Search Results - subject:"RATE-MAKING"

Analyzing size of loss frequency distribution patterns : uncovering the impact of the COVID-19 pandemic

Xie, Shengkun; Li, Yuanshun - In: Risks : open access journal 12 (2024) 2, pp. 1-19

This study delves into a critical examination of the Size of Loss distribution patterns in the context of auto insurance during pre- and post-pandemics, emphasizing their profound influence on insurance pricing and regulatory frameworks. Through a comprehensive analysis of the historical Size of...

Persistent link: https://www.econbiz.de/10014497328

Unified spatial clustering of territory risk to uncover impact of COVID-19 pandemic on major coverages of auto insurance

Xie, Shengkun; Ho, Nathaniel - In: Risks : open access journal 12 (2024) 7, pp. 1-22

This research delves into the fusion of spatial clustering and predictive modeling within auto insurance data analytics. The primary focus of this research is on addressing challenges stemming from the dynamic nature of spatial patterns in multiple accident year claim data, by using spatially...

Persistent link: https://www.econbiz.de/10014637191

Estimating territory risk relativity using generalized linear mixed models and fuzzy C-Means clustering

Xie, Shengkun; Gan, Chong - In: Risks : open access journal 11 (2023) 6, pp. 1-20

benchmarks used in rate filings within the regulation process. It also provides guidance for auto insurance companies on rate … making. …

Persistent link: https://www.econbiz.de/10014334432

Estimating risk relativity of driving records using generalized additive models : a statistical approach for auto insurance rate regulation

Xie, Shengkun - In: Asia-Pacific journal of risk and insurance : APJRI 18 (2024) 1, pp. 55-86

Persistent link: https://www.econbiz.de/10014531203

Improving explainability of major risk factors in artificial neural networks for auto insurance rate regulation

Xie, Shengkun - In: Risks 9 (2021) 7, pp. 1-21

In insurance rate-making, the use of statistical machine learning techniques such as artificial neural networks (ANN … complicated models are used. Furthermore, from both rate-making and rate-regulation perspectives, it is critical to investigate …

Persistent link: https://www.econbiz.de/10013200792

Improving explainability of major risk factors in artificial neural networks for auto insurance rate regulation

Xie, Shengkun - In: Risks : open access journal 9 (2021) 7, pp. 1-21

Persistent link: https://www.econbiz.de/10012598958

Classification of territory risk by generalized linear and generalized linear mixed models

Xie, Shengkun; Gan, Chong - In: Journal of management analytics 10 (2023) 2, pp. 223-246

Persistent link: https://www.econbiz.de/10014319505

Defining geographical rating territories in auto insurance regulation by spatially constrained clustering

Xie, Shengkun; Esposito, Emilio Xavier - In: Risks 7 (2019) 2, pp. 1-20

Territory design and analysis using geographical loss cost are a key aspect in auto insurance rate regulation. The major objective of this work is to study the design of geographical rating territories by maximizing the within-group homogeneity, as well as maximizing the among-group...

Persistent link: https://www.econbiz.de/10013200460

Defining geographical rating territories in auto insurance regulation by spatially constrained clustering

Xie, Shengkun; Esposito, Emilio Xavier - In: Risks : open access journal 7 (2019) 2/42, pp. 1-20

Persistent link: https://www.econbiz.de/10012019293

Estimating major risk factor relativities in rate filings using generalized linear models

Xie, Shengkun; Lawniczak, Anna T. - In: International Journal of Financial Studies 6 (2018) 4, pp. 1-14

Predictive modeling is a key technique in auto insurance rate-making and the decision-making involved in the review of …

Persistent link: https://www.econbiz.de/10011996152