SlideShare a Scribd company logo
INTRODUCTION TO CASEWARE IDEA
DESIGNED BY AUDITORS FOR AUDITORS
AGENDA
• Introduction to CaseWare IDEA Inc.
ABOUT CASEWARE IDEA INC.
• Founded in 1988
• Industry leader in solutions for finance, accounting,
governance, risk and audit professionals
• Over 400,000 users of our technologies across 150
countries and 16 languages
• Customers include Fortune 500 companies, Global
500 companies, 9 governments of the 15 largest
economies
WHY DATA ANALYTICS?
1. Volume of transactions has increased
2. Absence of physical evidence (all electronic)
3. Regulatory focus on fraud and controls
4. Audit standards recommend using CAATs
5. Need to test 100% of transactions
WHY DATA ANALYTICS?
6. Pressure on costs and efficiency
7. Manage risks more effectively
8. Pressure from the auditees to use more analytics
9. Value added (methodology)
CHALLENGES
• Data acquisition
• Retrieving data from different software and ERP systems
• Lack of standards
• Skills
• Acceptance and mindset
• Fundamental change in audit techniques
• Changes in auditing standards
• Which manual tests can be replaced
AGENDA
• Introduction to CaseWare IDEA Inc.
• Introduction IDEA Data Analysis software
DATA ANALYSIS PROCESS
RETRIEVAL IMPORT
CLEAN
PREPARE
VALIDATE ANALYSIS REPORTING
DATA ACQUISITION
IDEA allows you to
import and export
data in a multitude of
formats, including
files originating from
large mainframe
computers and
accounting software
IDEA
GETTING/UNDERSTANDING DATA
• Import from CSV, Excel, PDF, Reports
• Import directly from accounting software
• Connectors to ERP
• Different format = TAGGING
• Participating in data standards
AIS
SAF-T
Audit Data
Standard
Audit Data
Collection
DATA ANALYSIS
Pivot Tables
Reports
Charts
Exports
History
Project Overview
Automate
Import from
virtually any
source – from
PDF to ERP
Extract • Sort • Search • Group
Calculated Fields • Stratify •
Summarize Age • Gaps
Duplicates • Sample Statistics •
Join • Append • Compare
1. Import Data 2. Perform Analysis 3. Review Results
AGENDA
• Introduction to CaseWare IDEA Inc.
• Introduction IDEA Data Analysis software
• Case studies
CASE 1 - PAYMENTS
• Import
• Reconciliation / Field Stats
• Discover and Visualize the data
• Check on missing cheque numbers
• Check on duplicate cheque numbers
• Check on fuzzy duplicate suppliers
• Join with Authorization table
• Perform a stratified random Sample
CASE 2 – JOURNAL ENTRIES
• Import
• Exceptions (unbalanced entries)
• Summary by Accounts (sent to Working Papers)
CASE 3 - INVOICES
• Import
• Calculation accuracy
• Benford’s Law (Mark J. Nigrini PhD)
AGENDA
• Introduction to CaseWare IDEA Inc.
• Introduction IDEA Data Analysis software
• Case studies
• Benefits of CaseWare IDEA Data Analysis software
 Complicated equations
 No data integrity
 User friendly interface
 Data integrity
 Enter a few values and receive a
result
Use the Age Band column as the column field in the Pivot Table.
The oldest (i.e., first) date should be older than the oldest record.
For simplicity, use “1” (1/1/1900) as the date. This will represent the
“X days +” band.
EXCEL VS. IDEA: AGING
 Not intuitive
 Can easily override values
 No drill down feature
 No custom graph
 User friendly
 Read-only access
 Drill down feature
 Custom graph
Frequencies predicted by Benford’s
Law for First Digit, Second Digit,
and First Three Digit tests.
EXCEL VS. IDEA: BENFORD’S LAW
EXCEL VS IDEA – DATA PROTECTION
With protected data, you can do the following:
 Duplicate Detection
 Apply Benford’s Law
 Summarization
 Stratification
 Gap Detection
 Quick Extraction
 Several Sampling Methods
 Key Extraction
 Advanced Statistical Methods
 Multitask
 Various Imports
 Structure Reports
WHY USE CASEWARE IDEA?
1. IDEA protects the source data by allowing read
only access to the client's data to avoid any
unwanted changes, and maintain data integrity.
2. IDEA creates a record of all changes made to a file
(database) and maintains an audit trail or log of
all operations carried out on a database,
including the import and each audit test.
20
WHY USE CASEWARE IDEA?
3. IDEA can do the following:
• Compare, join, append, connect different files from
different sources
• Extract specific transactions, identifies gaps (e.g. check
number) or duplicates
• Profile data by summarizing, stratifying or aging the files
• Create useful File Statistics automatically
• Create samples using several different sampling
methods
21
WHY USE CASEWARE IDEA?
4. IDEA allows you to import and export data into a
multitude of formats, including files originating
from large mainframe computers and accounting
software.
5. Allows you to easily manage your files and results
and shows the source of your results
6. IDEA can read and process millions of records in
seconds. There is no limit to the number of
records that IDEA can process.
22
Change can be difficult for anyone.
Inventor Charles Kettering once said, “The
world hates change, yet it is the only thing that
has brought progress.” (IIA GTAG16)
SUMMARY: BENEFITS OF USING IDEA
1. Work more efficiently
... lower your costs
2. Work more effectively
… add more quality
3. Improve your capabilities
… add more value
INTERESTED IN A DEMO OF IDEA?
Contact us at salesidea@caseware.com to
schedule a demonstration
INTRODUCTION TO CASEWARE IDEA
DESIGNED BY AUDITORS FOR AUDITORS
Visit casewareanalytics.com
Email salesidea@caseware.com
Ad

More Related Content

What's hot (20)

