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Using Artificial Intelligence for the Evaluation of the Movability of Insurances
Umeå University, Faculty of Science and Technology, Department of Computing Science.
2013 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Today the decision to move an insurance from one company/bank to another is done manually. So there is always the risk that a incorrect decision is made due to human error. The goal of this thesis is to evaluate the possibility to use an artifcial intelligence, AI, to make that decision instead. The thesis evaluates three AI techniques Fuzzy clustering, Bayesian networks and Neural networks. These three techniques was compared and it was decided that Fuzzy clustering would be the technique to use. Even though Fuzzy clustering only achieved a hit rate of 69%, there is a lot of potential in Fuzzy clustering. In section 4.2 on page 32 a few improvements are discussed which should help raise the hit rate.

Place, publisher, year, edition, pages
2013.
Series
UMNAD, 953
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:umu:diva-80769OAI: oai:DiVA.org:umu-80769DiVA: diva2:651308
Educational program
Master of Science Programme in Computing Science and Engineering
Supervisors
Examiners
Available from: 2013-09-25 Created: 2013-09-25 Last updated: 2013-09-25Bibliographically approved

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