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dc.contributor.authorRuugia, Samuel K
dc.date.accessioned2014-12-03T09:34:33Z
dc.date.available2014-12-03T09:34:33Z
dc.date.issued2014-09
dc.identifier.urihttp://hdl.handle.net/11295/76044
dc.descriptionMastersen_US
dc.description.abstractDevelopments in Geographic Information Systems (GIS) have given rise to sophisticated scientific techniques for collection, analysis and visualization of location based data. GIS analysis is used to reveal some critical patterns of occurrences that are not usually obvious. Due to inaccurate analysis and covering of risks in Kenya, several companies have closed down prompting the Insurance Regulatory Authority (IRA) and Association of Kenyan Insurers (AKI) set up maximum and minimum premium rates on insurance risks. The set premiums discounts are given to the insured based on their annual claims records. The main problem is that the rates cover the entire nation without considering the distribution of risk in various regions. The main objective of this research was to show that GIS can be used to analyse and generate auto insurance risk territories for insurance companies in Nairobi County from which an insurance rating model can be developed. GIS analysis methods such as Inverse Distance Weighting (IDW) interpolation, data smoothing and clustering techniques were used. Auto Insurance accidents and crime, geo-coded police stations, roads, socio-economic, aerial and satellite imagery data for Nairobi County was used. A risk territory map showing the distribution of Auto insurance risk and other related maps were generated. A prescriptive insurance rating model auto rating model was developed that uses generated risk territories limits to calculate varying rates for auto insurance premiums rates for the respective regions. This research shows that GIS techniques can be used for better visualization of risk at a given location for accurate risk analysis and uptake. This research can also be applied to other locations and classes of risks as well as calculating upfront discounts on Auto insurance premium rates. Keywords: Auto Insurance Rating Model, Auto Insurance Risk Territory, Auto Insurance Accidents and Crime, Inverse Distance Weighting (IDW), Prescriptive, Spatial Interpolationen_US
dc.language.isoenen_US
dc.publisherUniversity of Nairobien_US
dc.titleApplication of GIS in auto insurance risk segmentation and rating: a case for Nairobi countyen_US
dc.typeThesisen_US
dc.type.materialen_USen_US


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