Computer aided audit techniques (CAAT) sourav mathur
Computer aided audit techniques (CAAT)  sourav mathurComputer aided audit techniques (CAAT)  sourav mathur
Computer aided audit techniques (CAAT) sourav mathur
sourav mathur
 
Data Analytics and the Small Audit Department: How to Implement for Big Gains
Data Analytics and the Small Audit Department: How to Implement for Big GainsData Analytics and the Small Audit Department: How to Implement for Big Gains
Data Analytics and the Small Audit Department: How to Implement for Big Gains
CaseWare IDEA
 
Power Bi Basics
Power Bi BasicsPower Bi Basics
Power Bi Basics
Abhishek Gautam
 
CAAT - Data Analysis and Audit Techniques
CAAT - Data Analysis and Audit TechniquesCAAT - Data Analysis and Audit Techniques
CAAT - Data Analysis and Audit Techniques
Saurabh Rai
 
FORENSIC ACCOUNTING
FORENSIC ACCOUNTINGFORENSIC ACCOUNTING
FORENSIC ACCOUNTING
KARTHIKDHILIP
 
Audit presentation
Audit presentationAudit presentation
Audit presentation
Metafrique group
 
My tableau
My tableauMy tableau
My tableau
Girish Srivastava
 
Presentation on history of accounting
Presentation on history of accountingPresentation on history of accounting
Presentation on history of accounting
Saba Khan
 
Introduction to caat
Introduction to caatIntroduction to caat
Introduction to caat
Arti Parab Academics
 
Computer Assisted Audit Tools and Techniques - the Force multiplier in the ba...
Computer Assisted Audit Tools and Techniques - the Force multiplier in the ba...Computer Assisted Audit Tools and Techniques - the Force multiplier in the ba...
Computer Assisted Audit Tools and Techniques - the Force multiplier in the ba...
Ee Chuan Yoong
 
Business analytics workshop presentation final
Business analytics workshop presentation   finalBusiness analytics workshop presentation   final
Business analytics workshop presentation final
Brian Beveridge
 
Power BI Overview
Power BI OverviewPower BI Overview
Power BI Overview
Nikkia Carter
 
Ledger
LedgerLedger
Ledger
SANGEETHASHAINU
 
DATA ANALYTICS FOR SOLVING BUSINESS PROBLEMS
DATA ANALYTICS FOR SOLVING BUSINESS PROBLEMSDATA ANALYTICS FOR SOLVING BUSINESS PROBLEMS
DATA ANALYTICS FOR SOLVING BUSINESS PROBLEMS
Alexander Kolker
 
Power bi
Power biPower bi
Power bi
Lakshmi Prasanna Kottagorla
 
Evolving role of internal auditing function
Evolving role of internal auditing functionEvolving role of internal auditing function
Evolving role of internal auditing function
Debashis Gupta
 
Introduction to Power BI and Data Visualization
Introduction to Power BI and Data VisualizationIntroduction to Power BI and Data Visualization
Introduction to Power BI and Data Visualization
Swapnil Jadhav
 
Audit of Joint Stock Companies -Purpose-
Audit of Joint Stock Companies -Purpose-Audit of Joint Stock Companies -Purpose-
Audit of Joint Stock Companies -Purpose-
bkaviya3
 
Accounting Cycle
Accounting CycleAccounting Cycle
Accounting Cycle
Suman Mia
 
Introduction To Analytics
Introduction To AnalyticsIntroduction To Analytics
Introduction To Analytics
Alex Meadows
 
Computer aided audit techniques (CAAT) sourav mathur
Computer aided audit techniques (CAAT)  sourav mathurComputer aided audit techniques (CAAT)  sourav mathur
Computer aided audit techniques (CAAT) sourav mathur
sourav mathur
 
Data Analytics and the Small Audit Department: How to Implement for Big Gains
Data Analytics and the Small Audit Department: How to Implement for Big GainsData Analytics and the Small Audit Department: How to Implement for Big Gains
Data Analytics and the Small Audit Department: How to Implement for Big Gains
CaseWare IDEA
 
CAAT - Data Analysis and Audit Techniques
CAAT - Data Analysis and Audit TechniquesCAAT - Data Analysis and Audit Techniques
CAAT - Data Analysis and Audit Techniques
Saurabh Rai
 
Presentation on history of accounting
Presentation on history of accountingPresentation on history of accounting
Presentation on history of accounting
Saba Khan
 
Computer Assisted Audit Tools and Techniques - the Force multiplier in the ba...
Computer Assisted Audit Tools and Techniques - the Force multiplier in the ba...Computer Assisted Audit Tools and Techniques - the Force multiplier in the ba...
Computer Assisted Audit Tools and Techniques - the Force multiplier in the ba...
Ee Chuan Yoong
 
Business analytics workshop presentation final
Business analytics workshop presentation   finalBusiness analytics workshop presentation   final
Business analytics workshop presentation final
Brian Beveridge
 
DATA ANALYTICS FOR SOLVING BUSINESS PROBLEMS
DATA ANALYTICS FOR SOLVING BUSINESS PROBLEMSDATA ANALYTICS FOR SOLVING BUSINESS PROBLEMS
DATA ANALYTICS FOR SOLVING BUSINESS PROBLEMS
Alexander Kolker
 
Evolving role of internal auditing function
Evolving role of internal auditing functionEvolving role of internal auditing function
Evolving role of internal auditing function
Debashis Gupta
 
Introduction to Power BI and Data Visualization
Introduction to Power BI and Data VisualizationIntroduction to Power BI and Data Visualization
Introduction to Power BI and Data Visualization
Swapnil Jadhav
 
Audit of Joint Stock Companies -Purpose-
Audit of Joint Stock Companies -Purpose-Audit of Joint Stock Companies -Purpose-
Audit of Joint Stock Companies -Purpose-
bkaviya3
 
Accounting Cycle
Accounting CycleAccounting Cycle
Accounting Cycle
Suman Mia
 
Introduction To Analytics
Introduction To AnalyticsIntroduction To Analytics
Introduction To Analytics
Alex Meadows
 

Viewers also liked (20)

IDEA to Detect Duplicate Invoice Payments
IDEA to Detect Duplicate Invoice PaymentsIDEA to Detect Duplicate Invoice Payments
IDEA to Detect Duplicate Invoice Payments
AuditWare Systems Ltd.
 
