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Proprietary
ANALYTICS FOR
AUDIT
©2019 Alteryx, Inc.
Proprietary
©2019 Alteryx, Inc.
GOALS OF IA WITH ANALYTICS
• Better testing of controls through 100% population testing
• Be more efficient in auditing controls
• Develop and deploy Continuous auditing
• Increase visibility to internal and external risk
• Meet expectations of internal and external stakeholders
• Lead a world class audit department
• Stay ahead of the trends
Proprietary
©2019 Alteryx, Inc.
WHY USE ANALYTIC TOOLS?
• Provide support for audits
• Provide data samples for audits
• Use data / metrics to perform a Risk Assessment
• Assist in determine data to look at prior to the audit. Risk
rating of controls
• Develop Continuous Monitoring applications to drive
adoptions within the business.
Proprietary
©2019 Alteryx, Inc.
• Data Access
• Understanding where to find the data and what to get
• Data is not available in electronic format
• Data corruption
• Reluctance to Change
• Executive Buy-in for investment
CURRENT CHALLENGES
Proprietary
©2019 Alteryx, Inc.
OVERCOMING CHALLENGES
• Data Access – assure IT read only access is
required
• Understanding where to find the data and what
to get – work with the business to understand
processes and where the data can be found
• Data is not available in electronic format –
leverage OCR technology to convert data into
electronic format
• Data corruption – normally a result of using
tools to pull and convert data. Request direct
access to data.
• Reluctance to Change – show the value of
analytics and how it improves the job function
• Executive Buy-in for investment – perform a
pilot with analytics to show quick wins.
Proprietary
TRENDS
©2019 Alteryx, Inc.
• Cyber Security Analytics (IT Audit)
• Compliance (ie, FCPA, SOX)
• Predictive Analytics
• Cloud based data sources (API’s)
• GRC / GRC
• Assist and/or compliment with RPA
• Key Risk Indicators (KRI’s)
A LT E RY X U S E D F O R :
Proprietary
CVS HEALTH
BUSINESS CASE
©2019 Alteryx, Inc.
Proprietary
OBJECTIVE
Leverage data, analytics and
technology to provide the highest
level of business assurance during
the audits.
©2019 Alteryx, Inc.
Proprietary
©2019 Alteryx, Inc.
MINDSET
Start with capabilities then deploy to audit projects
Experimental
Data Science Lab approach- don’t mix
undeveloped capabilities with active audits
Commitment
Resources & funds dedicated to
Analytics, Automation, RPA and AI
Authority to decide our own projects
Autonomy
Leverage Corporate Resources
Resourceful Capability based
32
4 65
 OCR & encryption
 Unstructured data
 Robotics
 Dashboarding
 Self-Service
 Risk & predictive modeling
 Natural Language Processing
 Geospatial analytics
 In-database analytics
 Unsupervised models
Intentional1
Daily scrums with 2-week sprints arranged to
deliver to the customer
Proprietary
©2019 Alteryx, Inc.
Audit Analytics Model
DATA RPA AI+ + +
DO
ANALYTICS = ASSURANCE
THINK ANALYZEGET VALUE
Proprietary
©2019 Alteryx, Inc.
ONE AUDITOR, ONE AUDIT, ONE WEEK
Proprietary
©2019 Alteryx, Inc.
T&E BUSINESS EXAMPLE
Risky T&E Transaction
ANALYTICS
RPA
AI / Machine Learning
Transactions Source System Audit DW Data Enrichment
- MCCs
- Org Details
- Demographics
Data Validation
Testing rules
to validate the
data
Merchant Info
Webster obtained
additional details from a
website about the
merchant
Descriptive Analytics
Proprietary
©2019 Alteryx, Inc.
T&E BUSINESS EXAMPLE
ANALYTICS
RPA
AI / Machine
Learning
Prescriptive Analytics Risk Scoring Prediction
20+ Audit
Tests
Early Warning UnsupervisedReconciliation
Ron validates success
of the automated feed
and documents
completeness and
accuracy
Prediction model uses
historical audit findings
to assess the likelihood
of the transaction of
being an exception
Risk model uses
quantitative and
qualitative calculations
to assess transaction
risk
ELI Identifies a risky
transaction and sends an
email with the analysis
Unsupervised models
create clusters of
entertainment and
miscellaneous expenses
Proprietary
PRESCRIPTIVE ANALYTICS
Proprietary
RISK SCORING
Proprietary
RISK SCORING
Proprietary
PREDICTION SCORING
Proprietary
PREDICTION SCORING
Case ManagementAudit Exceptions
Predictive Variables
Results
(Risk Score)
Logistic Regression
Historical Exceptions
Accuracy Check
Model
Penny
(Bot gathering info)
Proprietary
RISK MONITORING
Proprietary
EARLY WARNING
SYSTEM
©2019 Alteryx, Inc.
Proprietary
IN THE NEW WORLD, IT IS NOT
THE BIG FISH WHICH EATS
THE SMALL FISH, IT'S THE
FAST FISH WHICH EATS THE
SLOW FISH
KLAUS SCHWAB
©2019 Alteryx, Inc.
FINAL THOUGHT…

