Application of GIS Spatial Interpolation Methods inAuto Insurance Risk Territory Segmentation and Rating

Samuel Ruugia, Christopher Moturi


Evolution 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.

Keywords: Auto Insurance Risk Territory, Spatial Interpolation, Inverse Distance
Weighting (IDW), Prescriptive Auto Insurance Rating Model

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[ISSN 1821-7567 (Print)  & eISSN 2591-6947 (Online)]