Caseware refresher slides
Caseware refresher slidesCaseware refresher slides
Caseware refresher slides
Matthew Green
 
Basic IDEA Training
Basic IDEA TrainingBasic IDEA Training
Basic IDEA Training
Cristian Mihai
 
Bolivia integrated Emergency Management System Feasibility Study
Bolivia integrated Emergency Management System Feasibility StudyBolivia integrated Emergency Management System Feasibility Study
Bolivia integrated Emergency Management System Feasibility Study
YoungTae (Henry) Huh
 
Announcements- Tuesday March 28, 2017
Announcements- Tuesday March 28, 2017Announcements- Tuesday March 28, 2017
Announcements- Tuesday March 28, 2017
Ken Stayner
 
Adiós a la seguridad... ¡Es hora de vender inseguridad!
Adiós a la seguridad... ¡Es hora de vender inseguridad!Adiós a la seguridad... ¡Es hora de vender inseguridad!
Adiós a la seguridad... ¡Es hora de vender inseguridad!
Juanma Gaviria
 
Customer Experience Analytics - Action at the pace of the digitial consumer
Customer Experience Analytics - Action at the pace of the digitial consumerCustomer Experience Analytics - Action at the pace of the digitial consumer
Customer Experience Analytics - Action at the pace of the digitial consumer
Joan Pau Vizcaino Estanyol ☁
 
5x3 keys to be a successful ecommerce
5x3 keys to be  a successful ecommerce5x3 keys to be  a successful ecommerce
5x3 keys to be a successful ecommerce
Nacho Rosés
 
What is your value as a software developer?
What is your value as a software developer?What is your value as a software developer?
What is your value as a software developer?
Anujah Bosman
 
People don't want to buy another insurance product, they want what they need
People don't want to buy another insurance product, they want what they needPeople don't want to buy another insurance product, they want what they need
People don't want to buy another insurance product, they want what they need
Christophe jauquet
 
Facts You Didn’t Know About Gamification Industry
Facts You Didn’t Know About Gamification IndustryFacts You Didn’t Know About Gamification Industry
Facts You Didn’t Know About Gamification Industry
ZillionDesigns
 
Gender and oppression: A Detailed Disussion
Gender and oppression: A Detailed DisussionGender and oppression: A Detailed Disussion
Gender and oppression: A Detailed Disussion
Hathib KK
 
Black Fish Documentary Analysis
Black Fish Documentary AnalysisBlack Fish Documentary Analysis
Black Fish Documentary Analysis
HJones137
 
Berpikir Lateral (Lateral Thinking)
Berpikir Lateral (Lateral Thinking)Berpikir Lateral (Lateral Thinking)
Berpikir Lateral (Lateral Thinking)
Tri Widodo W. UTOMO
 
Operating Systems: Linux in Detail
Operating Systems: Linux in DetailOperating Systems: Linux in Detail
Operating Systems: Linux in Detail
Damian T. Gordon
 
Benefits of Travel Mobile Application
Benefits of Travel Mobile ApplicationBenefits of Travel Mobile Application
Benefits of Travel Mobile Application
Mobilmindz
 
トピックモデルの評価指標 Perplexity とは何なのか?
トピックモデルの評価指標 Perplexity とは何なのか?トピックモデルの評価指標 Perplexity とは何なのか?
トピックモデルの評価指標 Perplexity とは何なのか?
hoxo_m
 
とりあえずいい感じになるPower Pointテンプレート「Azusa Colors 改」を作った
とりあえずいい感じになるPower Pointテンプレート「Azusa Colors 改」を作ったとりあえずいい感じになるPower Pointテンプレート「Azusa Colors 改」を作った
とりあえずいい感じになるPower Pointテンプレート「Azusa Colors 改」を作った
幹弘 松山
 
Understanding Personalization Metrics - How to Measure Success
Understanding Personalization Metrics - How to Measure SuccessUnderstanding Personalization Metrics - How to Measure Success
Understanding Personalization Metrics - How to Measure Success
Certona
 
Flyer cahier op de campus 3 april 2017 meten is weten3
Flyer cahier op de campus  3 april 2017 meten is weten3Flyer cahier op de campus  3 april 2017 meten is weten3
Flyer cahier op de campus 3 april 2017 meten is weten3
Jasper van der Kemp
 
IDEA to Detect Duplicate Invoice Payments
IDEA to Detect Duplicate Invoice PaymentsIDEA to Detect Duplicate Invoice Payments
IDEA to Detect Duplicate Invoice Payments
AuditWare Systems Ltd.
 
