The Truth Behind Detecting Fraud Using Data Analytics
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The webinar covers the challenges and methodologies of detecting fraud using data analytics, emphasizing that it is not a simple process and requires substantial analysis. Participants must log in individually to receive CPE credits, answer polling questions, and follow specific guidelines to avoid technical issues. The document outlines the importance of understanding data cleaning, anomaly detection, and the necessity of using advanced data analytic tools to identify potential fraud effectively.
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The Truth Behind Detecting Fraud Using Data Analytics
- 1. 8/31/2017 1 THE TRUTH BEHIND DETECTING FRAUD USING DATA ANALYTICS WEBINAR HOUSEKEEPING This webinar and its material are the property of AuditNet® and its Webinar partners. Unauthorized usage or recording of this webinar or any of its material is strictly forbidden. • If you logged in with another individual’s confirmation email you will not receive CPE as the confirmation login is linked to a specific individual • This Webinar is not eligible for viewing in a group setting. You must be logged in with your unique join link. • We are recording the webinar and you will be provided access to that recording after the webinar. Downloading or otherwise duplicating the webinar recording is expressly prohibited. • If you have indicated you would like CPE you must answer all the polling questions to receive CPE per NASBA. • If you meet the NASBA criteria for earning CPE you will receive a link via email to download your certificate. The official email for CPE will be issued via [email protected] and it is important to white list this address. It is from this email that your CPE credit will be sent. There is a processing fee to have your CPE credit regenerated post event. • Submit questions via the chat box on your screen and we will answer them either during or at the conclusion. • Please complete the evaluation questionnaire to help us continuously improve our Webinars.
- 2. 8/31/2017 2 IMPORTANT INFORMATION REGARDING CPE! • SUBSCRIBERS/SITE LICENSE USERS - If you attend the Webinar and answer the required number of polling questions you will receive an email with the link to download your CPE certificate. The official email for CPE will be issued via [email protected] and it is important to white list this address. It is from this email that your CPE credit will be sent. There is a processing fee to have your CPE credit regenerated post event. • NON-SUBSCRIBERS/NON-SITE LICENSE USERS - If you attend the Webinar and answer the required number of polling questions and requested CPE you must pay a fee to receive your CPE. No exceptions! • We cannot manually generate a CPE certificate as these are handled by our 3rd party provider. We highly recommend that you work with your IT department to identify and correct any email delivery issues prior to attending the Webinar. Issues would include blocks or spam filters in your email system or a firewall that will redirect or not allow delivery of this email from Gensend.io • Anyone may register, attend and view the Webinar without fees if they opted out of receiving CPE. • We are not responsible for any connection, audio or other computer related issues. You must have pop-ups enabled on you computer otherwise you will not be able to answer the polling questions which occur approximately every 20 minutes. We suggest that if you have any pressing issues to see to that you do so immediately after a polling question. The views expressed by the presenters do not necessarily represent the views, positions, or opinions of AuditNet® LLC. These materials, and the oral presentation accompanying them, are for educational purposes only and do not constitute accounting or legal advice or create an accountant-client relationship. While AuditNet® makes every effort to ensure information is accurate and complete, AuditNet® makes no representations, guarantees, or warranties as to the accuracy or completeness of the information provided via this presentation. AuditNet® specifically disclaims all liability for any claims or damages that may result from the information contained in this presentation, including any websites maintained by third parties and linked to the AuditNet® website. Any mention of commercial products is for information only; it does not imply recommendation or endorsement by AuditNet® LLC
- 3. 8/31/2017 3 PRESENTER Sunder Gee Consultant, CPA, CMA, CIDA AGENDA • The Myth • What is Data Analytics • Leveraging the features of data analytics • Why You May Need Data Analytic Tools • The Reality • Examples
