Data Mining in Actuarial Science: Theory and Applications

Dear Colleagues,

Insurance companies continue to gather increasing volumes of information that are being used for improved data-driven decision making. In the past few years, this has generated an increasing interest and need for data mining tools and techniques to analyze data, especially big data, in insurance and actuarial science. Data mining has potential applications in all personal and commercial lines of insurance: life, non-life, health and pensions. Although data mining is clearly useful in insurance and actuarial science, it faces many challenges during its implementation.

This Special Issue aims to collect recent developments of applying data mining techniques in insurance and actuarial science. We welcome original research articles that develop data mining techniques and case studies that showcase applications. We also encourage data mining work derived from collaborative efforts between academia and the industry.

Prof. Dr. Emiliano A. Valdez
Dr. Guojun Gan
Guest Editors

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