Caseware refresher slides
Caseware refresher slidesCaseware refresher slides
Caseware refresher slides
Matthew Green
 
Bolivia integrated Emergency Management System Feasibility Study
Bolivia integrated Emergency Management System Feasibility StudyBolivia integrated Emergency Management System Feasibility Study
Bolivia integrated Emergency Management System Feasibility Study
YoungTae (Henry) Huh
 
Announcements- Tuesday March 28, 2017
Announcements- Tuesday March 28, 2017Announcements- Tuesday March 28, 2017
Announcements- Tuesday March 28, 2017
Ken Stayner
 
Adiós a la seguridad... ¡Es hora de vender inseguridad!
Adiós a la seguridad... ¡Es hora de vender inseguridad!Adiós a la seguridad... ¡Es hora de vender inseguridad!
Adiós a la seguridad... ¡Es hora de vender inseguridad!
Juanma Gaviria
 
Customer Experience Analytics - Action at the pace of the digitial consumer
Customer Experience Analytics - Action at the pace of the digitial consumerCustomer Experience Analytics - Action at the pace of the digitial consumer
Customer Experience Analytics - Action at the pace of the digitial consumer
Joan Pau Vizcaino Estanyol ☁
 
5x3 keys to be a successful ecommerce
5x3 keys to be  a successful ecommerce5x3 keys to be  a successful ecommerce
5x3 keys to be a successful ecommerce
Nacho Rosés
 
What is your value as a software developer?
What is your value as a software developer?What is your value as a software developer?
What is your value as a software developer?
Anujah Bosman
 
People don't want to buy another insurance product, they want what they need
People don't want to buy another insurance product, they want what they needPeople don't want to buy another insurance product, they want what they need
People don't want to buy another insurance product, they want what they need
Christophe jauquet
 
Facts You Didn’t Know About Gamification Industry
Facts You Didn’t Know About Gamification IndustryFacts You Didn’t Know About Gamification Industry
Facts You Didn’t Know About Gamification Industry
ZillionDesigns
 
Gender and oppression: A Detailed Disussion
Gender and oppression: A Detailed DisussionGender and oppression: A Detailed Disussion
Gender and oppression: A Detailed Disussion
Hathib KK
 
Black Fish Documentary Analysis
Black Fish Documentary AnalysisBlack Fish Documentary Analysis
Black Fish Documentary Analysis
HJones137
 
Berpikir Lateral (Lateral Thinking)
Berpikir Lateral (Lateral Thinking)Berpikir Lateral (Lateral Thinking)
Berpikir Lateral (Lateral Thinking)
Tri Widodo W. UTOMO
 
Operating Systems: Linux in Detail
Operating Systems: Linux in DetailOperating Systems: Linux in Detail
Operating Systems: Linux in Detail
Damian T. Gordon
 
Benefits of Travel Mobile Application
Benefits of Travel Mobile ApplicationBenefits of Travel Mobile Application
Benefits of Travel Mobile Application
Mobilmindz
 
トピックモデルの評価指標 Perplexity とは何なのか?
トピックモデルの評価指標 Perplexity とは何なのか?トピックモデルの評価指標 Perplexity とは何なのか?
トピックモデルの評価指標 Perplexity とは何なのか?
hoxo_m
 
とりあえずいい感じになるPower Pointテンプレート「Azusa Colors 改」を作った
とりあえずいい感じになるPower Pointテンプレート「Azusa Colors 改」を作ったとりあえずいい感じになるPower Pointテンプレート「Azusa Colors 改」を作った
とりあえずいい感じになるPower Pointテンプレート「Azusa Colors 改」を作った
幹弘 松山
 
Understanding Personalization Metrics - How to Measure Success
Understanding Personalization Metrics - How to Measure SuccessUnderstanding Personalization Metrics - How to Measure Success
Understanding Personalization Metrics - How to Measure Success
Certona
 
Flyer cahier op de campus 3 april 2017 meten is weten3
Flyer cahier op de campus  3 april 2017 meten is weten3Flyer cahier op de campus  3 april 2017 meten is weten3
Flyer cahier op de campus 3 april 2017 meten is weten3
Jasper van der Kemp
 
Ad

Similar to Introduction to CaseWare IDEA - Designed by Auditors for Auditors (20)

Why You Need to STOP Using Spreadsheets for Audit Analysis
Why You Need to STOP Using Spreadsheets for Audit AnalysisWhy You Need to STOP Using Spreadsheets for Audit Analysis
Why You Need to STOP Using Spreadsheets for Audit Analysis
CaseWare IDEA
 
Presentation on IDEA auditing software CA
Presentation on IDEA auditing software CAPresentation on IDEA auditing software CA
Presentation on IDEA auditing software CA
jiyagoyal10413
 
Data analytics and audit coverage guide
Data analytics and audit coverage guideData analytics and audit coverage guide
Data analytics and audit coverage guide
AstalapulosListestos
 
Data analytics and audit coverage guide
Data analytics and audit coverage guideData analytics and audit coverage guide
Data analytics and audit coverage guide
CenapSerdarolu
 
Unlocking New Insights with Information Discovery
Unlocking New Insights with Information DiscoveryUnlocking New Insights with Information Discovery
Unlocking New Insights with Information Discovery
Alithya
 
Why Your Data Science Architecture Should Include a Data Virtualization Tool ...
Why Your Data Science Architecture Should Include a Data Virtualization Tool ...Why Your Data Science Architecture Should Include a Data Virtualization Tool ...
Why Your Data Science Architecture Should Include a Data Virtualization Tool ...
Denodo
 
Data Warehouse Testing in the Pharmaceutical Industry
Data Warehouse Testing in the Pharmaceutical IndustryData Warehouse Testing in the Pharmaceutical Industry
Data Warehouse Testing in the Pharmaceutical Industry
RTTS
 
Exploration of business intelligence using Oralce B.I (OBIEE)
Exploration of business intelligence using Oralce B.I (OBIEE)Exploration of business intelligence using Oralce B.I (OBIEE)
Exploration of business intelligence using Oralce B.I (OBIEE)
Aneel Ahmed
 
Essential Prerequisites for Maximizing Success from Big Data
Essential Prerequisites for Maximizing Success from Big DataEssential Prerequisites for Maximizing Success from Big Data
Essential Prerequisites for Maximizing Success from Big Data
Society of Petroleum Engineers
 
Data kitchen 7 agile steps - big data fest 9-18-2015
Data kitchen   7 agile steps - big data fest 9-18-2015Data kitchen   7 agile steps - big data fest 9-18-2015
Data kitchen 7 agile steps - big data fest 9-18-2015
DataKitchen
 
