SUREFIRE WAYS TO SUCCEED WITH DATA ANALYTICS

WEBINAR

PRESENTER

Lenny BlockAssociate Vice President NASDAQ Internal Audit

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

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

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?

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

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

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

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)

THE CHALLENGE

• Think outside the box• Examples of traditional and

non-traditional ways data analytics tools can be used

BUSINESS APPLICATIONS

• Technology• Utilize tools that are both business application and technology

focused• Log files• Access Reviews• Alerts

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

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

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

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

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

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.

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

COST OF FCPA NON-COMPLIANCE

Top ten FCPA enforcement actions (Average fine: $65 million)1. Siemens (Germany): $1.6 billion in 20082. Alstom (France): $772 million in 20143. KBR / Halliburton (USA): $579 million in 20094. BAE (UK): $400 million in 20105. Total SA (France): $398 million in 20136. VimpelCom (Holland): $397.6 million in 20167. Alcoa (USA): $384 million in 20148. Snamprogetti Netherlands B.V./ENI S.p.A (Holland/Italy): $365 million in 20109. Technip SA (France): $338 million in 201010. JGC Corporation (Japan): $218.8 million in 2011

(Sources: FCPA Blog and SEC Websites)

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

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

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?

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

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

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

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

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

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

Learn more about CaseWare IDEA Data Analysis

Contact us at salesidea@caseware.com to schedule a demonstration

SUREFIRE WAYS TO SUCCEED WITH DATA ANALYTICS

WEBINAR

Visit casewareanalytics.com Email salesidea@caseware.com