Insurance. Meaning of Term "Theft" in Automobile Insurance Policy

1925 ◽  
Vol 34 (8) ◽  
pp. 913
Keyword(s):  
Automobile Insurance ◽  
Insurance Policy

Automobile Insurance: Analysis of the Impact of a Premium Change on the Behavior of Insured at the Time of Subscription and Termination

2019 ◽  
Vol 10 (6) ◽  
pp. 517-530
Author(s):  
Zakaria Rouaine ◽  
◽  
Mounir Jerry ◽  
Ahlam Qafas
Keyword(s):  
Insurance Premium ◽  
Insurance Contract ◽  
Insurance Market ◽  
Automobile Insurance ◽  
Insurance Policy ◽  
Contract Term ◽  
Insurance Premiums ◽  
The Impact ◽  
Premium Risk

the subscription of an insurance contract allows an individual to take precautions against the repercussions of hazards and fortuitous events affecting their person or property. In return for this insurance policy, the insured pays a contribution at the beginning of the coverage period, while the insurer may have to provide a service if a certain type of damage occurs during the period in question. While the insurance market acts both on the insured by being able to induce him to terminate his insurance contract, in the case of excessive prices to those of other insurers, and on the insurer by forcing him to a certain extent to make his insurance premiums tolerable. It therefore appears that the insurance premium risk threatens the competitiveness of insurers on the insurance market and the termination of policyholders at the end of the contract term. By choosing to work on automobile insurance market, which is becoming increasingly competitive, as precise premium pricing is a major challenge for each insurer. The aim of this work is to study the sensitivity of insured persons to positives changes in automobile insurance premiums at the end of the contract.

Assessing the Impact of Suicide Exclusion Periods on Life Insurance

Crisis ◽  
2010 ◽  
Vol 31 (4) ◽  
pp. 217-223 ◽  
Author(s):  
Paul Yip ◽  
David Pitt ◽  
Yan Wang ◽  
Xueyuan Wu ◽  
Ray Watson ◽  
...  
Keyword(s):  
Life Insurance ◽  
Accidental Death ◽  
Insurance Policy ◽  
Death Rates ◽  
Insurance Policies ◽  
Suicidal Death ◽  
Insured Individual ◽  
The Impact ◽  
Insurance Data ◽  
The Relationship

Background: We study the impact of suicide-exclusion periods, common in life insurance policies in Australia, on suicide and accidental death rates for life-insured individuals. If a life-insured individual dies by suicide during the period of suicide exclusion, commonly 13 months, the sum insured is not paid. Aims: We examine whether a suicide-exclusion period affects the timing of suicides. We also analyze whether accidental deaths are more prevalent during the suicide-exclusion period as life-insured individuals disguise their death by suicide. We assess the relationship between the insured sum and suicidal death rates. Methods: Crude and age-standardized rates of suicide, accidental death, and overall death, split by duration since the insured first bought their insurance policy, were computed. Results: There were significantly fewer suicides and no significant spike in the number of accidental deaths in the exclusion period for Australian life insurance data. More suicides, however, were detected for the first 2 years after the exclusion period. Higher insured sums are associated with higher rates of suicide. Conclusions: Adverse selection in Australian life insurance is exacerbated by including a suicide-exclusion period. Extension of the suicide-exclusion period to 3 years may prevent some “insurance-induced” suicides – a rationale for this conclusion is given.

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.

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