In order to better serve their customers, a project to create a methodology for identifying variables that could indicate future long-term care insurance usage was commissioned by Ability Resources, Inc. As a basis for constructing a predictive model, tools such as SAS and Excel were implemented. A k-means clustering algorithm in SAS was utilized to group policyholders with similar characteristics, and a performance evaluation was executed in Excel. Together, these processes created a tool that determined the impact each characteristic had on policyholder benefit utilization. The validity of the process was assessed by applying it to supplemental data generated by the team. After several trials, the Variable Identification Procedure proved accurate.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Bai, Jie
• Zhang, Xinyi
• Standring, Heather Lee
• Smeal, Ashleigh Rita

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-042810-124607

Advisor

• Abraham, Jon P.
• Vassallo, Helen G.

Year

• 2010

Sponsor

• Ability Resources, Inc.

Date created

• 2010-04-28

Resource type

• Major Qualifying Project

Major

• Interdisciplinary
• Actuarial Mathematics

Rights statement

• In Copyright

Última modificación

• 2021-01-27