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Key Research Challenges

Building better links between insurance and academia will improve the impact of cutting edge risk research.

Key Research Themes & Challenges

Often dubbed the ‘DNA of capitalism’, insurance is the business of understanding and mitigating the changing risks that societies and economies face, ultimately helping build societal and economic resilience.

To deliver on this vision, however, the industry needs to communicate the value of insurance and ensure it delivers the right products, to the right people, at the right time – and to achieve this we need research and knowledge on the topic of risk. From looking at how we can improve the risk models that the industry uses to assess and price risk, to understanding how we can make research more relevant to decision makers, the areas for progress are vast.

These are just a few of the questions and problem areas that form the key research challenges for insurers and academics to address, the main ones of which, we have summarised below.

This list is not exhaustive and we of course welcome new ideas and feedback.

    Hydrological & Atmospheric Risk

    Hydrological & Atmospheric Risk

    Hydrological and atmospheric risks are particularly challenging for insurers to model – losses are rising, and the risks are evolving thanks to trends such as urbanisation, more buildings in exposed areas, failed land-use practices, and climate change.

    To tackle this, the insurance industry must work more closely together with the academic sector to improve physical process understanding and risk modelling.

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    Climate
    Change Risk

    Climate Change Risk

    As the effects of climate change become more severe, catastrophe risk modelling is more relevant than ever. But while scientists have gained much more confidence evaluating how climate change may affect an extreme weather event over the last 15 years, much of current insurance risk modelling is based on the assumption of a stable climate.

    The re/insurance sector must have direct links to cutting edge research into the impacts of climate change in order to effectively model this evolving risk.

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    Emerging Technology and Cyber Risk

    Emerging Technology and Cyber Risk

    Underwriting cyber risk has become a major challenge for many re/insurers trying to make informed decisions about a risk that can be hard to evaluate. The ability to describe the problem in consistent terminology is essential, to allow comparisons between scenarios and threats.

    Re/insurers would benefit enormously from research into a standardised terminology framework for cyber incidents, as well as a consolidated data set of major historic cyber loss events.

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    Resilient economies and complex systems

    Resilient economies and complex systems

    The concept of resilience is becoming a key criteria in business and investment decisions.

    There is a clear gap for researchers to work with insurers to support the development of innovative tools to assess risk and resilience, and provide a clearer framework for embedding resilience into decision making for businesses and governments.

    The research community can also enable access to data, models and expertise which can be further developed by business into protectable IP on which to base risk assessments and resilience services.

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    Decision making under uncertainty

    Decision making under uncertainty

    A fair volume of research has already taken place in the field of decision making under uncertainty, but elements are missing or are not directly useful to insurance. Across academia, different disciplines consider uncertainty separately, with no joined up standardised framework or common language to communicate and correlate results.

    In order to improve the impact of future research, it would be hugely helpful to deconstruct the challenge and gain an oversight of what is missing, and what areas of new work should be pursued next.

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    The risk of risk modelling

    The risk of risk modelling

    The re/insurance industry strives to continually strengthen the predictive power of its catastrophe modelling capabilities.

    Researchers can support insurers by helping them to harness the data they hold to  develop global databases of standardised information, such as a worldwide buildings database using unique building identification, for example, as well as with efforts to compare different models.

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