A RISK-BASED ADJUSTMENT MODEL FOR EXPERIENCE RATING OF MOTOR INSURANCE IN NIGERIA
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Abstract
In establishing the burden of costs, the principle underlying the calculation of differentiated premium in the insurance portfolio is characterized by a pricing process that involves the classification of all risks regarding factors of influence. This classification is based on known observable characteristics of the insured. However, there are many other important factors that are unobservable by the insurer which cannot be taken into account a-priori when pricing motor liability insurance products but may represent significant risk factors. Also, it has become extremely difficult recently, for insurance companies to maintain cross subsidies between different risks categories in a competitive market. As competition between insurance companies intensifies, higher efficiency and greater focus on profitability are required. While the potential for cost reductions is limited, improvements in profitability and growth can be achieved through appropriate pricing mechanisms. Experience rating which is popularly referred to as No Claim Discount or Bonus-Malus Systems involves modifying premiums using claims records. Risk-based adjustment pricing is an experience rating technique commonly used in motor insurance to categorize policyholders into relatively homogenous group who pay premium relative to their claims experience. In this study, a risk-based adjustment model that incorporates costs in a fair and equitable manner given the individual characteristics of the insured for experience rating is adopted using generalized linear model. Claim cost and frequency data from motor insurance liability portfolio in Nigeria as well as the insured characteristics were collected and analysed using the generalized negative binomial and gamma regressions. Individual risk weights from the fitted models were used to compute the risk scores. This was subsequently used to determine the relative costs of an insured based on their individual characteristics and claims history. Results show that the claims data from automobile insurance scheme is highly peaked and leptokurtic. The claims data also vary significantly across age groups, gender, occupation, and nature of loss, as well as the place of residence, type of product and customer type. The study established that motor insurance risks are influenced by individual risk characteristics and a risk-based adjustment pricing be introduced to establish fair and equitable costs among the insured. It is recommended that a risk-based adjustment pricing be employed to estimate accurately the average expected loss in order to charge adequate price for motor insurance.
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