AI: Coming of age?

Maynard, Trevor; Baldassarre, Luca; Montjoye, Yves-Alexandre de; McFall, Liz; Óskarsdóttir, María

doi:10.1017/s1748499521000245

Cited by 4 publications

(2 citation statements)

References 17 publications

(14 reference statements)

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“…Insurance affordability is a key determinant of societal progress, with the modelling of insurance pricing practices playing a key role in this affordability (Daniels 2011), with actuarially fair pricing of insurance premiums allowing for a population to access insurance at rates which they can reasonably afford (Grant 2012). Transparency and explainability of AI models are core requirements to achieve impactful trustworthy AI in society (Felzmann et al 2019;Maynard et al 2022;Moradi and Samwald 2021). Trustworthiness is a core concept within the insurance industry, with enhanced XAI explanations directly affecting trust levels amongst insurance companies and their stakeholders.…”

Section: Introductionmentioning

confidence: 99%

Explainable Artificial Intelligence (XAI) in Insurance

Owens

Sheehan

Mullins

et al. 2022

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Explainable Artificial Intelligence (XAI) models allow for a more transparent and understandable relationship between humans and machines. The insurance industry represents a fundamental opportunity to demonstrate the potential of XAI, with the industry’s vast stores of sensitive data on policyholders and centrality in societal progress and innovation. This paper analyses current Artificial Intelligence (AI) applications in insurance industry practices and insurance research to assess their degree of explainability. Using search terms representative of (X)AI applications in insurance, 419 original research articles were screened from IEEE Xplore, ACM Digital Library, Scopus, Web of Science and Business Source Complete and EconLit. The resulting 103 articles (between the years 2000–2021) representing the current state-of-the-art of XAI in insurance literature are analysed and classified, highlighting the prevalence of XAI methods at the various stages of the insurance value chain. The study finds that XAI methods are particularly prevalent in claims management, underwriting and actuarial pricing practices. Simplification methods, called knowledge distillation and rule extraction, are identified as the primary XAI technique used within the insurance value chain. This is important as the combination of large models to create a smaller, more manageable model with distinct association rules aids in building XAI models which are regularly understandable. XAI is an important evolution of AI to ensure trust, transparency and moral values are embedded within the system’s ecosystem. The assessment of these XAI foci in the context of the insurance industry proves a worthwhile exploration into the unique advantages of XAI, highlighting to industry professionals, regulators and XAI developers where particular focus should be directed in the further development of XAI. This is the first study to analyse XAI’s current applications within the insurance industry, while simultaneously contributing to the interdisciplinary understanding of applied XAI. Advancing the literature on adequate XAI definitions, the authors propose an adapted definition of XAI informed by the systematic review of XAI literature in insurance.

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Section: Introductionmentioning

confidence: 99%

Explainable Artificial Intelligence (XAI) in Insurance

Owens

Sheehan

Mullins

et al. 2022

Risks

View full text Add to dashboard Cite

show abstract

“…Through a shared IT infrastructure between suppliers, manufacturers, distributors, retailers, auditors, consumers and, of course, insurers 3 , blockchain technology enabled a considerable growth in supply chain management. Furthermore, the big data revolution, accompanied by machine learning and neural networks, poses new challenges to the actuarial profession (Wüthrich & Merz, 2019;Maynard et al, 2022). So much so that top management in some insurance companies has voiced the need to increasingly replace actuaries by data scientists; this is "Another brick in the wall" (thank you Pink Floyd) we as a profession cannot allow to fall.…”

mentioning

confidence: 99%