Audit Webinar: Surefire ways to succeed with Data Analytics
Audit Webinar: Surefire ways to succeed with Data AnalyticsAudit Webinar: Surefire ways to succeed with Data Analytics
Audit Webinar: Surefire ways to succeed with Data Analytics
CaseWare IDEA
 
How to Automate your Enterprise Application / ERP Testing
How to Automate your  Enterprise Application / ERP TestingHow to Automate your  Enterprise Application / ERP Testing
How to Automate your Enterprise Application / ERP Testing
RTTS
 
CAATS.pptx tgrewughfehiwjjjfisufisjdihfh
CAATS.pptx tgrewughfehiwjjjfisufisjdihfhCAATS.pptx tgrewughfehiwjjjfisufisjdihfh
CAATS.pptx tgrewughfehiwjjjfisufisjdihfh
baghelaayushi08
 
Quicker Insights and Sustainable Business Agility Powered By Data Virtualizat...
Quicker Insights and Sustainable Business Agility Powered By Data Virtualizat...Quicker Insights and Sustainable Business Agility Powered By Data Virtualizat...
Quicker Insights and Sustainable Business Agility Powered By Data Virtualizat...
Denodo
 
IDEA 10.3 Launch Webinar
IDEA 10.3 Launch WebinarIDEA 10.3 Launch Webinar
IDEA 10.3 Launch Webinar
CaseWare IDEA
 
DWBI Testing and Analytics Testing Services
DWBI Testing and Analytics Testing ServicesDWBI Testing and Analytics Testing Services
DWBI Testing and Analytics Testing Services
CODETRU Software Solutions
 
Bdf16 big-data-warehouse-case-study-data kitchen
Bdf16 big-data-warehouse-case-study-data kitchenBdf16 big-data-warehouse-case-study-data kitchen
Bdf16 big-data-warehouse-case-study-data kitchen
Christopher Bergh
 
2022 Trends in Enterprise Analytics
2022 Trends in Enterprise Analytics2022 Trends in Enterprise Analytics
2022 Trends in Enterprise Analytics
DATAVERSITY
 
Smart analyzer v9 product profile
Smart analyzer v9 product profileSmart analyzer v9 product profile
Smart analyzer v9 product profile
AuditWare Systems Ltd.
 
Delivering digital transformation and business impact with io t, machine lear...
Delivering digital transformation and business impact with io t, machine lear...Delivering digital transformation and business impact with io t, machine lear...
Delivering digital transformation and business impact with io t, machine lear...
Robert Sanders
 
Why You Need to STOP Using Spreadsheets for Audit Analysis
Why You Need to STOP Using Spreadsheets for Audit AnalysisWhy You Need to STOP Using Spreadsheets for Audit Analysis
Why You Need to STOP Using Spreadsheets for Audit Analysis
CaseWare IDEA
 
Presentation on IDEA auditing software CA
Presentation on IDEA auditing software CAPresentation on IDEA auditing software CA
Presentation on IDEA auditing software CA
jiyagoyal10413
 
Data analytics and audit coverage guide
Data analytics and audit coverage guideData analytics and audit coverage guide
Data analytics and audit coverage guide
AstalapulosListestos
 
Data analytics and audit coverage guide
Data analytics and audit coverage guideData analytics and audit coverage guide
Data analytics and audit coverage guide
CenapSerdarolu
 
Unlocking New Insights with Information Discovery
Unlocking New Insights with Information DiscoveryUnlocking New Insights with Information Discovery
Unlocking New Insights with Information Discovery
Alithya
 
Why Your Data Science Architecture Should Include a Data Virtualization Tool ...
Why Your Data Science Architecture Should Include a Data Virtualization Tool ...Why Your Data Science Architecture Should Include a Data Virtualization Tool ...
Why Your Data Science Architecture Should Include a Data Virtualization Tool ...
Denodo
 
Data Warehouse Testing in the Pharmaceutical Industry
Data Warehouse Testing in the Pharmaceutical IndustryData Warehouse Testing in the Pharmaceutical Industry
Data Warehouse Testing in the Pharmaceutical Industry
RTTS
 
Exploration of business intelligence using Oralce B.I (OBIEE)
Exploration of business intelligence using Oralce B.I (OBIEE)Exploration of business intelligence using Oralce B.I (OBIEE)
Exploration of business intelligence using Oralce B.I (OBIEE)
Aneel Ahmed
 
Essential Prerequisites for Maximizing Success from Big Data
Essential Prerequisites for Maximizing Success from Big DataEssential Prerequisites for Maximizing Success from Big Data
Essential Prerequisites for Maximizing Success from Big Data
Society of Petroleum Engineers
 
Data kitchen 7 agile steps - big data fest 9-18-2015
Data kitchen   7 agile steps - big data fest 9-18-2015Data kitchen   7 agile steps - big data fest 9-18-2015
Data kitchen 7 agile steps - big data fest 9-18-2015
DataKitchen
 
Audit Webinar: Surefire ways to succeed with Data Analytics
Audit Webinar: Surefire ways to succeed with Data AnalyticsAudit Webinar: Surefire ways to succeed with Data Analytics
Audit Webinar: Surefire ways to succeed with Data Analytics
CaseWare IDEA
 
How to Automate your Enterprise Application / ERP Testing
How to Automate your  Enterprise Application / ERP TestingHow to Automate your  Enterprise Application / ERP Testing
How to Automate your Enterprise Application / ERP Testing
RTTS
 
CAATS.pptx tgrewughfehiwjjjfisufisjdihfh
CAATS.pptx tgrewughfehiwjjjfisufisjdihfhCAATS.pptx tgrewughfehiwjjjfisufisjdihfh
CAATS.pptx tgrewughfehiwjjjfisufisjdihfh
baghelaayushi08
 
