcomes as well as covering possible implementation pathways.
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