Abstract:
This study examined risk exposure and auto insurance premium determinants in Ghana . We analysed an existing data set
of 23 434 policies (without claims = 84 .1%, policies with claims = 15 .9%; comprehensive policies = 48 .0%, third-party
policies = 52 .0%) applying the Autoregressive Distributed Lag (ARDL) model, controlling for driver demographics,
value of car, and car usage variables . Findings indicate policyholders’ age significantly determine premiums charges .
Additionally, auto seating capacity significantly influenced third-party rather than comprehensive premiums, and auto’s
cubic capacity had no significant impact on premium charges . Pricing system impact premiums were influenced by
policyholders’ characteristics more than variables from the insured vehicle . These findings suggest that policyholders’ age
(novice drivers) and vehicles with many occupants increases auto insurers risk exposure
