Contract contracts or optional reinsurance contracts often set a limit on losses attributable to the reinsurer. This limit is agreed upon in the reinsurance contract; it protects the reinsurance company from unlimited liability. In this way, contractual and optional reinsurance contracts are similar to a standard insurance contract that provides coverage of up to a certain amount. If this is advantageous to the reinsurer, it forces the insurance company to reduce the losses. For example, a non-life insurance company enters into a reinsurance contract with a deductible. The trigger is based on losses from the broader market, with the reinsurer indicating that it will cover the insurer`s losses when the market suffers losses of $15 million. The investment point – the point at which the insurer pays first – is set at $10,000. When the contract suffers losses of $20 million, the reinsurer will cover the losses of more than 10,000 $US of the insurer that has withdrawn. Another factor is the number of codes. As the number of codes increases, kappas become higher. Based on a simulation study, Bakeman and colleagues concluded that for fallible observers, Kappa values were lower when codes were lower. And in accordance with Sim-Wright`s claim on prevalence, kappas were higher than the codes were about equal.
Thus Bakeman et al. concluded that no Kappa value could be considered universally acceptable. :357 They also provide a computer program that allows users to calculate values for Kappa that indicate the number of codes, their probability and the accuracy of the observer. If, for example, the codes and observers of the same probability, which are 85% accurate, are 0.49, 0.60, 0.66 and 0.69 if the number of codes 2, 3, 5 and 10 is 2, 3, 5 and 10. A case that is sometimes considered a problem with Cohen`s Kappa occurs when comparing the Kappa, which was calculated for two pairs with the two advisors in each pair that have the same percentage agree, but one pair gives a similar number of reviews in each class, while the other pair gives a very different number of reviews in each class.  (In the following cases, there is a similar number of evaluations in each class. , in the first case, note 70 votes in for and 30 against, but these numbers are reversed in the second case.) For example, in the following two cases, there is an equal agreement between A and B (60 out of 100 in both cases) with respect to matching in each class, so we expect Cohens Kappa`s relative values to reflect that.