MACC — Data and Analytics

The W. P. Carey Master of Accountancy (MACC) is among a select group of accounting master’s programs that offers a data and analytics track in partnership with KPMG.

Delving into the technologies and methodologies used in today’s complex, data-centric audits, the data and analytics track prepares you with the analytical skills and critical thinking needed to keep pace with the modern world.

Distinct opportunity for future accountants

Building upon traditional accounting principles, this program prepares students to excel in a range of professional environments. Hands-on experience is critical to that development. From internships to applied elective courses and beyond, all data and analytics students are encouraged to pursue learning opportunities and experiences with relevance to their future goals.

Rigorous curriculum with real-world relevance

Developed in partnership with KPMG, the data and analytics track provides a solid foundation in the technologies and methodologies used to navigate today’s highly complex and data-centric audit and financial consulting environment.

Note: Data and analytics track curriculum as listed is tentative, pending final approval.

Addresses internal control frameworks and US Generally Accepted Auditing Standards related to an auditor’s consideration of internal controls for purposes of financial statement audits and audits of internal control over financial reporting. The course covers various schemes pertaining to misappropriation of assets, corruption, and fraudulent financial reporting. Using audit software, you will evaluate control risks and fraud detection.

Examines the emerging roles of accounting analytics in business, auditing, and tax contexts. Technological advances have allowed the capture and economic storage of massive accounting and business data; the course focuses on how to productively gather and apply Big Data to a variety of accounting related contexts. Learn to understand the data within major accounting information systems and generate meaningful audit and/or tax analytics from the data. A deep understanding of accounting flows, processes, and controls is critical to understanding and building meaningful audit-centric and/or tax-centric analytics.

Builds on skills obtained in the beginning auditing course, including audit planning, evidence, and reporting procedures along with addressing audit risks. Key elements of the course include case- and application-based approaches for evaluating advanced analytical procedures, as well as auditing complex accounting estimates and fair values measurements.

Develops familiarity and expertise with tools and techniques for framing research questions about accounting and financial reporting issues, finding authoritative answers and evidence-based answers to such questions, and communicating the results. This case-based course provides hands-on experience researching relevant accounting issues.

Explores theories of probability and uncertainty through statistics — including descriptive, predictive, and prescriptive analyses — as well as regression and other models to support audit decisions and conclusions.

Analyzes the role of financial statements and non-financial indicators in measuring value creation. You will learn to develop equity valuation models that incorporate business strategy and forecasting in evaluating the economic drivers of value and create and present a high-quality valuation report.

Considers the role of technology-related innovations on audits and auditing performance. The course will look at both capturing data from recent innovations in technologies for audit applications (e.g., IoT) as well as examining roles of these recent technology innovations for audit performance (e.g., cognitive computing).

Examines the design of insightful business data visualizations and dashboards to improve business decision-making. You will learn to apply advanced data visualization techniques to make sense of large data sets including temporal, geospatial, topical, and business data, while also making it easier to digest, present, and utilize for business needs and users.

Explores corporate governance systems by which corporations are directed and controlled, and how these may contribute to sustainable enterprise. A case-based approach facilitates class discussion on the mechanisms of governance, analysis organizational strategies that facilitate sustainable, high–performing organizations, and the balance among various stakeholders.

Introduces the practice of data mining and predictive modeling. You will learn the fundamental principles and techniques of data mining, and examine real-world examples and data to place data-mining techniques in context and develop data-analytic thinking. Through coursework, you will gain a broad set of practical data mining and predictive modeling skills based on hands-on experience with a data mining software, SAS Enterprise Miner.