Auto insurance premiums in Ghana: An Autoregressive Distributed Lag model approach to risk exposure variables

Measuring the Adequacy of Loss Distribution for the Ghanaian Auto Insurance Risk Exposure through Maximum Likelihood Estimation

“…Information on risk exposure and premiums for (n = 23,434) vehicle insurance policyholders was obtained throughout 2018 from a leading Ghanaian insurance Open Journal of Business and Management company (Azaare et al, 2021). Due to existing market competition, this leading insurer opted to be unanimous.…”

“…Measuring the Adequacy of Loss Distribution for the Ghanaian Auto Insurance Risk Exposure through Maximum Likelihood Estimation. Open Journal of Business and Management,10,[846][847][848][849][850][851][852][853][854][855][856][857][858][859] https://doi.org/10.4236/ojbm.2022.102047 Open Journal of Business and Management nomic growth and development cannot be underrated (Azaare & Wu, 2020;Azaare et al, 2021). Hence, safeguarding the market to understand insurers' exposed risk probability distribution is essential (Azaare & Wu, 2020;Stojakovic & Jeremic, 2016).…”

Exploring the Effects of Classical Auto Insurance Rating Variables on Premium in ARDL: Is the high Policyholders’ Premium in Ghana Justified?

“…Furthermore, in Ghana, the seating capacity of an insured vehicle plays a significant role in determining the final premium. ''Except for the linear association between auto mass and accident severity, there is no sufficient evidence in the literature to support its inclusion'' (Azaare et al, 2021).The standard number of seats included in the flat-rate system for both third-party and comprehensive insurance is five. In this situation, each vehicle with more than five seats pays 5 and 8 Ghana cedis per seat for private and commercial use, respectively (Azaare et al, 2021;Ghana National Insurance Commission [NIC], 2015).…”

“…Surprisingly, despite all of the variables used by insurers in premium calculations, the Ghanaian auto insurance market based solely on vehicle age, cubic capacity, type of use for third-party policies, and inclusion of the vehicle’s sum in the comprehensive (C) premium case (Awunyo-Vitor, 2012; Ghana National Insurance Commission [NIC], 2015; Laryea, 2016), which this study discovers that not all of these variables are significant. The pricing model used by the market does not also capture any characteristics of the insured driver or the policyholder involved but relies on only the limited classical variables of the insured auto, leaving a mixed feeling from policyholders on variables considered because of the high nature of premiums (Azaare et al, 2021). According to the Ghana National Insurance Commission’s (NIC, 2015) pricing system, vehicles with fewer than 5 years of age are not charged age loading, but those with 5 to 10 and more than 10 years are paid 5% and 7.5% of the basic premium as age loadings, respectively.…”

“…also shows the variables that were used in the model. The explanatory variables in our model are classical premium variables that are found in market data, such as policyholder age, insured vehicle age, cubic capacity, claims size, and vehicle seating capacity(Awunyo-Vitor, 2012;Azaare et al, 2021; Ghana National Insurance Commission [NIC], 2015;Laryea, 2016).…”