DescriptionThis dissertation has three essays. The first essay examines several analytical models that can be used in the insurance industry. We develop a continuous auditing framework for the insurance industry’s claims payment process. We propose analytical models to detect anomalies in the already paid claims and in the premium calculations. The second essay proposes a framework for developing the Audit Data Standards (ADSs) for specific industries. We apply the framework on the insurance industry. In specific, we apply it on claim payment business cycles of the life / disability insurance industry. We then use these ADSs to develop an interactive auditor dashboard. The third essay examines a possible way for the auditor to overcome data limitations. We examine the added value of using the macroeconomic indicators to improve the prediction and error detection performance of the statistical models used by the auditor through two research questions. our first research question investigated the effect of using macroeconomic indicators in the prediction models by comparing the Mean Absolute Percentage Error (MAPE) with and without the use of the macroeconomic indicators. our second research question investigated the effect of using macroeconomic indicators in the prediction models when the independent variables contain undetected errors. We tested each research question in three different situations; the macroeconomic variable is used individually, collectively, or with the peer data. our results came in favor of the macroeconomic indicator’s use, specifically when used along with the peer data.