scholarly journals Generalized Linear Models in Vehicle Insurance

2014 ◽  
Vol 62 (2) ◽  
pp. 383-388 ◽  
Author(s):  
Silvie Kafková ◽  
Lenka Křivánková
Keyword(s):  
Risk Factors ◽  
Linear Models ◽  
Information Criterion ◽  
Insurance Premium ◽  
Insurance Companies ◽  
Predictor Variables ◽  
Estimation Of Parameters ◽  
Claim Frequency ◽  
Insurance Data ◽  
Selection Of

Actuaries in insurance companies try to find the best model for an estimation of insurance premium. It depends on many risk factors, e.g. the car characteristics and the profile of the driver. In this paper, an analysis of the portfolio of vehicle insurance data using a generalized linear model (GLM) is performed. The main advantage of the approach presented in this article is that the GLMs are not limited by inflexible preconditions. Our aim is to predict the relation of annual claim frequency on given risk factors. Based on a large real-world sample of data from 57 410 vehicles, the present study proposed a classification analysis approach that addresses the selection of predictor variables. The models with different predictor variables are compared by analysis of deviance and Akaike information criterion (AIC). Based on this comparison, the model for the best estimate of annual claim frequency is chosen. All statistical calculations are computed in R environment, which contains stats package with the function for the estimation of parameters of GLM and the function for analysis of deviation.

scholarly journals Impact De-Tarrification in Modeling Motor Insurance Premium in Malaysia

2019 ◽  
Vol 8 (3) ◽  
pp. 7394-7400
Keyword(s):  
Risk Factors ◽  
Insurance Industry ◽  
Risk Profile ◽  
Insurance Premium ◽  
Insurance Companies ◽  
Good Service ◽  
Motor Insurance ◽  
Premium Calculation ◽  
Rating Factor ◽  
The Impact

De-tariffication has become a hot topic for Malaysian motor insurers after effectively implemented on 1 July 2017. Generally, the insurance companies need to set a rating factor for their premium before calculating the price on selected premium. Typically, these rating factors are based on the risk profile of the policyholder. That means, the price of the premium determined by the risk factors from the profile of the policyholder. The aim of this research to investigate the impact after de-tariff implemented among the motor insurance industry. This research also investigates the effect of de-tariff on the Good Service Tax (GST) in the premium calculation. Multiple Linear Regression (MLR) was used to determine the most significant rating factor that influence the calculation of the premium received by the motor insurance industry. Once these k rating factors and parameters are identified, the value of premiums can be calculated by taking into account these rating factors and parameters in the de-tariff formula and comparing with the existing model. The result of the study indicates that de-tariff model has lower premium compared to Malaysia tariff model. Furthermore, GST is also found to have a significant impact on the motor insurance premium, where policyholders are required to pay higher premiums than non-GST premiums. The results will help the insurance companies to find new formulas in considering new rating factors and improve the accuracy of premium calculations.

scholarly journals IMPLEMENTASI METODE BAYES PADA PENGHITUNGAN PREMI ASURANSI KENDARAAN BERMOTOR

2020 ◽  
Vol 3 (2) ◽  
pp. 112-123
Author(s):  
Rika Fitriani ◽  
Gunardi Gunardi
Keyword(s):  
Historical Data ◽  
Motor Vehicle ◽  
Insurance Premium ◽  
Insurance Companies ◽  
Bayes Method ◽  
General Insurance ◽  
Pure Premium ◽  
Historical Data Analysis ◽  
Claim Frequency ◽  
Motor Vehicle Insurance

One type of general insurance is motor vehicle insurance. Premium pricing of general insurance can be calculated by some methods. In this study, Bayes method will be used. The distribution of claim frequency is Poisson distribution and the distribution of claim severity is Exponential distribution. The premium is calculated by multiplying the expectation of claim frequency and the expectation of claim severity. Based on the historical data analysis using the Bayes method, the highest pure premium of motor vehicle insurance in Indonesia is Hino brand and the lowest pure premium is Honda brand. The result of this premium pricing can be used as a reference for the insurance companies to manage their motor vehicle insurance reserves.

scholarly journals The Measures of Accuracy of Claim Frequency Credibility Predictor

