Audit Webinar: Surefire ways to succeed with Data Analytics
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The document outlines a webinar presented by Lenny Block from Nasdaq on the successful implementation of data analytics, emphasizing its importance to audit processes and identifying barriers to its adoption. Key topics include the necessity of specific skills, gaining management support, practical applications of data analytics in auditing, and understanding compliance, particularly regarding the FCPA. The summary also highlights the iterative nature of data analytics and its role in supplementing traditional audit techniques for more effective results.
Audit Webinar: Surefire ways to succeed with Data Analytics
- 1. SUREFIRE WAYS TO SUCCEED WITH DATA ANALYTICS WEBINAR
- 2. PRESENTER Lenny Block Associate Vice President NASDAQ Internal Audit
- 3. AGENDA 1. Who is NASDAQ? 2. What are the barriers to using Data Analytics? 3. How do you increase and expand use of Data Analytics? 4. Business and technology applications 5. What skills are required? 6. Gaining internal management support 7. Measure staff utilization and effectiveness 8. Takeaways & benefits to your organization
- 4. WHO IS NASDAQ? More than a stock exchange… • Multiple exchanges and clearing houses - NY, Philadelphia, Boston, Nordics, Baltics, Canada, Europe • Listing venue for publicly traded companies to raise capital (IPO) • Multiple asset classes (equities, options, commodities) Corporate Solutions • Investor relations, public relations, multimedia solutions, governance Market Technology • Trading and data solutions to exchanges, alternative-trading venues, banks and securities brokers • Internal audit team - 20 worldwide - NY, Maryland, Philadelphia, Stockholm, Vilnius
- 5. BARRIERS TO USING ANALYTICS • We know Analytics are important • While majority of internal audit leaders and C-suite executives agree data analytics is important to strengthening audit coverage, only a small percentage of organizations are actively using Data Analytics regularly • What are the barriers to starting, sustaining and expanding the use of Data Analytics?
- 6. BARRIERS TO USING ANALYTICS • Frustration: Natural reaction during implementation • Occurs for the following reasons: • Lack of technology skills • No experience • Not knowing how to incorporate a Data Analytics tool into the audit • Source data - How to load it into the tool? • Assessing progress
- 7. INCREASING USE OF DATA ANALYTICS • Eliminate frustration • These are familiar concepts • Small success using analytics builds confidence and shows value • Data Analytics is not a magic wand “If you do not know where you are going, any road will get you there.” -- Lewis Carroll
- 8. BUSINESS, TECHNOLOGY APPLICATIONS • Data Analytics can help to achieve audit goals: • What audit objectives we want to achieve • What questions about our data do we want answered • Validation of assumptions about whether systems are programmed correctly • Investment that pays off, requires perseverance • Expanded coverage • Better understanding of the data • Integrity of the data preserved • Will uncover concerns in other areas
- 9. DATA ANALYTICS HELP • Data Analytics helps with the following audit objectives: • Validate data accuracy • Display data in different ways – Prepare data for analysis • Identification of strange items, exception testing • Completeness (gaps, matching) • Validity of formulas and calculations • Edit checks • Compliance testing • Relationships (fuzzy logic)
- 10. THE CHALLENGE • Think outside the box • Examples of traditional and non-traditional ways data analytics tools can be used
- 11. BUSINESS APPLICATIONS • Technology • Utilize tools that are both business application and technology focused • Log files • Access Reviews • Alerts
- 12. EMAIL LOGS • Common tests • Summarize emails by service provider • Summarize and sort numbers of emails by employee • Isolate, summarize and examine personal emails • Stratify emails by time and examine any unusual activity (e.g., lunchtime, weekends, bank holidays) • Analyze incoming emails and identify common domain addresses
- 13. EMAIL LOGS • Common tests • Calculate and sort length of time employees spent on email in a given time period • Match emails with a list of employees and extract any emails that were sent by non-employees • Analyze any dormant accounts • Identify non-work related emails by searching for specific words
- 14. ACCESS RIGHTS • Identify accounts with: • Passwords not set or not required for access • Passwords < the recommended number of characters • Access to key directories • Supervisor status • Equivalence to users with high level access • That have not been used in the last 6 months • Group memberships • Age password changes
- 15. SYSTEMS LOGS • Identify accounts with: • Access outside office hours (Holiday/Sick Leave • Users, particularly those with supervisory rights • Perform data analysis by user • Summarize by network address to identify: • All users with their normal PCs or all PCs with their normal users • Users on unusual PCs • Summarize charges by user for resource utilization • Analyze utilization by period to show historical trends ie: daily, weekly, monthly
- 16. FILE ACCESS & MANAGEMENT • Monitor file activity and user behavior • Prevent data breaches and assists with permissions management • Monitor every file touch • Know when sensitive files and emails are opened, moved, modified or deleted
- 17. REGULATORY • Rule Book Validation • Independent validation of software algorithms utilized to ensure compliance with rules • For example: • To list on a national stock exchange and to remain listed companies must meet comprehensive qualitative and quantitative standards for both the company and the securities offered.
