SUBSTANTIVE ANALYTICAL PROCEDURES IN SHARIA COMPLIANTS AS AGREED-UPON PROCEDURES SERVICE IN ITALIAN CORPORATE GOVERNANCE

Islamic finance is a complex of banking, financial and insurance activities carried out in accordance with the dictates of Islamic law (shari'a) and which can be framed in the broader genus of ethical or sustainable finance. Since its inception, but especially in the last thirty years, it has experienced constant and surprisingly rapid growth. However, the rise of Islamic finance has remained confined to some specific geographic realities, failing, at least for the moment, to establish solid roots in the European, Australian or American markets. Although Islamic finance began to appear on the European scene as early as the early 2000s, the response of the states was, in general and with some relevant exceptions, rather disappointing. In Italy, for example, the spread of this phenomenon is hindered by the absence of regulatory frameworks, by a distorted narrative and communication as well as by technical and cultural barriers. This work aims to be a reflection on various aspects - historical, social and economic - of Islamic finance of which our country, by virtue of its geopolitical position and its historical traditions, should become more aware. [1]

Can Substantive Analytical Procedures with Data and Data Analytics Replace Sampling as Tests of Details?

To avoid problems caused by moderate or weak substantive analytical procedures (SAPs), audit firms tend to focus more on tests of details than SAPs, especially for large income statement accounts such as revenues. Based on findings from previous studies, this commentary study attempts to: 1) summarize the outcomes of SAPs developed by advanced analytics models (e.g., regression and time series models), and 2) respond to the question of SAP use by evaluating the limitations and benefits if one test replaces the other. The outcomes of prior studies generally show that SAPs developed by advanced analytical models do not provide a high level of assurance for revenue. Since SAPs and audit sampling present different risks and unique benefits, they are often complementary. Without the careful consideration of conditions related to the risks and benefits of each test, simply avoiding SAPs could reduce the effectiveness of substantive tests.

The Reel Wheel: Using Analytical Procedures as Substantive Tests of Account Balances

ABSTRACT This case provides students an introductory experience to substantive analytical procedures in a realistic audit setting. Students are presented with a scenario, adapted from a real-world example, requiring them to (1) research relevant auditing standards, (2) develop an independent expectation for a client's revenue account, and (3) consider the precision of the estimate, additional audit procedures, and the reliability of the underlying data and evidence obtained. In completing the case, students will learn to: (1) explain the benefits and challenges of using substantive analytical procedures, (2) research relevant auditing standards, (3) create and analyze relevant substantive analytics, (4) evaluate the appropriateness of data aggregation in substantive analytical procedures, and (5) discuss factors affecting the reliability of data used by the auditor. The case is typically assigned as an out-of-class assignment, combined with a subsequent in-class discussion. It can be used in either undergraduate or graduate auditing courses.

Disclosure and Audit Implications of Nonfinancial Measures: A Teaching Case

SUMMARY This case introduces students to nonfinancial measures (NFMs) and encourages thoughtful consideration and discourse surrounding their reporting and use by managers and auditors. NFMs are commonly reported by companies to provide increased transparency of operations and to more effectively describe performance. External parties such as analysts and auditors make use of NFMs in performing valuation assessments, fraud risk assessments, and substantive analytical procedures. In completing this case, students will be exposed to actual NFMs disclosed in SEC filings and employ Microsoft Excel knowledge to perform foundational analytical procedures. Students will also analyze how these NFMs link to the financial statements, as well as reflect upon the implications of NFMs for both internal and external users.

Between a Rock and a Hard Place: A Path Forward for Using Substantive Analytical Procedures in Auditing Large P&L Accounts: Commentary and Analysis

SUMMARY Substantive analytical procedures can be an important and effective audit tool to gather evidence and highlight areas of potential misstatement, and for decades have been one of the common substantive procedures applied to income statement accounts. Recently, however, there is a growing trend for public company auditors to forego substantive analytical procedures on large income statement accounts, such as revenue, due to criticisms from regulatory inspectors that such procedures are not capable of providing useful substantive evidence. In this commentary, we address the concern that discouraging the application of appropriately rigorous substantive analytical procedures may diminish overall audit quality. We consider whether rigorous substantive analytical procedures can be designed to provide useful evidence at moderate and low levels of assurance for large income statement accounts, such as revenue, even when the significant-difference threshold exceeds overall materiality. Such procedures can provide strong evidence that financial statements are free of massive fraud or unintentional misstatement. Further, the moderate or low assurance obtained by such substantive analytical procedures can be combined with assurance provided by other audit procedures to yield high overall assurance. We illustrate one potential approach that may be useful in designing substantive analytical procedures to achieve moderate or low assurance and we explain how our approach is consistent with auditing theory and auditing standards.

Causal Inference in Auditing: A Framework

SUMMARY Causal inference—that is, determining the “root cause(s)” of an observed anomaly—is one of the most fundamental audit tasks. This study develops an analytical framework to formally model conditions present in many audit settings, and provides illustrations related to performing substantive analytical procedures. We examine four conditions not fully considered in prior research: multiple hypotheses about what may cause an anomaly, multiple items of evidence with varying diagnosticity, observed effects that may not be certain, and hypotheses sets that may not be exhaustive. The results reveal when the following phenomena should occur: (1) discounting or inflating of posterior probabilities, (2) superadditive probabilities of various causes, and (3) unchanged probability of a potential cause given evidence in support of a different cause. The analytical findings have implications for the design and interpretation of experimental auditing research, for educating novice auditors, and for potentially improving audit practice.

Auditors' Assessment and Incorporation of Expectation Precision in Evidential Analytical Procedures

This paper reports on an experiment that investigates auditors' abilities to assess expectation precision and incorporate their assessments into judgments related to substantive analytical procedures, as required by professional standards. Auditors appear sensitive to both account predictability and level of information detail in assessing expectation precision overall; however, their assessments do not reflect differences in level of detail when the account is less predictable. This finding supports regulators' and prior researchers' calls for additional guidance to assist auditors in forming expectations that consider the nature of the account. We also find that auditors judge the level of assurance from analytical procedures consistent with their precision assessments. However, in contrast to guidance specified in professional standards, we find that auditors do not always incorporate their precision assessments into judgments about the range of possible differences between expected and recorded amounts, nor the likelihood of misstatement causes. Failing to do so may lead auditors to make important decision errors.