2021 ◽  
Vol 13 (21) ◽  
pp. 11959
Author(s):  
Alicja Wolny-Dominiak ◽  
Tomasz Żądło
Keyword(s):  
Life Insurance ◽  
Mixed Models ◽  
Linear Mixed Models ◽  
Parametric Bootstrap ◽  
Credibility Theory ◽  
Insurance Companies ◽  
Green Technologies ◽  
Claim Frequency ◽  
Bootstrap Algorithm ◽  
Insurance Data

Nowadays, the sustainability risks and opportunities start to affect strongly insurance companies in regard to the resulting additional variability of future values of variables taken into account in the decision processes. This is important especially in the era of sustainable non-life insurance promoting, among others, the use of ecological car engines or ecological systems of building heating. The fundamental issue in non-life insurance is to predict future claims (e.g., the aggregate value of claims or the number of claims for a single policy) in a heterogeneous portfolio of policies taking account of claim experience. For this purpose, the so-called credibility theory is used, which was initiated by the fundamental Bühlmann model modified to the Bühlmann–Straub model. Several modifications of the model have been proposed in the literature. One of them is the development of the relationship between the credibility models and statistical mixed models (e.g., linear mixed models) for longitudinal data. The article proposes the use of the parametric bootstrap algorithm to estimate measures of accuracy of the credibility predictor of the number of claims for a single policy taking into account new risk factors resulting from the emergence of green technologies on the considered market. The predictor is obtained for the model which belongs to the class of Generalised Linear Mixed Models (GLMMs) and which is a generalization of the Bülmann–Straub model. Additionally, the possibility of predicting the number of claims and the problem of the assessment of the prediction accuracy are presented based on a policy characterized by new green risk factor (hybrid motorcycle engine) not previously present in the portfolio. The paper presents the proposed methodology in a case study using real insurance data from the Polish market.

Effect of explicit deposit insurance premium on the moral hazard of banks’ risk-taking: Around the globe

2018 ◽  
Vol 05 (02) ◽  
pp. 1850012
Author(s):  
Raheel Mumtaz ◽  
Imran Abbas Jadoon
Keyword(s):  
Moral Hazard ◽  
Risk Taking ◽  
Deposit Insurance ◽  
Linear Models ◽  
Banking System ◽  
Insurance Premium ◽  
Empirical Estimation ◽  
Negative Effect ◽  
Small Banks ◽  
Selection Of

The adoption of explicit deposit insurance increases the moral hazard of banks’ risk-taking, caused by the decrease in depositors’ discipline. Based on the contract theory, this study probes whether the inception of risk-based deposit insurance premium may limit the moral hazard of banks’ risk-taking triggered by the deposit insurance. This study conducted the analysis on 2,196 banks of 125 countries, covered by the Bankscope database from 2002 to 2014 period. The hierarchical linear models (HLM) were used for empirical estimation of research models. The findings revealed that risk-based deposit insurance premium deteriorated the moral hazard of banks’ risk-taking, incited by the enactment of explicit deposit insurance, while this effect was high for the small banks. Therefore, the small banks were more stable and positively affected by the selection of risk-based deposit insurance premium as compared to the larger counterparts. However, it cannot eliminate this negative effect completely. Hence, the implementation of the premium structure by policymakers on the finding of this study encouraged the depositors and investors’ confidence in the banking system around the globe.

scholarly journals Geographic Premium Rating by Whittaker Spatial Smoothing

2001 ◽  
Vol 31 (1) ◽  
pp. 147-160 ◽  
Author(s):  
Greg Taylor
Keyword(s):  
Sampling Error ◽  
Underlying Surface ◽  
Reliable Estimate ◽  
Spatial Smoothing ◽  
Numerical Example ◽  
Claim Frequency ◽  
Insurance Data ◽  
Selection Of

AbstractWhittaker graduation is applied to the spatial smoothing of insurance data. Such data (e.g. claim frequency) form a surface over the 2-dimensional geographic domain to which they relate. Observations on this surface are subject to sampling error. They need to be smoothed spatially if a reliable estimate of the underlying surface is to be obtained.A measure of smoothness of a surface has been defined. This has been incorporated in 2-dimensional Whittaker graduation to effect the necessary smoothing. The details of this are worked out in Section 4. The procedure is illustrated by numerical example in Section 5. The Bayesian interpretation of this form of spatial smoothing is discussed, and used to assist in the selection of the Whittaker relativity constant.

