Risk classification with on‐demand insurance

Braun, Alexander; Haeusle, Niklas; Thistle, Paul D.

doi:10.1111/jori.12429

Cited by 3 publications

(1 citation statement)

References 23 publications

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“…While there is some literature on specific business models such as on-demand insurance (Braun et al, 2023;Zeier-Röschmann et al, 2022), usage-based insurance (Che et al, 2022;Holzapfel et al, 2023) or the impact of artificial intelligence on business model transformation…”

Section: Introductionmentioning

confidence: 99%

InsurTech in the United States and Germany—What are the drivers behind the different business models?

Oletzky

2023

Risk Manage Insurance Review

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Comparing the InsurTech ecosystems of the United States and Germany (Europe), there are significant regional differences in the choice of business models. While many InsurTechs in the United States have opted for the business model of a fully licensed insurer, this business model is much less common in Europe. In Europe, many InsurTechs seem to shy away from applying for a license as an insurer and limit themselves to the business model of a broker or a managing general agent. This paper analyzes the factors that influence an InsurTech's choice of business model when deciding whether or not to apply for an insurance license. It examines the impact of different local market environments on these decisions, as well as the role that access to venture capital plays in business model decisions and how regulators and their actions influence the decision‐making process.

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Section: Introductionmentioning

confidence: 99%

InsurTech in the United States and Germany—What are the drivers behind the different business models?

Oletzky

2023

Risk Manage Insurance Review

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A valorization framework to strategically manage data for creating competitive value

Bonvino,

Giorgino

2024

International Journal of Production Economics

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Big data, risk classification, and privacy in insurance markets

Eling,

Gemmo,

Guxha

et al. 2024

Geneva Risk Insur Rev

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The development of new technologies and big data analytics tools has had a profound impact on the insurance industry. A new wave of insurance economics research has emerged to study the changes and challenges those big data analytics developments engendered on the insurance industry. We provide a comprehensive literature review on big data, risk classification, and privacy in insurance markets, and discuss avenues for future research. Our study is complemented by an application of the use of big data in risk classification, considering individuals' privacy preferences. We propose a framework for analyzing the trade-off between the accuracy of risk classification and the discount offered to policyholders as an incentive to share private data. Furthermore, we discuss the conditions under which using policyholders' private data to classify risks more accurately is profitable for an insurer. In particular, we find that improving the accuracy of risk classification, if achieved by requiring the use of private data, does not necessarily provide an incentive for insurers to create more granular risk classes.

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Risk classification with on‐demand insurance

Cited by 3 publications

References 23 publications

InsurTech in the United States and Germany—What are the drivers behind the different business models?

InsurTech in the United States and Germany—What are the drivers behind the different business models?

A valorization framework to strategically manage data for creating competitive value

Big data, risk classification, and privacy in insurance markets

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