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dc.contributor.authorRuugia, Samuel K
dc.contributor.authorMoturi, Christopher A
dc.description.abstractEvolution in the field of Geographic Information Systems (GIS) has given rise to sophisticated scientific techniques for collection, analysis and visualization of location based data. These GIS analysis processes are used to reveal some critical patterns of occurrences. Due to inaccurate analysis and covering of insurance 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 records of their annual claims. The main problem here is that the rates cover the entire nation without considering the distribution of risk in various regions. The objective of the paper is to show that GIS can be used to analyse and generate auto insurance risk territories for insurance companies from which an insurance rating model can be developed. We used GIS analysis methods such as inverse distance weighting (IDW) interpolation, data smoothing and clustering techniques and data on auto insurance accidents and crime, geo-coded police stations, roads, socio-economic, aerial and satellite imagery for Nairobi County. A risk territory map showing the distribution of auto insurance risk and other related maps were generated. A prescriptive insurance rating model was then developed that uses generated risk territories 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.
dc.subjectAuto insurance risk territory
dc.subjectSpatial Interpolation
dc.subjectInverse Distance Weighting
dc.titleApplication of GIS spatial interpolation methods in auto insurance risk territory segmentation and ratingen_US

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