scholarly journals Modelling Claim Frequency in Insurance Using Count Models

2021 ◽  
pp. 14-20
Author(s):  
A. Adetunji Ademola ◽  
Shamsul Rijal Muhammad Sabri
Keyword(s):  
Bayesian Information Criterion ◽  
Regression Models ◽  
Negative Binomial ◽  
Predictive Ability ◽  
Information Criterion ◽  
Information Criteria ◽  
Binomial Model ◽  
Count Models ◽  
Claim Frequency ◽  
Insurance Data

Background: In modelling claim frequency in actuary science, a major challenge is the number of zero claims associated with datasets. Aim: This study compares six count regression models on motorcycle insurance data. Methodology: The Akaike Information Criteria (AIC) and the Bayesian Information Criterion (BIC) were used for selecting best models. Results: Result of analysis showed that the Zero-Inflated Poisson (ZIP) with no regressors for the zero component gives the best predictive ability for the data with the least BIC while the classical Negative Binomial model gives the best result for explanatory purpose with the least AIC.

scholarly journals Age differences of arterial trauma – Selection of the most appropriate age classification

2020 ◽  
Author(s):  
Vitaliy Petrov
Keyword(s):  
Age Differences ◽  
Linear Models ◽  
Information Criterion ◽  
Treatment Type ◽  
Wide Range ◽  
Arterial Trauma ◽  
Physical Activity Recommendations ◽  
Clinical Patterns ◽  
Selection Of

Introduction: Studies on age differences of arterial trauma (AT) carry significant methodological differences in terms of selection of the most appropriate age classification. Aim: This study aims to verify the most optimal age classification when comparing clinical patterns of the civil AT. Material and methods: 222 AT patients were identified from the Lviv Clinical Regional Hospital. In each case the following clinical patterns were identified: patient age, etiology, mechanism, AT type, topography, diagnostics mode, treatment type. Patients were distributed using six age classifications (Erikson 1950, UN 1989, Quinn 1994, Craig 2000, WHO physical activity recommendations 2010, by decades of life). Generalized linear models (GLMs) were created, with age distributions as predictors and clinical patterns as dependent factors. Akaike information criterion (AIK) was used to compare the quality of statistical sets. Results and discussion: Six GLMs were obtained, in each age of them age classifications were compared using the AIK. Rating list of age classifications was developed (starting with the most appropriate and ending with the least appropriate): E. Erikson (1950) → V. Quinn (1994) → G. Craig (2000) → UN (1989) → Decades → WHO (2010). Conclusions: Human development classifications may be preferable in assessing the age differences of AT in patients of wide range.

Cluster Analysis of Antigenic Profiles of Tumors: Selection of Number of Clusters Using Akaike’s Information Criterion

1990 ◽  
Vol 29 (03) ◽  
pp. 200-204 ◽  
Author(s):  
J. A. Koziol
Keyword(s):  
Cluster Analysis ◽  
Basic Problem ◽  
Information Criterion ◽  
Akaike's Information Criterion ◽  
Cell Surface Antigens ◽  
Number Of Clusters ◽  
Akaike’S Information Criterion ◽  
Multinomial Data ◽  
Tumor Types ◽  
Selection Of

AbstractA basic problem of cluster analysis is the determination or selection of the number of clusters evinced in any set of data. We address this issue with multinomial data using Akaike’s information criterion and demonstrate its utility in identifying an appropriate number of clusters of tumor types with similar profiles of cell surface antigens.

scholarly journals Assessment of the relationship between estimated cardiovascular risk and structural damage in patients with axial spondyloarthritis

2020 ◽  
Vol 12 ◽  
pp. 1759720X2098283
Author(s):  
María Lourdes Ladehesa-Pineda ◽  
Iván Arias de la Rosa ◽  
Clementina López Medina ◽  
María del Carmen Castro-Villegas ◽  
María del Carmen Ábalos-Aguilera ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cluster Analysis ◽  
Structural Damage ◽  
Disease Duration ◽  
Linear Models ◽  
Axial Spondyloarthritis ◽  
Subclinical Atherosclerosis ◽  
Intima Media Thickness ◽  
Atherosclerotic Plaques ◽  
Cross Sectional

