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Detecting Fraud Using Data Analysis Seminar- Live Online

SKU: s-201026 Category: Tag:
Start
Oct 26, 2020 - Oct 27, 2020 | 08:30 AM - 04:30 PM CST | Live Online | 16 CPE
End
Address
Live Online | 8:30 AM Central   View map

$895.00

17 in stock

Status

17 Seats Available

1 Has Sold


During this two-day, hands-on seminar, attendees will apply data analysis techniques to real-life fraud scenarios using data files and case studies to identify and solve problems. Our goal is to teach audit and accounting professionals to detect fraud, waste and abuse early and address them professionally. This event will qualify for 16 CPE credits in Specialized Knowledge/Fraud.

  

Who should attend: Auditors, Investigators, Accounting Professionals.

  

Whether you are a seasoned investigator or someone seeking a better understanding of what can go wrong in your organization, you will benefit from this program. Novice auditors or those new to data analysis will learn and employ fundamental detection techniques to real cases, while advanced users and investigators will apply their knowledge in new and challenging ways to detect buried symptoms within complex schemes.

  

The Instructor will provide downloadable data for use in class. Don't use IDEA? A virtual interactive platform of IDEA software will be provided to you. IDEA runs in Windows and is not compatible with the Mac operating system. From the opening exercise, we will employ a team approach to solving cases, as in the field. Within IDEA, you will apply to actual case data: Creative Extractions; Statistical Analyses; Join-matches & mismatches; Trend Analysis; Pivot Tables; Embedded Functions; Field Manipulation; Numeric & Date Stratification; Benford's Law; Data Duplications & Exclusions; and more!

 

Scott Langlinais, CPA

 

Scott has over 20 years of experience in fraud detection and investigation. He has planned and conducted examinations related to executive corruption, bribes, kickbacks, vendor overbilling and underperformance, and employee theft. Scott regularly reports his findings to Boards of Directors, has testified in court on fraud matters, and has submitted his findings to federal law enforcement.

  

Scott regularly employs data analysis software to develop continuous monitoring programs and to perform searches for circumstances such as: unbilled revenues, unauthorized cash transfers, employee reimbursement and P-card improprieties, and payments to fictitious vendors and employees. He develops strategic plans including risk analyses, policies & charters, continuous monitoring, Sarbanes-Oxley (SOX) compliance, and procedures for effective internal consulting for organizations of all sizes across various industries.  He has authored white papers on fraud prevention, detection, and response for the International Risk Management Institute and serves as a regular guest speaker at nationwide conferences and chapter meetings held by the IIA, the ACFE, the AICPA, and ISACA. Prior to starting his own practice in 2003, Mr. Langlinais held public accounting and internal audit leadership positions, and served as Chief Audit Executive for a NASDAQ 100 software company. He received a BBA degree from the University of Notre Dame in 1991.

 
Preparing to Detect Fraud
  • Factors that discourage us from detecting fraud.
  • Building discipline to handle wrongdoing and avoid the dangers of mishandling cases.
  • Applying a five-step approach to fraud detection.
  • Understanding what can go wrong and recognizing symptoms of wrongdoing.
  • Correcting problems with the data import, identifying missing and hidden data.
  • Keeping your data organized.
Detecting Fraud with IDEA
  • Identifying patterns through statistical review, data sorting, and field summarizations.
  • Effective and creative extractions for disbursements, employee reimbursements, liquid assets, revenues, and general ledger transactions.
  • Employing editable fields to flag anomalies.
  • Applying duplicate key detection/exclusion, and combining with field manipulation to detect circumvention of system controls.
  • Avoiding six common errors in data analysis.
  • Stratifying data to detect approval circumvention, earnings management, and money laundering.
  • Using special functions to carve out symptoms embedded within blocks of data.
  • Employing join-matches and mismatches to detect fictitious vendors, revenue leaks, and false shipments.
  • Extracting key-word symptoms of corruption and fraudulent financial reporting.
  • Application of pivot tables, Benford's law, and trend analysis.
Putting It All Together
  • Developing programs to detect theft and fraudulent reporting.
  • Applying techniques to solve cases from allegation to presentation of evidence.
  • Weaving techniques into a continuous monitoring program.
  • Using principles of effective thinking and presentation to compile effective evidence.
Through hands-on instruction, taught at an optimal learning pace, attendees will learn how to:
 
  • Apply a five-step approach to fraud detection, and avoid the dangers of mishandling cases.
  • Blend traditional detection methods with data analysis techniques.
  • Correct problems with the data import, identifying missing and hidden data.
  • Keep data organized and use editable fields to isolate problems.
  • Employ more creative extractions to increase the chance of detecting wrongdoing.
  • Use effective techniques for detecting circumvention of system controls.
  • Extract symptoms embedded within blocks of data.
  • Identify symptoms of theft and fraudulent reporting within common processes.
  • Use principles of effective thinking and presentation to compile strong evidence.
NASBA CPE LogoAudimation Services, Inc. is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of the continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website: nasbaregistry.org
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