Results 11 to 20 of about 6,133 (181)
Journal of Mathematics, 2021 During the process of jujube planting, there are not only natural risks caused by natural disasters but also market risks caused by price factors. In the study, firstly, wavelet analysis method was used to stabilize the jujube yield per unit area and the
Li-Mei Qi +6 more
doaj +2 more sources
The Future of Road Safety: Challenges and Opportunities. [PDF]
Milbank Q, 2023 Policy Points Traditional approaches to addressing motor vehicle crashes are yielding diminishing returns. A comprehensive strategy known as the Safe Systems approach shows promise in both advancing safety and equity and reducing motor vehicle crashes. In addition, a range of emerging technologies, enabled by artificial intelligence, such as automated ...
Ehsani JP, Michael JP, MacKENZIE EJ.
europepmc +2 more sources
Multiple Bonus–Malus Scale Models for Insureds of Different Sizes
Risks, 2022 How to consider the a priori risks in experience-rating models has been questioned in the actuarial community for a long time. Classic past-claim-rating models, such as the Buhlmann–Straub credibility model, normalize the past experience of each insured ...
Jean-Philippe Boucher
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mSHAP: SHAP Values for Two-Part Models
Risks, 2021 Two-part models are important to and used throughout insurance and actuarial science. Since insurance is required for registering a car, obtaining a mortgage, and participating in certain businesses, it is especially important that the models that price ...
Spencer Matthews, Brian Hartman
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Machine Learning in P&C Insurance: A Review for Pricing and Reserving
Risks, 2020 In the past 25 years, computer scientists and statisticians developed machine learning algorithms capable of modeling highly nonlinear transformations and interactions of input features.
Christopher Blier-Wong +3 more
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Risk classification with on‐demand insurance
Journal of Risk and Insurance, Volume 90, Issue 4, Page 975-990, December 2023., 2023 Abstract On‐demand insurance is an innovative business model from the InsurTech space, which provides coverage for episodic risks. It makes use of a simple fact in a practical way: People differ in their frequency of exposure as well as the probability of loss.
Alexander Braun +2 more
wiley +1 more source
Approximation of Zero-Inflated Poisson Credibility Premium via Variational Bayes Approach
Risks, 2022 While both zero-inflation and the unobserved heterogeneity in risks are prevalent issues in modeling insurance claim counts, determination of Bayesian credibility premium of the claim counts with these features are often demanding due to high ...
Minwoo Kim, Himchan Jeong, Dipak Dey
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Improving risk classification and ratemaking using mixture‐of‐experts models with random effects
Journal of Risk and Insurance, Volume 90, Issue 3, Page 789-820, September 2023., 2023 Abstract In the underwriting and pricing of nonlife insurance products, it is essential for the insurer to utilize both policyholder information and claim history to ensure profitability and proper risk management. In this paper, we apply a flexible regression model with random effects, called the Mixed Logit‐weighted Reduced Mixture‐of‐Experts, which ...
Spark C. Tseung +4 more
wiley +1 more source
Ratemaking Model of Usage Based Insurance Based on Driving Behaviors Classification
International Journal of Crowd Science, 2022 Based on the present situation of usage based insurance (UBI) research and application, this paper puts forward the UBI rating model based on driving behavior classification, and applies the technology of data mining to the evaluation of driving behavior.
Zhishuo Liu, Mengjun Hao, Fang Tian
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Who captures whom? Regulatory misperceptions and the timing of cognitive capture
Regulation &Governance, Volume 17, Issue 1, Page 43-60, January 2023., 2023 Abstract To explain cognitive capture, economic sociologists often examine the structure of relationships between regulators and market participants. This paper argues that the nature of regulators' misperception should be subject to analysis as well. Different types of misperceptions develop over timelines of varying lengths.
Georg Rilinger
wiley +1 more source