Course Information

In this course, discover how mathematical tools available in Excel allow you to perform powerful analysis of relationships in data. Are you data rich, but information poor? Are you trawling through copious amounts of data, but can’t see the forest for the trees? ‘Data Analytics’ is a buzz word in our industry, but not all ‘Data Analytics’ are alike… ‘Data Analytics’ can range from simple comparisons (e.g. finding duplicate payments in accounts payable) to complex analyses (e.g. identifying statistical outliers for potential fraud). And often, there’s a catch, since many Data Analytics experts will say you need to buy expensive software to deploy the analytics. This is a myth!

In this course you will look at your data differently and discover how ‘complex’ analytics can be made easy using math tools available in Excel to assist you in identifying and concentrating your testing on the high risk issues that matter. You will learn how to apply regression analysis in an audit context and audit smarter by quickly and efficiently identifying outliers and targeting your testing, thus saving you audit time and costs. Do all of this while complying with the GAO’s yellow book and AICPA standards.

You will also learn how to take it to the next level by building statistical bounds and adding benchmarks to your analysis. You will identify and address some common complexities that arise when running regression in the real world, which will help you to persist with your analysis when hurdles arise. Further you will discover how regression analysis can enable you to address your responsibilities to obtain reasonable assurance that accounts are free from material misstatement caused by fraud.  

Upon completion of this course, participants will be able to:

• Understand and employ multiple types of analytics in an audit context, but in particular, regression analysis.
• Distinguish between differing types of audit evidence and their associated costs.
• Comply with promulgated internal and external audit standards for analytical procedures.
• Introduce efficiency and effectiveness into the audit process via analytical procedures.
• Perform regression analysis in Excel.
• Assign statistical confidence and tolerances to regression analyses in Excel.
• Apply benchmarks to analyses.
• Utilize features of the Analysis ToolPak in Excel.
• Address common complexities that arise when analyzing data.
• Perform correlation analysis and multivariate regression.

Detailed Course Outline

DAY 1

The Audit Risk Model and What’s In It for Me?

•        Challenging the Traditional Audit Approach

•        The Audit Risk Model and Cost of Audit Evidence

•        The Key to Efficient Auditing

•        What World Class Audit Team are Doing

•        Are You Auditing Harder or Smarter

Clarifying Confusion Around The ‘Analytics’ Juggernaut

•        Data Analytics v Analytical Procedures

•        Using Analytics to Risk Assess

•        Where are you on the Data Analytics Maturity Scale

•        The Standards Encourage Smarter Auditing via Analysis

The Six Levels of Analytical Procedures

•        Level 1 Trend Analysis

•        Level 2 Financial Ratio Analysis

•        Level 3 Operational Metrics

•        Level 4 Anchor & Adjustment Tests

•        Level 5 Reasonableness/Mini-Max Tests

•        Level 6 Simple Linear Regression

How to Perform Simple Linear Regression

•        Step-by-step Guidance and Case Study

•        Simple Linear Regression via the Analysis Toolpak

•        Why Do These Statistics Matter

Setting Statistical Confidence and Tolerances

•        Defining Confidence and Tolerances

•        Step-by-step Guidance and Case Study

•        Adding a Benchmark to Your Analysis

•        Dealing with Outliers/Anomalies

Dealing with Complexities in Your Data

•        Noise Due to Sub-Populations

•        Case Study

•        Noise Due to Lagging

•        Case Study

•        Non-Linear Regression

•        Case Study

DAY 2

Frequently Asked Questions and Related Support

•        Sources of Data

•        Causation and Correlation

•        Applying Regression for Targeted Auditing

•        What is a Good R2

•        Using the 45 Degree Line as a Benchmark

•        Limitations of Excel

•        Ideas for X and Y

Multivariate Regression and Correlation Analysis

•        Correlation and Testing for Independent Variables

•        Correlation Analysis Step-by-Step Guidance and Case Study

•        Multivariate Regression

•        Multivariate Regression Step-by-Step Guidance and Case Study

Previous Attendee Regression Presentations

•        Real World Applications of Regression

Analysis for Fraud, Waste and Abuse

•        The Elusive Completeness Assertion

•        How Fraud is Found

•        Fraud Statistics in the Local Region  

•        Gap Analysis and Case Study

•        What Happens When The Data Has No Integrity and Cast Study

•        Flags for Systematic Fraud and Case Study

•        Analytics for Fraud Risk Assessment and Case Study

What Might have Gone Wrong and Indicators You Got it Right

•        What Might have Gone Wrong

•        Indicators You Got it Right

The Student Becomes the Teacher

•        Some Talking Points to Remember

•        Construct dashboards for Continuous Auditing/Monitoring

•        Are you Auditing Harder or Smarter?

•        The Vast Benefits of Advanced Analytical Procedures

•        You Can Audit Smarter!

• Learn how to reconstruct questionable or missing source data and use regression analysis to identify systematic fraud.
• Address frequently asked questions when performing regression in an audit context.

TAC Rule 523.142(g) requires the CPE Sponsor to monitor individual attendance and assign the correct number of CPE credits. Participants will be asked to document their time of arrival and departure in compliance with this Rule. Additionally, attendance will be monitored throughout the day and CPE certificates will reflect actual attendance of each participant.

If you are making travel plans to come to Austin, we recommend making "refundable" air and hotel reservations or waiting until 14 days before the class to actually book your reservations. Courses are occasionally canceled or rescheduled due to low enrollment. We determine whether a course has enough participants 16 days prior to the course date. If we cancel or reschedule, we will email the participant and his or her billing contact no later than 14 days before the original class date.

The course coordinator will contact you with parking information. Handicapped parking is free at the meters around the downtown area.

Vending machines with Coca-Cola products and various snack items are available. There is also a refrigerator and microwave in our coffee bar area. Feel free to bring in your own drinks and food if you prefer.

You might want to bring a light sweater or jacket, as room temperatures vary.

To see answers to our Frequently Asked Questions, visit http://www.sao.texas.gov/training/faq.html.