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Using Big Data to Discriminate Charged Price in the Car Insurance Industry: Evidence from United States

         

摘要

The purpose of this paper is to examinethe gender-based discrimination in car insurance ratesand whether the reasons provided by the car insurancecompanies for the different rates are valid or not. Thepaper studies the average annual premiums paid bymen and women across different age groups from 16years old to over 56 years old along with the percentagedifferences. Additionally, the concept of big data andhow it is utilized by businesses to apply personalizeprice discrimination is investigated. The researchdesign is conclusive and secondary data is used in bothqualitative and quantitative forms. Qualitative data iscollected from articles for the literature review andas for the quantitative data it is in the form of reportsand surveys. The data shows that at lower age groupswomen pay less than men for car insurance but as theage increase men start paying less. The paper reaches aconclusion that gender is not necessarily a crucial riskfactoras the regular factors such as driving record canprovided accurate risk determinants.

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