Quicker Insights and Sustainable Business Agility Powered By Data Virtualizat...
Quicker Insights and Sustainable Business Agility Powered By Data Virtualizat...Quicker Insights and Sustainable Business Agility Powered By Data Virtualizat...
Quicker Insights and Sustainable Business Agility Powered By Data Virtualizat...
Denodo
 
IDEA 10.3 Launch Webinar
IDEA 10.3 Launch WebinarIDEA 10.3 Launch Webinar
IDEA 10.3 Launch Webinar
CaseWare IDEA
 
Bdf16 big-data-warehouse-case-study-data kitchen
Bdf16 big-data-warehouse-case-study-data kitchenBdf16 big-data-warehouse-case-study-data kitchen
Bdf16 big-data-warehouse-case-study-data kitchen
Christopher Bergh
 
2022 Trends in Enterprise Analytics
2022 Trends in Enterprise Analytics2022 Trends in Enterprise Analytics
2022 Trends in Enterprise Analytics
DATAVERSITY
 
Delivering digital transformation and business impact with io t, machine lear...
Delivering digital transformation and business impact with io t, machine lear...Delivering digital transformation and business impact with io t, machine lear...
Delivering digital transformation and business impact with io t, machine lear...
Robert Sanders
 
Ad

More from CaseWare IDEA (20)

Auditor Sous Les Projecteurs: Marcelo Barreto Rodrigues
Auditor Sous Les Projecteurs: Marcelo Barreto Rodrigues Auditor Sous Les Projecteurs: Marcelo Barreto Rodrigues
Auditor Sous Les Projecteurs: Marcelo Barreto Rodrigues
CaseWare IDEA
 
Auditor Destacado: Marcelo Barreto Rodrigues
Auditor Destacado: Marcelo Barreto Rodrigues Auditor Destacado: Marcelo Barreto Rodrigues
Auditor Destacado: Marcelo Barreto Rodrigues
CaseWare IDEA
 
Auditrice Sous Les Projecteurs: Bistra Dimitrova
Auditrice Sous Les Projecteurs: Bistra Dimitrova Auditrice Sous Les Projecteurs: Bistra Dimitrova
Auditrice Sous Les Projecteurs: Bistra Dimitrova
CaseWare IDEA
 
How to build a data analytics strategy in a digital world
How to build a data analytics strategy in a digital worldHow to build a data analytics strategy in a digital world
How to build a data analytics strategy in a digital world
CaseWare IDEA
 
Auditor Descado - Robert Berry
Auditor Descado - Robert BerryAuditor Descado - Robert Berry
Auditor Descado - Robert Berry
CaseWare IDEA
 
Auditeur sous les Projecteurs - Robert Berry
Auditeur sous les Projecteurs - Robert BerryAuditeur sous les Projecteurs - Robert Berry
Auditeur sous les Projecteurs - Robert Berry
CaseWare IDEA
 
Auditor Spotlight: Robert Berry
Auditor Spotlight: Robert Berry Auditor Spotlight: Robert Berry
Auditor Spotlight: Robert Berry
CaseWare IDEA
 
The Data Behind Audit Analytics
The Data Behind Audit AnalyticsThe Data Behind Audit Analytics
The Data Behind Audit Analytics
CaseWare IDEA
 
Auditora Destacada - Anke Eckardt
Auditora Destacada - Anke EckardtAuditora Destacada - Anke Eckardt
Auditora Destacada - Anke Eckardt
CaseWare IDEA
 
Auditeur sous les Projecteurs - Anke Eckardt
Auditeur sous les Projecteurs - Anke EckardtAuditeur sous les Projecteurs - Anke Eckardt
Auditeur sous les Projecteurs - Anke Eckardt
CaseWare IDEA
 
Audit Webinar How to get the right data for your audit in 3 easy steps
Audit Webinar How to get the right data for your audit in 3 easy stepsAudit Webinar How to get the right data for your audit in 3 easy steps
Audit Webinar How to get the right data for your audit in 3 easy steps
CaseWare IDEA
 
How to find new ways to add value to your audits
How to find new ways to add value to your auditsHow to find new ways to add value to your audits
How to find new ways to add value to your audits
CaseWare IDEA
 
Auditor Spotlight - Erin Baker
Auditor Spotlight - Erin BakerAuditor Spotlight - Erin Baker
Auditor Spotlight - Erin Baker
CaseWare IDEA
 
Auditeur Sous Les Projecteurs: Fred Lyons
Auditeur Sous Les Projecteurs: Fred LyonsAuditeur Sous Les Projecteurs: Fred Lyons
Auditeur Sous Les Projecteurs: Fred Lyons
CaseWare IDEA
 
Auditeur Sous Les Projecteurs: Erin Baker
Auditeur Sous Les Projecteurs: Erin BakerAuditeur Sous Les Projecteurs: Erin Baker
Auditeur Sous Les Projecteurs: Erin Baker
CaseWare IDEA
 
Auditor Destacado - Fred Lyons
Auditor Destacado - Fred LyonsAuditor Destacado - Fred Lyons
Auditor Destacado - Fred Lyons
CaseWare IDEA
 
Auditor Spotlight - Fred Lyons
Auditor Spotlight - Fred LyonsAuditor Spotlight - Fred Lyons
Auditor Spotlight - Fred Lyons
CaseWare IDEA
 
The Three Lines of Defense Model & Continuous Controls Monitoring
The Three Lines of Defense Model & Continuous Controls MonitoringThe Three Lines of Defense Model & Continuous Controls Monitoring
The Three Lines of Defense Model & Continuous Controls Monitoring
CaseWare IDEA
 
Integrating Data Analytics into a Risk-Based Audit Plan
Integrating Data Analytics into a Risk-Based Audit PlanIntegrating Data Analytics into a Risk-Based Audit Plan
Integrating Data Analytics into a Risk-Based Audit Plan
CaseWare IDEA
 
