Contractors' risk and insurance in the Australian building industry

The thesis commences with problems faced by the building industry in regard to relatively high commissions and management changes, relatively low outstanding claims and the inadequate knowledge of underwriting security in the event of catastrophic losses. Examination of insurance industry practice with contractors' risk general insurance contracts highlights further problems in terms of inadequate existing insurance provisions and the insurance of subcontractors, where recent attempts to secure reform have proved unsuccessful. Analysis of building industry practice shows the problems of traditional methods of securing adequate project insurance. The need for project insurance specifications that are competitively tendered is highlighted by way of example. Risk identification programmes are devised for streamlining existing procedures with due consideration of the constraints in obtaining change within the building industry. An approach to quantify the range of risks and probabilities of events is introduced with the risk probability model that, by way of illustration, is used to assess a fire and explosion risk premium for a project. The risks to principal parties under contract, being owners, builders and insurers, are represented using Venn diagrams. In order to secure a change in present procedures, better communication aids are required as a prerequisite to the development of mathematical models and risk databanks for more accurate analysis and assessment of risk and insurance premiums. A maxium risk model is used as a method of corporate planning, using the Venn diagram notations, to identify any contract party that may have a financial inability to absorb its maximum risk liabilities under a project contract. A third mathematical model is introduced for the assessment of contract conflict costs which provides scope for a possible new insurance field. In the example given, subjective costs and probabilities are used. However, a method is stated of obtaining actual costs, probabilities and the ranking of risk for the contract conflict model. Directions for further research include standard terminology, further diagrammatic relationships and mathematical models, and the establishment of industry databanks of risk and insurance information that will allow more accurate risk forecasting, rating and better loss minimisation schemes.