The importance of cybersecurity to you, the accounting and finance professional, and your organization or client What it takes to develop a security mindset to be a trusted adviser and key contributor toward cybersecurity risk management Key cybersecurity terminology to enable you to converse and collaborate with other functional leaders, employees and vendors The impact of digital transformation on cybersecurity
Determine the relevance of risk assessment procedures in gathering evidence to direct audit effort and support the audit opinion, including establishing a proper audit materiality. Identify key points related to the auditor’s requirements regarding internal control as part of a financial statement audit. Recall the relevant information regarding the Committee of Sponsoring Organizations of the Treadway Commission (COSO) framework. Recognize the potential of audit data analytics in risk assessment procedures.
Recall the basics of internal control, including using the work of others. Identify the key concerns regarding fraud considerations in a GAAS audit. Recall the purpose and procedures regarding analytical procedures and their use in an audit. Identify the audit procedures typically performed by new staff in the following areas and match them to stated audit objectives and relevant assertions: Cash and cash equivalents Accounts receivable Inventory Prepaid and other current assets Property, plant, and equipment Accounts payable Debt
Recall the audit risk model and its elements. Recall how the audit risk model combines risks to assess overall audit risk Understand the audit risk model and how it is used at the onset of and throughout the audit process. Learn how the audit risk model works as a tool that can help peer reviewers and inspectors determine the sufficiency of procedures performed.
Define the characteristics of an analytical and data-driven mindset. Recognize how to establish objectives and desired outcomes of a data analytics project for a business or client. Recognize ways data is described and interpreted. Describe the types and categories of data. Recognize how data science and data analytics are connected. Recognize characteristics of the technology and data ecosystem for data analytics.
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