Honors Theses and Capstones
Date of Award
Spring 2017
Project Type
Senior Honors Thesis
College or School
PAUL
Department
Decision Sciences
Program or Major
Business Administration: Accounting and Information Systems & Business Analytics
Degree Name
Bachelor of Science
First Advisor
Inchan Kim
Abstract
The development of computing sensor devices with the capability of tracking an individual’s activity changed the way we live and move. The data collected and generated from wearable technology provides implications to the user for leading a healthy, more active lifestyle; however, the potential data uses extend beyond the user. Significant opportunity exists in the insurance industry as it relates to discounting premiums. The purpose of this research was to provide insight as to whether insurance companies should consider offering discount on premiums for policyholders who use wearable technology to track their personal fitness by identifying and suggesting potential groups of consumers to target these discounts toward. Using the platform R, researchers collected and analyzed tweets about four leading wearable technology companies including Fitbit, Jawbone, Misfit, and Withings. Both unsupervised and supervised learning techniques were pursued during the study in the form of topic modeling and artificial intelligence. Through detailed analysis, researchers determined that companies may want to consider reducing premiums for wearable technology users who use the devices for weight loss, as it would benefit both policyholders and insurance companies.
Recommended Citation
Zukowski, Kaleigh Alexis, "Trading Data for Discounts: An Exploration of Unstructured Data Through Machine Learning in Wearable Technology" (2017). Honors Theses and Capstones. 366.
https://scholars.unh.edu/honors/366