Updating Bonus–Malus Indexing Mechanism to Adjust Long-Term Health Insurance Premiums

Dizaji, Atefeh Kanani; Najafabadi, Amir T. Payandeh

doi:10.1080/10920277.2022.2110123

Cited by 2 publications

(1 citation statement)

References 23 publications

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“…When inflation is not considered in pricing, it causes insurance premiums to be below the real costs. This puts the sustainability of the business at risk (Dizaji and Payandeh Najafabadi 2022). Thus, ignoring inflation can lead to imbalances and financial losses between insurance companies and policyholders.…”

Section: Discussionmentioning

confidence: 99%

Insurtech in Europe: identifying the top investment priorities for driving innovation

Eti,

Dinçer,

Meral

et al. 2024

Financ Innov

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The purpose of this study is to determine the essential indicators to improve insurtech systems and select the most critical alternative to increase insurtech-based investments in European countries. A novel fuzzy decision-making model is generated by integrating entropy and additive ratio assessment (ARAS) techniques with spherical fuzzy sets. First, the indicators are weighted using spherical fuzzy entropy. Then, the alternatives are ranked using spherical fuzzy ARAS. The alternatives are also ranked with the spherical fuzzy technique for order of preference by similarity to the ideal solution methodology. The main contribution of this study is that it would help investors to take the right actions to increase the performance of insurtech investments without incurring high costs. Another important novelty is that a new fuzzy decision-making model is proposed to solve this problem. The results of the two models are quite similar, proving the validity and coherency of the findings. It is found that pricing is the most critical factor that affects the performance of insurtech investments. Insurtech companies are required to make accurate pricing by conducting risk analyses to increase their profits and minimize their risks. Additionally, according to the ranking results, big data are the most appropriate way to improve the performance of insurtech investments in Europe. Big data analytics helps companies learn more about the behavior of their customers. By analyzing data about their customers’ past transactions, companies can provide more convenient services to them. This would increase customer satisfaction and enable companies to achieve long-term customer loyalty.

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Section: Discussionmentioning

confidence: 99%

Insurtech in Europe: identifying the top investment priorities for driving innovation

Eti,

Dinçer,

Meral

et al. 2024

Financ Innov

View full text Add to dashboard Cite

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Weekly dynamic motor insurance ratemaking with a telematics signals bonus-malus score

Yanez,

Guillén,

Nielsen

2024

ASTIN Bull.

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We present a dynamic pay-how-you-drive pricing scheme for motor insurance using telematics signals. More specifically, our approach allows the insurer to apply penalties to a baseline premium on the occurrence of events such as hard acceleration or braking. In addition, we incorporate a bonus-malus system (BMS) adapted for telematics data, providing a credibility component based on past telematics signals to the claim frequency predictions. We purposefully consider a weekly setting for our ratemaking approach to benefit from the signal’s high-frequency rate and to encourage safe driving via dynamic premium corrections. Moreover, we provide a detailed structure that allows our model to benefit from historical records and detailed telematics data collected weekly through an onboard device. We showcase our results numerically in a case study using data from an insurance company.

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Updating Bonus–Malus Indexing Mechanism to Adjust Long-Term Health Insurance Premiums

Cited by 2 publications

References 23 publications

Insurtech in Europe: identifying the top investment priorities for driving innovation

Insurtech in Europe: identifying the top investment priorities for driving innovation

Weekly dynamic motor insurance ratemaking with a telematics signals bonus-malus score

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