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Repeated audit controls

机译：重复审核控制

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摘要

An important task of auditors is to check whether recorded values are correct. From the number (or total) of the errors found in a sample, upper confidence limits for the fraction (or total) of the errors in the population are calculated by standard methods.Even auditors are human, however, and may make mistakes: errors may remain unnoticed. As administrative rules and regulations are becoming more and more complicated, this kind of auditors' mistakes tends to occur more frequently. Hence, there is an increasing need to check the auditing process itself. This can be achieved by checking a subsample of audited values a second time, now by an error-free supervisor.This paper investigates the consequences of the (possible) occurrence of errors in this subsample. A simple and analytically attractive model is presented for the number of errors found in this double inspection scheme. Maximum likelihood estimators are derived for the population fraction of errors and the probability of an error remaining unnoticed. Based on that, an exact upper confidence limit for the population fraction of errors is calculated, treating the probability of an unnoticed error as a nuisance parameter. Our method was originally developed during a recent Dutch case study: in a subsample of already audited values one additional error was found by the supervisor. It is shown that, as a consequence, the upper confidence limit is increased very sizeably.
机译：审核员的一项重要任务是检查记录的值是否正确。根据样本中发现的错误的数量（或总数），使用标准方法计算总体中错误的分数（或总数）的置信上限，但是即使是审核员也是人为的，并且可能会出错：错误可能不会被注意。随着行政法规越来越复杂，这类审计师的错误往往会越来越频繁。因此，越来越需要检查审核过程本身。这可以通过现在由无差错的主管再次检查审核值的子样本来实现。本文研究了该子样本中（可能）发生错误的后果。针对这种双重检查方案中发现的错误数量，提出了一个简单且具有分析吸引力的模型。得出最大似然估计值，以得出误差的总体比例以及误差未被发现的概率。在此基础上，针对错误的总体比例计算出确切的置信上限，并将未注意到的错误的概率视为令人讨厌的参数。我们的方法最初是在最近的荷兰案例研究中开发的：在已经审计的值的子样本中，主管发现了另一个错误。结果表明，置信上限极大地增加了。

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