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Analytics for Audit

  • 2. Proprietary ©2019 Alteryx, Inc. GOALS OF IA WITH ANALYTICS • Better testing of controls through 100% population testing • Be more efficient in auditing controls • Develop and deploy Continuous auditing • Increase visibility to internal and external risk • Meet expectations of internal and external stakeholders • Lead a world class audit department • Stay ahead of the trends
  • 3. Proprietary ©2019 Alteryx, Inc. WHY USE ANALYTIC TOOLS? • Provide support for audits • Provide data samples for audits • Use data / metrics to perform a Risk Assessment • Assist in determine data to look at prior to the audit. Risk rating of controls • Develop Continuous Monitoring applications to drive adoptions within the business.
  • 4. Proprietary ©2019 Alteryx, Inc. • Data Access • Understanding where to find the data and what to get • Data is not available in electronic format • Data corruption • Reluctance to Change • Executive Buy-in for investment CURRENT CHALLENGES
  • 5. Proprietary ©2019 Alteryx, Inc. OVERCOMING CHALLENGES • Data Access – assure IT read only access is required • Understanding where to find the data and what to get – work with the business to understand processes and where the data can be found • Data is not available in electronic format – leverage OCR technology to convert data into electronic format • Data corruption – normally a result of using tools to pull and convert data. Request direct access to data. • Reluctance to Change – show the value of analytics and how it improves the job function • Executive Buy-in for investment – perform a pilot with analytics to show quick wins.
  • 6. Proprietary TRENDS ©2019 Alteryx, Inc. • Cyber Security Analytics (IT Audit) • Compliance (ie, FCPA, SOX) • Predictive Analytics • Cloud based data sources (API’s) • GRC / GRC • Assist and/or compliment with RPA • Key Risk Indicators (KRI’s) A LT E RY X U S E D F O R :
  • 8. Proprietary OBJECTIVE Leverage data, analytics and technology to provide the highest level of business assurance during the audits. ©2019 Alteryx, Inc.
  • 9. Proprietary ©2019 Alteryx, Inc. MINDSET Start with capabilities then deploy to audit projects Experimental Data Science Lab approach- don’t mix undeveloped capabilities with active audits Commitment Resources & funds dedicated to Analytics, Automation, RPA and AI Authority to decide our own projects Autonomy Leverage Corporate Resources Resourceful Capability based 32 4 65  OCR & encryption  Unstructured data  Robotics  Dashboarding  Self-Service  Risk & predictive modeling  Natural Language Processing  Geospatial analytics  In-database analytics  Unsupervised models Intentional1 Daily scrums with 2-week sprints arranged to deliver to the customer
  • 10. Proprietary ©2019 Alteryx, Inc. Audit Analytics Model DATA RPA AI+ + + DO ANALYTICS = ASSURANCE THINK ANALYZEGET VALUE
  • 11. Proprietary ©2019 Alteryx, Inc. ONE AUDITOR, ONE AUDIT, ONE WEEK
  • 12. Proprietary ©2019 Alteryx, Inc. T&E BUSINESS EXAMPLE Risky T&E Transaction ANALYTICS RPA AI / Machine Learning Transactions Source System Audit DW Data Enrichment - MCCs - Org Details - Demographics Data Validation Testing rules to validate the data Merchant Info Webster obtained additional details from a website about the merchant Descriptive Analytics
  • 13. Proprietary ©2019 Alteryx, Inc. T&E BUSINESS EXAMPLE ANALYTICS RPA AI / Machine Learning Prescriptive Analytics Risk Scoring Prediction 20+ Audit Tests Early Warning UnsupervisedReconciliation Ron validates success of the automated feed and documents completeness and accuracy Prediction model uses historical audit findings to assess the likelihood of the transaction of being an exception Risk model uses quantitative and qualitative calculations to assess transaction risk ELI Identifies a risky transaction and sends an email with the analysis Unsupervised models create clusters of entertainment and miscellaneous expenses
  • 18. Proprietary PREDICTION SCORING Case ManagementAudit Exceptions Predictive Variables Results (Risk Score) Logistic Regression Historical Exceptions Accuracy Check Model Penny (Bot gathering info)
  • 21. Proprietary IN THE NEW WORLD, IT IS NOT THE BIG FISH WHICH EATS THE SMALL FISH, IT'S THE FAST FISH WHICH EATS THE SLOW FISH KLAUS SCHWAB ©2019 Alteryx, Inc. FINAL THOUGHT…

Editor's Notes

  1. Break slide option 1