Process mining refers to analyzing business processes using the event log information from the accounting information systems. Process mining techniques have been widely applied in many research domains; however, the application of process mining in auditing has just emerged. Motivated by the potential benefits of applying process mining to auditing, this dissertation consists of three essays that examine how process mining can serve as new audit evidence to evaluate internal control effectiveness, assist auditors in audit risk assessment, and identify fraud schemes. The first essay aims at adopting process mining to evaluate the effectiveness of internal control using a real-life event log. Specifically, the evaluation is based on the full population of an event log and contains four analyses: (1) variant analysis that identifies standard and non-standard variants, (2) segregation of duty analysis that examines process instances and employees that violate segregation of duty controls, (3) personnel analysis that investigates employees who are involved in multiple potential control violations, and (4) timestamp analysis that detects time related issues such as the process instances that have lengthy process duration. The second essay aims at building a framework on how auditors can utilize both routing and transaction value information when using process mining as a new type of audit evidence. Specifically, this framework is based on auditor’s risk assessment. The application of the proposed risk assessment framework on an event log from a not for profit organization shows that auditors could benefit from the prioritized process mining results as they could focus on process instances with material transaction values and have higher risk scores. The third essay aims at providing a framework on how process mining can be applied to identify corporate fraud schemes and assessing the riskiness of business processes. Specifically, the proposed framework captures how the patterns in process mining can be used to detect potentially fraudulent transactions. This essay contributes to the existing literature by associating non-standard variants/activities with potential fraud schemes and then assigning risk levels, which could be used as an automatic tool to test the fraud risk of every transaction.