Econometric Forecasting of Automobile Insurance Paid-Claim Costs

1985 ◽  
pp. 247-277
Author(s):  
J. David Cummins ◽  
Scott E. Harrington
Keyword(s):  
Automobile Insurance

Identifying Key Fraud Indicators in the Automobile Insurance Industry Using SQL Server Analysis Services

2019 ◽  
Vol 64 (2) ◽  
pp. 53-71
Author(s):  
Botond Benedek ◽  
Ede László
Keyword(s):  
Neural Network ◽  
Decision Tree ◽  
Naive Bayes ◽  
Insurance Industry ◽  
Naïve Bayes ◽  
Sql Server ◽  
Categorical Variables ◽  
Automobile Insurance ◽  
Price Determination ◽  
Mining Tool

Abstract Customer segmentation represents a true challenge in the automobile insurance industry, as datasets are large, multidimensional, unbalanced and it also requires a unique price determination based on the risk profile of the customer. Furthermore, the price determination of an insurance policy or the validity of the compensation claim, in most cases must be an instant decision. Therefore, the purpose of this research is to identify an easily usable data mining tool that is capable to identify key automobile insurance fraud indicators, facilitating the segmentation. In addition, the methods used by the tool, should be based primarily on numerical and categorical variables, as there is no well-functioning text mining tool for Central Eastern European languages. Hence, we decided on the SQL Server Analysis Services (SSAS) tool and to compare the performance of the decision tree, neural network and Naïve Bayes methods. The results suggest that decision tree and neural network are more suitable than Naïve Bayes, however the best conclusion can be drawn if we use the decision tree and neural network together.

Unisex Tariffs and the Automobile Insurance Market - Insights from Germany

2012 ◽  
Author(s):  
Vijay Aseervatham ◽  
Christoph Lex ◽  
Martin Spindler
Keyword(s):  
Insurance Market ◽  
Automobile Insurance

An Evaluation of the New Japanese Bonus–Malus System with No-claim and Claimed Subclasses

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Mahito Okura ◽  
Takuya Yoshizawa ◽  
Motohiro Sakaki
Keyword(s):  
Simulation Analysis ◽  
Insurance Premium ◽  
Automobile Insurance ◽  
Insurance Claims ◽  
Present Value ◽  
Time Discount

AbstractThe purpose of this research is to evaluate the new Japanese Bonus–Malus System (BMS 2012) in automobile insurance, which is an unusual system wherein both no-claim and claimed subclasses exist. To evaluate BMS 2012, we conduct a simulation analysis and compare BMS 2012 with the former Japanese BMS (BMS 2009) in terms of the present value of the total insurance premium that is closely related to the frequency of insurance claims. Based on the comparison, our main conclusion is that BMS 2012 offers more effects to lower the frequency of insurance claims than BMS 2009 does when the policyholders’ classes in BMS are high classes that evaluate as safety drivers, time discount and/or renewal rates are relatively low, and the policyholders’ risk averseness is large.

A Comparison of State-of-the-Art Classification Techniques for Expert Automobile Insurance Claim Fraud Detection

2002 ◽  
Vol 69 (3) ◽  
pp. 373-421 ◽  
Author(s):  
Stijn Viaene ◽  
Richard A. Derrig ◽  
Bart Baesens ◽  
Guido Dedene
Keyword(s):  
State Of The Art ◽  
Fraud Detection ◽  
Automobile Insurance ◽  
Insurance Claim ◽  
Classification Techniques
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