We believe collaborations with academia to be key to our company, and indeed to our industry. While this might seem an entirely uncontroversial statement for an innovation-driven company, I once heard during an insurance conference that the sector should “stop seeking academics’ help to solve its problems,” and that the industry should “come up with its own solutions.”  The reality is that many people in our sector are not collaborating, with academics or with each other, which has led to an isolated and fragmented cat risk modelling community. I would argue that taking the isolationist path gives rise to under-utilisation of the vast body of scientific knowledge generated by academics and their intellectual resources. The science of natural hazards is a very active and prolific research field, as testified by the over 800 submissions to the natural hazards section at the upcoming AGU Fall Meeting this year. 

 

However, productive collaborations are not easy. Professor of hydrology and atmospheric sciences at the University of Arizona Xubin Zeng rightly points out that, to make the widespread scientific knowledge in the area of natural hazards useful for the re/insurance sector, academic researchers need to know more regarding the models currently in use. He also argues that the re/insurance industry is slowing the development of cat models by not seeking more interactions with academics[1]. Fortunately, pleas for the establishment of more links between academia and the re/insurance sector come from both parties. From the industrial side, Dickie Whitaker regularly calls with passion for the industry to create closer ties with academia in order to improve its understanding of the systemic risks that societies face both today and in a changing climate. The Lighthill Risk Network, headed by Dickie, helps to steer the sector in this direction by identifying key research priorities[2] and providing funding for collaborative research projects. 

  

Academics have strong incentives to work with industry. For example, REF (Research Excellence Framework) impact case studies reward academic research that leads to industrial impact, the latter being defined as "an effect on, change or benefit to the economy, society, culture, public policy or services, health, the environment or quality of life, beyond academia"[3]. Furthermore, government funding provided by UK Research and Innovation (UKRI) supports the development of industrial impact through the sharing of knowledge and expertise between academia and industry. It is important to recognise that although academics are subject-matter experts, deep expertise in the industry sector of interest is needed for the knowledge to be made meaningfully applicable in industry. Particularly relevant schemes, which strive to overcome the so called “valley of death”[4] (the gap between research development and industrial uptake) by transferring academic-produced scientific knowledge directly to businesses, are Impact Acceleration Accounts, Knowledge Exchange Fellowships and Knowledge Transfer Partnerships. 

 

From the industry perspective, some of the benefits of working with academics could be (i) increased profitability (via the cost savings achieved by making processes easier or faster, or through increased profit due to better pricing), (ii) a competitive advantage from employing new scientific techniques, and (iii) reputational advantage[5], as working with academics can be seen as a guarantee that the company’s products and services are based on state-of-the-art knowledge. There are also fields of study relevant to the re/insurance sector that are inherently interdisciplinary and could hardly be tackled by a single company. An example is decision-making under uncertainty, which is studied by mathematicians, economists, philosophers and psychologists, among others. Although a lot of research has already been done in this field, what is missing to be useful for insurers is an attachment to a business-specific end-point within the industry. This is one area that Max Info is working on with philosophers at the London Schools of Economics and risk modelers at Reask on a project funded by the Lighthill Risk Network.  

 

While we have mentioned some of the incentives to collaborate on both sides it is, of course, important to point out that there are hurdles too, such as differences in language, working cultures and time frames[5]. On the latter, industry usually works on shorter time-frames than academia, often with daily business deliverables, quarterly requirements for financial reporting [6], and meeting short-term goals more important for career progression. Conversely, academics work on a long-term discovery and creation process. When setting up a collaboration with academics it is essential to take these differences into account, and to align objectives and be clear about the expectations from both sides. Note that long-term collaborations are often built one step at a time. They might not start with a large-scale grant proposal, but rather as less ambitious exchanges of training, high quality data, models and tools. Such exchanges might go in either direction. For example, academics might provide consultancy services of limited scope, while practitioners and academics might be asked to take advisory roles at a university or a panel, respectively.  

 

In addition to the above-mentioned Lighthill Risk Network, there are already some very good initiatives in the re/insurance sector that strive to close the gap between the two worlds, such as the Willis Research Network, the AXA Research Fund, the Aon Research Forum, the new Gallagher Research Centre and the UK Centre for Greening Finance and Investment. At Maximum Information we are encouraging the sector to continue moving in this direction, as we consider collaborative projects the company’s cornerstone and necessary to democratise risk modelling. In turn, this will produce transparent and cost-effective baselines and methodologies to enhance societal resilience to natural hazards. 

 

 

 

References 

[1] https://www.theinsurer.com/tv/xubin-zeng-limited-collaboration-with-academia-is-slowing-development-of-cat-models/24401.article 

[2] Lighthill Risk Network Report (2020) Improving Impact – Building better links between insurance and academia 

[3] McLellan, T. (2021). Impact, theory of change, and the horizons of scientific practice. Social Studies of Science, 51(1), 100–120. https://doi.org/10.1177/0306312720950830. 

[4] Markham, S.K. et al. (2010) “The valley of death as context for role theory in product innovation,” Journal of Product Innovation Management, 27(3), pp. 402–417. https://doi.org/10.1111/j.1540-5885.2010.00724.x. 

[5] Hillier, J. K., Saville, G. R., Smith, M. J., Scott, A. J., Raven, E. K., Gascoigne, J., … & Craig, J. (2019) Demystifying academics to enhance university–business collaborations in environmental science. Geosci. Commun., 2, 1–23, https://doi.org/10.5194/gc-2-1-2019. 

[6] Bellefeuille, J. H. & Rice, J. B. (2002) A Job Fit for Evel Knievel: Jumping the Canyon of Academia-To-Industry Knowledge Transfer. IEEE International Engineering Management Conference Cambridge, UK, pp. 629–634. doi: 10.1109/IEMC.2002.1038509.