- 18. ETHICS – FCPA COMPLIANCE • FCPA Act - Enacted in 1977 • Impact of billion dollar fines • FCPA compliance is focused fraud analytics geared to bribery and anti corruption of government officials • One can not identify corruption straight up but you can identify red flags for follow-up
- 19. COST OF FCPA NON-COMPLIANCE Top ten FCPA enforcement actions (Average fine: $65 million) 1. Siemens (Germany): $1.6 billion in 2008 2. Alstom (France): $772 million in 2014 3. KBR / Halliburton (USA): $579 million in 2009 4. BAE (UK): $400 million in 2010 5. Total SA (France): $398 million in 2013 6. VimpelCom (Holland): $397.6 million in 2016 7. Alcoa (USA): $384 million in 2014 8. Snamprogetti Netherlands B.V./ENI S.p.A (Holland/Italy): $365 million in 2010 9. Technip SA (France): $338 million in 2010 10. JGC Corporation (Japan): $218.8 million in 2011 (Sources: FCPA Blog and SEC Websites)
- 20. FCPA COMPLIANCE How we use Data Analytics to ensure FCPA Compliance: • Identifying spending trends of vendors, contractors, employees • Prohibited list screening • Risk Scoring to identify high risk vendors, contractors • Supplemental traditional AP analytics
- 21. OTHER KEYS TO SUCCESS • Repeatable- “Productionalize” • Only need to refresh data • Visualization • Easily Interpret and summarize data in user friendly way • Drill down into the underlying data • Picture worth a thousand words • Just like auditing, data analytics is an iterative process, one set of results provides additional questions and the next step in your analysis
- 22. SKILLS SETS • Critical thinking • Understanding the business • Familiarity with automated solutions • Data extract query tools are already built in to ERP and other systems today. • SAP, PeopleSoft, Hyperion • Creative problem solvers, what do I want to know about the data?
- 23. SKILLS SETS • Not afraid of data and technology • Relational Database concepts versus Excel • Willing to adapt and grow their skill sets - Necessity for their careers • Investment of time to learn • Trial and error • Perseverance
- 24. GAINING MANAGEMENT SUPPORT • A necessity made easier… • To search manually for irregularities is almost impossible • Information is more complex • Automated tools are easier to use than before • To rely only on professional judgement can be subjective or based on poor information
- 25. SUPPLEMENTS TRADITIONAL AUDIT • Data Analytics is a supplement to traditional audit techniques • Expanded coverage • Better understanding of the data • Uncover concerns in other areas beyond the current area of focus • Data Analytics allows can grow into a continuous monitoring or continuous auditing program • Red flags resulting from data analytics can be used to develop a targeted scope for a traditional audit, drilling down to root causes and control gaps
- 26. STANDARDS HAVE CHANGED Critical Thinking Advanced Fuzzy Duplicate Trend Analysis PLANNING Data Discovery Data Sampling Visualization Data Insights Identify trends Trend Analysis & outliers Benford’s Law Analysis Focus the Audit DATA INTEGRITY CaseWare Analytics Profile your Data • Today Data Analytics is a requirement rather than a recommendation • Highlighted in the IIA standards under “Proficiency” where auditors need to have sufficient knowledge of “technology-based audit techniques” to do their work
- 27. STAFF UTILIZATION & EFFECTIVENESS • Build in to the methodology: • Require the auditor to address before fieldwork begins how analytics will be used. • It can be as simple as profiling data to determine sampling approach • Sample selection itself • Tie analytics to compensation and incentives
- 28. TAKEAWAYS & BENEFITS • Think outside the box • A necessity – Standards now include data analytics • Make it about the audit objectives, not the tool • Expanded coverage • Better understanding of the data • Better defense with regulators…mitigates actions of rouge employees • Lets people know we are watching • Job specific training (ie: anti-corruption activities) • Provide employee incentives to learn and use analytics
- 29. Learn more about CaseWare IDEA Data Analysis Contact us at salesidea@caseware.com to schedule a demonstration
- 30. SUREFIRE WAYS TO SUCCEED WITH DATA ANALYTICS WEBINAR Visit casewareanalytics.com Email salesidea@caseware.com