Audit: Breaking Down Barriers to Increase the Use of Data Analytics
Audit: Breaking Down Barriers to Increase the Use of Data AnalyticsAudit: Breaking Down Barriers to Increase the Use of Data Analytics
Audit: Breaking Down Barriers to Increase the Use of Data Analytics
CaseWare IDEA
 
Auditor Sous Les Projecteurs: Marcelo Barreto Rodrigues
Auditor Sous Les Projecteurs: Marcelo Barreto Rodrigues Auditor Sous Les Projecteurs: Marcelo Barreto Rodrigues
Auditor Sous Les Projecteurs: Marcelo Barreto Rodrigues
CaseWare IDEA
 
Auditor Destacado: Marcelo Barreto Rodrigues
Auditor Destacado: Marcelo Barreto Rodrigues Auditor Destacado: Marcelo Barreto Rodrigues
Auditor Destacado: Marcelo Barreto Rodrigues
CaseWare IDEA
 
Auditrice Sous Les Projecteurs: Bistra Dimitrova
Auditrice Sous Les Projecteurs: Bistra Dimitrova Auditrice Sous Les Projecteurs: Bistra Dimitrova
Auditrice Sous Les Projecteurs: Bistra Dimitrova
CaseWare IDEA
 
How to build a data analytics strategy in a digital world
How to build a data analytics strategy in a digital worldHow to build a data analytics strategy in a digital world
How to build a data analytics strategy in a digital world
CaseWare IDEA
 
Auditor Descado - Robert Berry
Auditor Descado - Robert BerryAuditor Descado - Robert Berry
Auditor Descado - Robert Berry
CaseWare IDEA
 
Auditeur sous les Projecteurs - Robert Berry
Auditeur sous les Projecteurs - Robert BerryAuditeur sous les Projecteurs - Robert Berry
Auditeur sous les Projecteurs - Robert Berry
CaseWare IDEA
 
Auditor Spotlight: Robert Berry
Auditor Spotlight: Robert Berry Auditor Spotlight: Robert Berry
Auditor Spotlight: Robert Berry
CaseWare IDEA
 
The Data Behind Audit Analytics
The Data Behind Audit AnalyticsThe Data Behind Audit Analytics
The Data Behind Audit Analytics
CaseWare IDEA
 
Auditora Destacada - Anke Eckardt
Auditora Destacada - Anke EckardtAuditora Destacada - Anke Eckardt
Auditora Destacada - Anke Eckardt
CaseWare IDEA
 
Auditeur sous les Projecteurs - Anke Eckardt
Auditeur sous les Projecteurs - Anke EckardtAuditeur sous les Projecteurs - Anke Eckardt
Auditeur sous les Projecteurs - Anke Eckardt
CaseWare IDEA
 
Audit Webinar How to get the right data for your audit in 3 easy steps
Audit Webinar How to get the right data for your audit in 3 easy stepsAudit Webinar How to get the right data for your audit in 3 easy steps
Audit Webinar How to get the right data for your audit in 3 easy steps
CaseWare IDEA
 
How to find new ways to add value to your audits
How to find new ways to add value to your auditsHow to find new ways to add value to your audits
How to find new ways to add value to your audits
CaseWare IDEA
 
Auditor Spotlight - Erin Baker
Auditor Spotlight - Erin BakerAuditor Spotlight - Erin Baker
Auditor Spotlight - Erin Baker
CaseWare IDEA
 
Auditeur Sous Les Projecteurs: Fred Lyons
Auditeur Sous Les Projecteurs: Fred LyonsAuditeur Sous Les Projecteurs: Fred Lyons
Auditeur Sous Les Projecteurs: Fred Lyons
CaseWare IDEA
 
Auditeur Sous Les Projecteurs: Erin Baker
Auditeur Sous Les Projecteurs: Erin BakerAuditeur Sous Les Projecteurs: Erin Baker
Auditeur Sous Les Projecteurs: Erin Baker
CaseWare IDEA
 
Auditor Destacado - Fred Lyons
Auditor Destacado - Fred LyonsAuditor Destacado - Fred Lyons
Auditor Destacado - Fred Lyons
CaseWare IDEA
 
Auditor Spotlight - Fred Lyons
Auditor Spotlight - Fred LyonsAuditor Spotlight - Fred Lyons
Auditor Spotlight - Fred Lyons
CaseWare IDEA
 
The Three Lines of Defense Model & Continuous Controls Monitoring
The Three Lines of Defense Model & Continuous Controls MonitoringThe Three Lines of Defense Model & Continuous Controls Monitoring
The Three Lines of Defense Model & Continuous Controls Monitoring
CaseWare IDEA
 
Integrating Data Analytics into a Risk-Based Audit Plan
Integrating Data Analytics into a Risk-Based Audit PlanIntegrating Data Analytics into a Risk-Based Audit Plan
Integrating Data Analytics into a Risk-Based Audit Plan
CaseWare IDEA
 
Audit: Breaking Down Barriers to Increase the Use of Data Analytics
Audit: Breaking Down Barriers to Increase the Use of Data AnalyticsAudit: Breaking Down Barriers to Increase the Use of Data Analytics
Audit: Breaking Down Barriers to Increase the Use of Data Analytics
CaseWare IDEA
 

Recently uploaded (20)

Classification_in_Machinee_Learning.pptx
Classification_in_Machinee_Learning.pptxClassification_in_Machinee_Learning.pptx
Classification_in_Machinee_Learning.pptx
wencyjorda88
 
Thingyan is now a global treasure! See how people around the world are search...
Thingyan is now a global treasure! See how people around the world are search...Thingyan is now a global treasure! See how people around the world are search...
Thingyan is now a global treasure! See how people around the world are search...
Pixellion
 
