Using the Clustering Algorithms and Rule-based of Data Mining to Identify Affecting Factors in the Profit and Loss of Third Party Insurance, Insurance Company Auto

Faramarz Karamizadeh  and Seyed Ahad Zolfagharifar

doi:10.17485/ijst/2016/v9i7/87846

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Using the Clustering Algorithms and Rule-based of Data Mining to Identify Affecting Factors in the Profit and Loss of Third Party Insurance, Insurance Company Auto

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2016/v9i7/87846

Year: 2016, Volume: 9, Issue: 7, Pages: 1-9

Original Article

Using the Clustering Algorithms and Rule-based of Data Mining to Identify Affecting Factors in the Profit and Loss of Third Party Insurance, Insurance Company Auto

Faramarz Karamizadeh¹ and Seyed Ahad Zolfagharifar^2*

¹Department of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran; [email protected] ²Kohgiluyeh and Boyer Ahmad Science and Research Branch, Islamic Azad University, Iran; [email protected]

*Author for Correspondence
Seyed Ahad Zolfagharifar
Kohgiluyeh and Boyer Ahmad Science and Research Branch, Islamic Azad University, Iran; [email protected]

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Background/Objectives: Insurance data analysis can be considered as a way of losses reduction by using data mining. It uses the machine learning, pattern recognition and data base theory for discovering the unknown knowledge. Methods/ Statistical Analysis: In this paper, information of 2011, third party insurance of Iran insurance company auto has analyzed in Kohgiluyeh and Boyer Ahmad by using the data mining method. Findings: The results show that using clustering algorithms with acceptable clusters will be able to provide a model to identify affecting factors and to determine the effect of them in the profit and loss of auto third party insurance. Applications/Improvements: The algorithm of K-Means has formed the best clustering with 9 clusters that have relatively good quality. It means that has been able to maximize the distance between the cluster and minimize the within cluster distance.

Keywords: Clustering Algorithm, Data Mining, Insurance, Profit and Loss, Third Party