Insurance and Risk Control Management
Historically, insurance premiums have been dictated by market forces, based for the most part on perceptions of risk rather than any realistic data. Such data is, however, often readily available. For example, by utilising risk assessment data, such as may be collected to satisfy regulators, it is possible to identify, for a major asset, the actual risks faced.
Risks Faced
A Risk Profile (that is, a record of the detrimental events associated with the asset, along with their probable frequency and consequences) may be constructed. Estimates of consequences may include asset damage, business interruption costs and costs associated with environmental clean-up or compensation. The Risk Profile can then be used to calculate the long-term average annual loss, or "expected loss".
By transferring the risk fully to an underwriter, an asset owner smoothes his cash flow. Also, since he will naturally be adverse to major losses, and in order to allow for uncertainties in the Risk Profile, the owner ought to be prepared to pay the underwriter significantly more than the "expected loss". The premium income that the underwriter receives is therefore more than his average annual payout and so in the long term he makes a profit. His risk aversion should be lower than that of the asset owner since he can re-insure and pool risks across his client base.
Rational Solutions
Therefore, it should be possible to find a solution that is satisfactory for both parties - in most cases there will exist a premium that is low enough to represent a rational purchase decision for the asset owner and yet high enough to allow the underwriter to make a fair profit in the long term.
By utilising the Data and Decision Management Tool (DDMT) together with an add-on Decision Support Tool (DST), it is possible for both the insured and the insurer to optimise their strategy. The approach can be used by asset owners or underwriters in isolation, or by the two working in collaboration.