Increasing the efficiency of risk allocation in project financed infrastructure transactions by reducing the impact of risk noise

Project finance provides a source of funding for infrastructure projects that relies on the lenders to the project bearing more risk than a lender would normally agree to bear. Despite the careful structuring of risk allocation in project financing, such projects tend not to follow the commonly accepted approach to efficient risk allocation in infrastructure projects. This thesis looks at 12 different project financing transactions and analyses whether and why they fail to implement this commonly accepted approach to efficient risk allocation. It argues that on a review of the literature, the commonly accepted approach to efficient risk allocation assumes that the parties have all the information they need and are able to assess that information objectively. Yet, it is seldom the case that the parties to an infrastructure project have access to such information or the ability to make wholly objective assessments. Further, on review of the literature on risk perception and assessment, parties to a project will compensate for their lack, or perceived lack, of information by implementing various conscious and subconscious techniques to assess risk. I have taken these various theories of risk assessment and refined them into a concept I call 'Risk Noise'. The case studies indicate that Risk Noise is one of the key influences that result in project financing transactions implementing 'inefficient' approaches to risk allocation. This thesis also proposes an analytical model to assess whether it would be advisable to endeavour to filter out Risk Noise in a given project if that Risk Noise is perceived to be causing a reduction in efficiency.