Bridging the gap between risk and uncertainty in insurance

Abstract

This contribution evokes Orio Giarini’s courage to think ‘outside the box’. It proposes a practical way to bridge the gap between risk (where probabilities of occurrence are fully known) and uncertainty (where these probabilities are unknown). However, in the context of insurance, neither extreme applies: the risk type of a newly enrolled customer is not fully known, loss distributions (especially their tails) are difficult to estimate with sufficient precision, the diversification properties of a block of policies acquired from another company can be assessed only to an approximation, and rates of return on investment depend on decisions of central banks that cannot be predicted too well. This contribution revolves around the launch of an innovative insurance product, where the company has a notion of whether a favourable market reception is more likely than an unfavourable one, of the chance of obtaining approval from the regulatory authority and the risk of a competitor launching a similar innovation. Linear partial information theory is proposed and applied as a particular practical way to systematically exploit the imprecise information that may exist for all of these aspects. The decision-making criterion is maxEmin, an intuitive modification of the maximin rule known from games against nature.

An efficient stopping rule for mitigating risk factors: Applications in pharmaceutical and generalized green supply chains

“…In such a system, there is usually limited or no information about the attack events. Zweifel (2021) used linear partial information theory to deal with imprecise information in the insurance domain where the risk profile of a newly enrolled customer is not fully known.…”

Examining insurance companies’ use of technology for innovation

“…COVID-19 acted as a catalyst for innovation in insurance, as in other service industries (Heinonen and Strandvik 2020 ), although the insurance industry is generally known for its conservatism (Nam 2018 ). The sector is, so far, clearly struggling with innovation and change (Zweifel 2021 ; Nam 2018 ), and insurance companies are not taking full advantage of the intangible nature of their products and services, which could enable them to become digital leaders (Stoeckli et al 2018 ), despite several efforts having been made. Data abundancy has facilitated the emergence of new insurance business models, ranging from peer-to-peer insurance (Stoeckli et al 2018 ) and personalisation achieved through wearable devices (McCrea and Farrell 2018 ; McFall 2019 ) to insurance policies tailored to individual behaviour (Dijksterhuis et al 2016 ), such as pay-how-you-drive (PHYD) policies, where pricing reflects driving style (Stoeckli et al 2018 ).…”