Aims: To evaluate the association of estimated cardiovascular (CV) risk and subclinical atherosclerosis with radiographic structural damage in patients with axial spondyloarthritis (axSpA). Methods: Cross-sectional study including 114 patients axSpA from the SpA registry of Córdoba (CASTRO) and 132 age- and sex-matched healthy controls (HCs). Disease activity and the presence of traditional CV risk factors were recorded. The presence of atherosclerotic plaques and carotid intima media thickness (cIMT) were evaluated through carotid ultrasound and the SCORE index was calculated. Radiographic damage was measured though modified Stoke Ankylosing Spondylitis Spinal Score (mSASSS). The association between mSASSS and SCORE was tested using generalized linear models (GLM), and an age-adjusted cluster analysis was performed to identify different phenotypes dependent on the subclinical CV risk. Results: Increased traditional CV risk factors, SCORE, and the presence of carotid plaques were found in axSpA patients compared with HCs. The presence of atherosclerotic plaques and SCORE were associated with radiographic structural damage. The GLM showed that the total mSASSS was associated independently with the SCORE [β coefficient 0.24; 95% confidence interval (CI) 0.10–0.38] adjusted for disease duration, age, tobacco, C-reactive protein, and non-steroidal anti-inflammatory drugs (NSAID) intake. Hard cluster analysis identified two phenotypes of patients. Patients from cluster 1, characterized by the presence of plaques and increased cIMT, had a higher prevalence of CV risk factors and SCORE, and more structural damage than cluster two patients. Conclusion: Radiographic structural damage is associated closely with increased estimated CV risk: higher SCORE levels in axSpA patients were found to be associated independently with mSASSS after adjusting for age, disease duration, CRP, tobacco and NSAID intake.

Characteristics of Adenocarcinoma of the Gallbladder Following Cholecystectomies in the Hispanic Population

2019 ◽  
Vol 152 (Supplement_1) ◽  
pp. S64-S65
Author(s):  
David Gustafson ◽  
Osvaldo Padilla
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Incidental Finding ◽  
Conditional Logistic Regression ◽  
Gallbladder Disease ◽  
Predictor Variables ◽  
Wall Thickening ◽  
Conditional Logistic Regression Analysis

Abstract Introduction Gallbladder adenocarcinoma (GBC) is a rare malignancy. Frequency of incidental adenocarcinoma of the gallbladder in the literature is approximately 0.2% to 3%. Typically, GBC is the most common type and is discovered late, not until significant symptoms develop. Common symptoms include right upper quadrant pain, nausea, anorexia, and jaundice. A number of risk factors in the literature are noted for GBC. These risk factors are also more prevalent in Hispanic populations. This study sought to compare patients with incidental gallbladder adenocarcinomas (IGBC) to those with high preoperative suspicion for GBC. Predictor variables included age, sex, ethnicity, radiologic wall thickening, gross pathology characteristics (wall thickness, stone size, stone number, and tumor size), histologic grade, and staging. Methods Cases of GBC were retrospectively analyzed from 2009 through 2017, yielding 21 cases. Data were collected via Cerner EMR of predictor variables noted above. Statistical analysis utilized conditional logistic regression analysis. Results The majority of patients were female (n = 20) and Hispanic (n = 19). There were 14 IGBCs and 7 nonincidental GBCs. In contrast with previous research, exact conditional logistic regression analysis revealed no statistically significant findings. For every one-unit increase in AJCC TNM staging, there was a nonsignificant 73% reduction in odds (OR = 0.27) of an incidental finding of gallbladder carcinoma. Conclusion This study is important in that it attempts to expand existing literature regarding a rare type of cancer in a unique population, one particularly affected by gallbladder disease. Further studies are needed to increase predictive knowledge of this cancer. Longer studies are needed to examine how predictive power affects patient outcomes. This study reinforces the need for routine pathologic examination of cholecystectomy specimens for cholelithiasis.

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