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A fuzzy knowledge‐based system for premium rating of workers' compensation insurance for building projects
journal contribution
posted on 2007-01-01, 00:00 authored by Imriyas KamardeenImriyas Kamardeen, Low Sui Pheng, Evelyn Ai Lin TeoOccupational injuries and fatalities are rampant in construction. The significance of the workers’ compensation
insurance (WCI) is immeasurable in safeguarding the interests of construction workers and contractors. From
the insurers’ perspective, the commitment under this insurance is extremely broad; there are no exclusions and
a maximum limit on their liability. Thus, insurers must accomplish rigorous risk and market assessments to
decide optimal premiums for construction projects. The conventional experience rating approach of premium
rating has been proven ineffective for construction applications. Based on the findings of a literature review and
an interview questionnaire survey, a new WCI premium rating model was developed for building projects. A
hybrid of interviews and past workers’ compensation claims data analysis was adopted to develop the
conceptual model of a fuzzy knowledge-based system (KBS) to automate the proposed model. It was then
prototyped, and verified with Turing tests. The proposed model and its fuzzy KBS advocate real time
structured assessments of project hazards, safety, market condition and insurers’ internal factors for premium
rating. They also establish an effective risk control strategy via a well-structured incentive system for contractors
and clients. Their implementation in the general insurance industry can facilitate accident control in the
construction industry, thereby minimizing insurers’ financial risks.
insurance (WCI) is immeasurable in safeguarding the interests of construction workers and contractors. From
the insurers’ perspective, the commitment under this insurance is extremely broad; there are no exclusions and
a maximum limit on their liability. Thus, insurers must accomplish rigorous risk and market assessments to
decide optimal premiums for construction projects. The conventional experience rating approach of premium
rating has been proven ineffective for construction applications. Based on the findings of a literature review and
an interview questionnaire survey, a new WCI premium rating model was developed for building projects. A
hybrid of interviews and past workers’ compensation claims data analysis was adopted to develop the
conceptual model of a fuzzy knowledge-based system (KBS) to automate the proposed model. It was then
prototyped, and verified with Turing tests. The proposed model and its fuzzy KBS advocate real time
structured assessments of project hazards, safety, market condition and insurers’ internal factors for premium
rating. They also establish an effective risk control strategy via a well-structured incentive system for contractors
and clients. Their implementation in the general insurance industry can facilitate accident control in the
construction industry, thereby minimizing insurers’ financial risks.
