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Audit & Forensic Data Analysis with MS Excel
Rating: 4.1 out of 5(153 ratings)
590 students

Audit & Forensic Data Analysis with MS Excel

An exhaustive and comprehensive course on Data Analytics for Audits and Forensic Accounting
Created byNikunj Shah
Last updated 5/2020
English
English [Auto],

What you'll learn

  • 1. Implement Digital Analysis techniques like Benford's Law and Relative Size factor Theory (RSF) in Excel to identify red flags or fraudulent transactions
  • 2. Use Pareto analysis (80-20 rule) and identify high value (and high risk) transactions
  • 3. Use Statistical measures like Standard Deviation and Coefficient of variation to zero-down on transactions of audit interest
  • 4. Re-engineer your audit processes to create dramatic efficiencies in analysis and reporting
  • 5. Perform a ‘Time Dimension’ analysis on data, learn to interpret results
  • 6. Perform a Vendor master clean-up and identify suspicious and fraudulent vendors
  • 7. Connect Excel worksheet to corporate (or Tally) database & extract any data that you want
  • 8. Connect your Excel worksheet to live data on the Internet to track (for e.g.) current value of investments
  • 9. Get Kaleidoscopic views on data by slicing and dicing the data
  • 10 Automatically create, from a single report within Excel, a report for each of the vendor's transactions (for confirmation)
  • 11. Detect non-compliance with organizational policies & compliance frame work
  • 12. Identify revenue leakages, double payments, etc.
  • 13. Work with large data sets (even more than million rows) in Excel

Course content

12 sections • 95 lectures • 12h 19m total length

  • Data Files/ Resources0:03
  • Welcome & Introduction to Concepts1:44

    Explore different kinds of analytics, concepts of business and forensic data analysis using Microsoft Excel, and the phases of an audit analytics engagement.

  • Types of Analysis8:55

    Describe how analytics move from descriptive to diagnostic, predictive, and prescriptive in Excel, using data mining and statistical models to understand past patterns, causes, forecasts, and optimized decisions.

  • Business Analytics2:57

    Explore how data-based decision making drives business analytics and informs audit and forensic data analysis.

  • Audit Analysis and Forensic Data Analysis28:45

    Use audit analytics in MS Excel to evaluate internal controls—design, implementation, and operation—identify revenue leakage and noncompliance, and distinguish audit analytics from forensic data analysis.

  • Formal Definitions3:39

    Learn the formal definition of business analytics and how data analytics informs decision making, audits internal controls and noncompliance with internal and external regulations, and forensic data analysis detects fraud.

  • Skill Sets & Phases7:48

    Identify essential skill sets and the four sequential phases of audit and forensic analytics in Excel, from defining objectives to data analysis and interpretation, to forming an audit opinion.

  • Data Integrity20:41

    Learn how data integrity underpins audit and forensic analytics, using disk imaging to create exact data copies, hash values to verify integrity, and chain-of-custody practices for court proceedings.

  • Closing Remarks on Concepts2:29

    Recap key audit analytics and forensic concepts, including data integrity and chain-of-custody practices. Preview hands-on Excel techniques for importing, analyzing, and forming an audit opinion in the next module.

Requirements

  • At least 6 months experience of working on MS Excel

Description

Challenges are multifarious. Overwhelming nos. of transactions, loss of conventional (paper) audit trail, system based controls, ever increasing and complex compliance requirements are amongst the prime reasons why traditional methods of collecting and evaluating evidence (like vouching and verification) are no longer adequate. The auditor can no longer treat Information Systems as a ‘Black Box’ and audit around it. His methods and techniques have to change. This change is what the world calls today, ‘Assurance Analytics’ i.e. data analysis from an ‘audit perspective’.


Using advance features of MS Excel, the auditor can access client’s data from their databases and analyse it to discharge the onerous duty cast on him. Since over 15 years, CA Nikunj Shah has been perfecting these techniques of ‘assurance analytics’. These include digital analysis techniques like Benford’s Law, Relative Size Factor Theory (RSF) and Pareto’s 80-20 rule that have enabled auditors and forensic investigators to identify control failures and over rides, detect non-compliance with laws, zero down on questionable transactions and identify red flags lost in millions of transactions. It is like quickly finding the needle in a hay stack!! In this unique course, your favourite instructor shall share the best of his research, auditing and training experience. The participants shall learn, step-by-step, the nuts-and-bolts details of using advance features of Microsoft® Excel coupled with the instructor’s insights to apply them in real-world audit situations. Each section shall equip participants with assurance analytic techniques using real-world examples and learn-by-doing exercises.

Who this course is for:

  • 1. Chartered Accountants, Managers, Team Members and Articled Trainees in Audit function (All types of Audits like Internal, Statutory, Management, Performance, etc.)
  • 2. Heads, Managers and Team Members in Financial Accounting function
  • 3. Forensic Accountants and Financial Fraud Investigators
  • 4. Information Systems Auditors

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