Final answer:
The risk is known as audit risk, especially the type I error or α risk, which refers to the possibility of accepting a control as effective when it's not. This risk level is set by auditors based on the required confidence level in their assessment, balancing the need for assurance with efficiency.
Step-by-step explanation:
The risk which the auditor is willing to take in accepting a control as being effective when the true population exception rate is greater than a tolerable rate is referred to as the audit risk. Specifically, this scenario is about the type I error or α risk, which is the risk of incorrectly rejecting a true null hypothesis while performing hypothesis testing. It is important for auditors to set a threshold for this risk to mitigate the chance of accepting an ineffective control. For example, in statistical terms, if an auditor is using a 90% confidence interval, there is a 10% risk that the true population mean does not fall within the calculated interval. This is analogous to accepting a control that might not be truly effective 10% of the time. Auditors must balance this risk assessment with the need for reasonable assurance and efficiency.