- 4. 8/31/2017 4 THE MYTH • Detecting fraud using data analytics is just a simple mouse click away • Simplistic presentation and article titles perpetuate the myth PERPETUATING THE MYTH • Bad title: “Detecting Fraud Using Data Analytic Tools” • International Workshop on ICT for Auditing, Lisbon, Portugal – June 21, 2017 • Better title: “Fraud and Fraud Detection: A Data Analytics Approach” • Published by John Wiley & Sons, Inc., Hoboken, New Jersey, ISBN 978-1-118-77965-1 • Best title: “Detecting Anomalies Using Data Analytic Tools for Internal Auditors”
- 5. 8/31/2017 5 WHAT IS DATA ANALYTICS? • Data analytics is the process of examining data in order to formulate conclusions WHAT DATA ANALYTICS CAN DO • Data analytic software enable users to obtain quick overview of data and can drill down to detail information • Using data analytic software, every transactions can be involved or touched • Identify anomalies, trends, patterns and concerns • Large volumes of data
- 6. 8/31/2017 6 POLLING QUESTION 1 The Truth Behind Detecting Fraud Using Data Analytics DATA OVERVIEW: PAYROLL
- 7. 8/31/2017 7 DATA OVERVIEW: FIELD STATISTICS DATA OVERVIEW: VISUALIZATION
- 8. 8/31/2017 8 DATA OVERVIEW: DESCRIPTIVES & STATISTICS INFORMATION Descriptives Data Statistics Data STANDARD DATA ANALYTIC FEATURES • Extract • Sort • Gaps • Duplicates • Aging • Samples • Summarize • Stratify • Join/Match
- 9. 8/31/2017 9 STATISTICAL & ADVANCED FEATURES • Benford’s Law • Trend Analysis • Time Series Analysis • Correlation • Z-Score • Relative Size Factor • Same-Same-Same • Same-Same-Different WHY YOU MAY NEED DATA ANALYTIC TOOLS “By using ADAs, auditors are able to discover and analyze patterns, identify anomalies, and obtain other information from relevant data populations that may be very useful to an organization.” • CPA Canada Audit Client Briefing Audit Data Analytics – May 2017
- 10. 8/31/2017 10 WHY YOU MAY NEED DATA ANALYTIC TOOLS • Standard 2210.A2 — The internal auditors must consider the probability of significant errors, fraud, non-compliance, and other exposures when developing the engagement objectives • Data analysis technology enables auditors and other fraud examiners to analyze transactional data to obtain insights into the operating effectiveness of internal controls and to identify indicators of fraud risk or actual fraudulent activities • GTAG 13 – Global Technology Audit Guide Fraud Prevention and Detection in an Automated World , IIA – December 2009 WHY YOU MAY NEED DATA ANALYTIC TOOLS • Internal control systems have weaknesses • The need to look at every transaction that takes place and test them • Sampling serves well when issues are relatively consistent throughout the data – but fraud does not occur randomly • Test specific hypothesis • Perform risk analysis and quantify fraud if determined
- 11. 8/31/2017 11 THE REALITY ABOUT FRAUD DETECTION • No magic to finding fraud • Fraud detection is part of a process • High number of anomalies from the process • Few errors • Fewer fraudulent transactions THE PROCESS: PREPARING THE DATA • Define audit objectives • Obtain the data • Verify • Normalize • Analyze • Apply rules/criteria
- 12. 8/31/2017 12 THE PROCESS: FINDING ANOMALIES • Resulting anomalies • Interpret the data, professional judgement • Reduce anomalies • Additional criteria • Cut off • Sampling • Investigate • Validate • Report POLLING QUESTION 2 The Truth Behind Detecting Fraud Using Data Analytics
- 13. 8/31/2017 13 POLLING QUESTION 3 The Truth Behind Detecting Fraud Using Data Analytics HIGH RISK ANOMALIES: PAYROLL DATA
- 14. 8/31/2017 14 EXAMPLE: PAYROLL DATA ANOMALIES • Same-Same-Same Test: • Same Employee Number + • Same Check Date + • Same Account Description (Payroll Type) • 19,854 Records EXAMPLE: PAYROLL DATA ANOMALIES
- 15. 8/31/2017 15 EXAMPLE: PAYROLL DATA ANOMALIES Same-Same-Same Regular Pay: • 11,645 Records PAYROLL DATA ANOMALIES Same-Same-Same Regular Pay: • Equal or greater than $5,000 • 312 Records
- 16. 8/31/2017 16 PAYROLL DATA ANOMALIES Same-Same-Same Regular Pay: • Summarize by Employee ID • 454 Records • Indexed (Descending) by Hours • Also index by: - Amount - Number of Records - Average Hours - Average Amount POLLING QUESTION 4 The Truth Behind Detecting Fraud Using Data Analytics
- 17. 8/31/2017 17 PAYROLL DATA ANOMALIES Same-Same-Same Regular Pay: • Random Sampling of 50 Records SUMMARY • By using anomaly detection methods, data analytics can help in finding fraud • Unusual patterns needs to be identified • With fraudulent transactions being rare, one must understand what is normal
- 18. 8/31/2017 18 POLLING QUESTION 5 The Truth Behind Detecting Fraud Using Data Analytics Questions?
- 19. 8/31/2017 19 [email protected] 1-800-265-4332 EXT. 2800 [email protected] AUDITNET® AND CRISK ACADEMY • Grants unlimited access to this and other AuditNet webinar recordings • Previous AuditNet® webinars are available on-demand for CPE credit http://criskacademy.com http://ondemand.criskacademy.com Coupon code: 50OFF Discount on this webinar for one week
- 20. 8/31/2017 20 THE TRUTH BEHIND DETECTING FRAUD USING DATA ANALYTICS WEBINAR