A study on the application of data mining for an insurance company ─ a case on the evaluation of sales rep compensation
Advisor: Prof. C.K. Farn
Student: Hsi Keng Chen
Data mining is a comprehensive technique which combines information technique, analysis technique and industry know-how. With this technique, users can discover the hidden patterns in large volumes of data and transform such data into useful information and even business operating tactics. Nowadays, data mining is applied in many business fields.
Business applications of data mining include profitability analysis, customer attraction, market segmentation, asset risk management, and cross selling etc.. This study applies data mining technique in the insurance industry. Insurance companies can use the results from prescription on sales’ behavior to expand their business performance. Data mining creates information assets that a company can leverage to achieve the business strategic objectives.
The target company for this study is a traditional Taiwanese life insurance company. The management of the company believes that more sales rep contributes to higher revenues. Motivating sales rep is a difficult problem facing the management. The results of this data mining study can help to accomplish this goal.
The results of this study are: there is significant relationship among performance, salary, position and tenure. As a result, it is suggested that tenure can be included as a factor in determining sales rep compensation.
Keywords: Data Mining, Decision Tree, Insurance, Compensation||en_US|