چكيده به لاتين
With the Expansion of industry، Rapid technological progress، competitive market، the requirement of using data mining knowledge in the industry is necessary. The success of insurers depends on their ability to turn raw data into a practical information with data mining tools, predictability, comprehensibility and Knowledge partitioning, and assessment and risk management. This can be achieved through data mining.
The most important services offered in the insurance industry using data mining methods is analyzing and identifying profitable customers and estimating customer premiums based on the risk of each customer, predicting the amount of damage based on customer groups, managing the relationship with the insurers and Developing a strategy based on target customers, Determining the loyalty and turning away factors in customers.
The purpose of this study was to investigate the assumptions about the profitable customers of one of the insurance companies and In the following we provide a model for profitable customers in the field of automobile insurance Using the analysis of company's huge data that was used to achieve this goal by using software such as R and Oracle with regression algorithms. First, the research hypotheses were studied، then, by using the clustering algorithms and the decision tree, the Classification of customers in the field of automobile insurance were carried out.
Then, we used training data to verify the validity of the proposed model and whether there was a reasonable relationship between profitability of customers based on the decision tree and the profitability of the customers in real. In addition, we used diagnostic analysis to verify the accuracy of the model, which shows 95% accuracy.
Finally, we also used the svm model to compare the results of the proposed model. The results showed that the proposed decision tree model predicted more accurate.
