Abstract. In countries globally there is intense political interest in fostering effective university–business collaborations, but there has been scant attention devoted to exactly how an individual scientist's workload (i.e. specified tasks) and incentive structures (i.e. assessment criteria) may act as a key barrier to this. To investigate this an original, empirical dataset is derived from UK job specifications and promotion criteria, which distil universities' varied drivers into requirements upon academics. This work reveals the nature of the severe challenge posed by a heavily time-constrained culture; specifically, tension exists between opportunities presented by working with business and non-optional duties (e.g. administration and teaching). Thus, to justify the time to work with business, such work must inspire curiosity and facilitate future novel science in order to mitigate its conflict with the overriding imperative for academics to publish. It must also provide evidence of real-world changes (i.e. impact), and ideally other reportable outcomes (e.g. official status as a business' advisor), to feed back into the scientist's performance appraisals. Indicatively, amid 20–50 key duties, typical full-time scientists may be able to free up to 0.5 day per week for work with business. Thus specific, pragmatic actions, including short-term and time-efficient steps, are proposed in a “user guide” to help initiate and nurture a long-term collaboration between an early- to mid-career environmental scientist and a practitioner in the insurance sector. These actions are mapped back to a tailored typology of impact and a newly created representative set of appraisal criteria to explain how they may be effective, mutually beneficial and overcome barriers. Throughout, the focus is on environmental science, with illustrative detail provided through the example of natural hazard risk modelling in the insurance sector. However, a new conceptual model of academics' behaviour is developed, fusing perspectives from literature on academics' motivations and performance assessment, which we propose is internationally applicable and transferable between sectors. Sector-specific details (e.g. list of relevant impacts and user guide) may serve as templates for how people may act differently to work more effectively together.

Abstract. In countries globally (e.g. UK, Australia) there is intense political interest in fostering effective universitybusiness collaborations, but there has been scant attention devoted to exactly how individual scientists' workload (i.e. specified tasks) and incentive structures (i.e. assessment criteria) may act as a key barrier to this. To investigate this an original, empirical dataset is derived from UK job specifications and promotion criteria, which distil universities' varied drivers into requirements upon academics. This reveals the nature of the severe challenge posed by a heavily time-35 constrained culture; specifically, a tension exists between opportunities presented by working with industry and non-optional duties (e.g. administration, teaching). Thus, to justify the time to work with industry, such work must inspire curiosity and facilitate future novel science in order to mitigate its conflict with the overriding imperative for academics to publish. It must also provide evidence of real-world changes (i.e. impact), and ideally other reportable outcomes (e.g. official status as a business' advisor), to feed back into the scientist's performance appraisals. Indicatively, amid 20-50 key duties, scientists 40

Recent advances in numerical weather prediction, combined with the new generation, high‐resolution climate simulations, and open‐source loss modeling frameworks, herald a move beyond the limited statistical representation of catastrophe risk based on past observations. In this new forward‐looking view of risk, an appreciation that our observed record of past natural catastrophes represents a limited sample of possible events, and that the statistics of weather and climate are changing as the planet warms, highlights a key limitation in traditional catastrophe modeling approaches that are built on defining statistical relationships using the observed record. Instead, ensembles of new spatially and dynamically consistent simulations of weather and climate provide physically plausible, but as‐yet‐unseen events at scales appropriate for making effective risk management and risk transfer decisions. This approach is especially useful in locations around the world where observational records are unobtainable or of short historical duration, such as in low‐income countries. We take a forward‐looking approach at the way that future catastrophe modeling and insurance underwriting could occur in response to these technological and scientific advances, using open‐source loss model frameworks.

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