Safety Innovation in Mt. Vernon A Westchester County Model for New Rochelle a...
Safety Innovation in Mt. Vernon A Westchester County Model for New Rochelle a...Safety Innovation in Mt. Vernon A Westchester County Model for New Rochelle a...
Safety Innovation in Mt. Vernon A Westchester County Model for New Rochelle a...
James Francis Paradigm Asset Management
 
AI Competitor Analysis: How to Monitor and Outperform Your Competitors
AI Competitor Analysis: How to Monitor and Outperform Your CompetitorsAI Competitor Analysis: How to Monitor and Outperform Your Competitors
AI Competitor Analysis: How to Monitor and Outperform Your Competitors
Contify
 
VKS-Python-FIe Handling text CSV Binary.pptx
VKS-Python-FIe Handling text CSV Binary.pptxVKS-Python-FIe Handling text CSV Binary.pptx
VKS-Python-FIe Handling text CSV Binary.pptx
Vinod Srivastava
 
Data Science Courses in India iim skills
Data Science Courses in India iim skillsData Science Courses in India iim skills
Data Science Courses in India iim skills
dharnathakur29
 
CTS EXCEPTIONSPrediction of Aluminium wire rod physical properties through AI...
CTS EXCEPTIONSPrediction of Aluminium wire rod physical properties through AI...CTS EXCEPTIONSPrediction of Aluminium wire rod physical properties through AI...
CTS EXCEPTIONSPrediction of Aluminium wire rod physical properties through AI...
ThanushsaranS
 
EDU533 DEMO.pptxccccvbnjjkoo jhgggggbbbb
EDU533 DEMO.pptxccccvbnjjkoo jhgggggbbbbEDU533 DEMO.pptxccccvbnjjkoo jhgggggbbbb
EDU533 DEMO.pptxccccvbnjjkoo jhgggggbbbb
JessaMaeEvangelista2
 
Defense Against LLM Scheming 2025_04_28.pptx
Defense Against LLM Scheming 2025_04_28.pptxDefense Against LLM Scheming 2025_04_28.pptx
Defense Against LLM Scheming 2025_04_28.pptx
Greg Makowski
 
Secure_File_Storage_Hybrid_Cryptography.pptx..
Secure_File_Storage_Hybrid_Cryptography.pptx..Secure_File_Storage_Hybrid_Cryptography.pptx..
Secure_File_Storage_Hybrid_Cryptography.pptx..
yuvarajreddy2002
 
DPR_Expert_Recruitment_notice_Revised.pdf
DPR_Expert_Recruitment_notice_Revised.pdfDPR_Expert_Recruitment_notice_Revised.pdf
DPR_Expert_Recruitment_notice_Revised.pdf
inmishra17121973
 
computer organization and assembly language.docx
computer organization and assembly language.docxcomputer organization and assembly language.docx
computer organization and assembly language.docx
alisoftwareengineer1
 
chapter3 Central Tendency statistics.ppt
chapter3 Central Tendency statistics.pptchapter3 Central Tendency statistics.ppt
chapter3 Central Tendency statistics.ppt
justinebandajbn
 
How iCode cybertech Helped Me Recover My Lost Funds
How iCode cybertech Helped Me Recover My Lost FundsHow iCode cybertech Helped Me Recover My Lost Funds
How iCode cybertech Helped Me Recover My Lost Funds
ireneschmid345
 
Molecular methods diagnostic and monitoring of infection - Repaired.pptx
Molecular methods diagnostic and monitoring of infection  -  Repaired.pptxMolecular methods diagnostic and monitoring of infection  -  Repaired.pptx
Molecular methods diagnostic and monitoring of infection - Repaired.pptx
7tzn7x5kky
 
Data Analytics Overview and its applications
Data Analytics Overview and its applicationsData Analytics Overview and its applications
Data Analytics Overview and its applications
JanmejayaMishra7
 
Medical Dataset including visualizations
Medical Dataset including visualizationsMedical Dataset including visualizations
Medical Dataset including visualizations
vishrut8750588758
 
GenAI for Quant Analytics: survey-analytics.ai
GenAI for Quant Analytics: survey-analytics.aiGenAI for Quant Analytics: survey-analytics.ai
GenAI for Quant Analytics: survey-analytics.ai
Inspirient
 
Adobe Analytics NOAM Central User Group April 2025 Agent AI: Uncovering the S...
Adobe Analytics NOAM Central User Group April 2025 Agent AI: Uncovering the S...Adobe Analytics NOAM Central User Group April 2025 Agent AI: Uncovering the S...
Adobe Analytics NOAM Central User Group April 2025 Agent AI: Uncovering the S...
gmuir1066
 
md-presentHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHation.pptx
md-presentHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHation.pptxmd-presentHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHation.pptx
md-presentHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHation.pptx
fatimalazaar2004
 
Classification_in_Machinee_Learning.pptx
Classification_in_Machinee_Learning.pptxClassification_in_Machinee_Learning.pptx
Classification_in_Machinee_Learning.pptx
wencyjorda88
 
Thingyan is now a global treasure! See how people around the world are search...
Thingyan is now a global treasure! See how people around the world are search...Thingyan is now a global treasure! See how people around the world are search...
Thingyan is now a global treasure! See how people around the world are search...
Pixellion
 
Safety Innovation in Mt. Vernon A Westchester County Model for New Rochelle a...
Safety Innovation in Mt. Vernon A Westchester County Model for New Rochelle a...Safety Innovation in Mt. Vernon A Westchester County Model for New Rochelle a...
Safety Innovation in Mt. Vernon A Westchester County Model for New Rochelle a...
James Francis Paradigm Asset Management
 
AI Competitor Analysis: How to Monitor and Outperform Your Competitors
AI Competitor Analysis: How to Monitor and Outperform Your CompetitorsAI Competitor Analysis: How to Monitor and Outperform Your Competitors
AI Competitor Analysis: How to Monitor and Outperform Your Competitors
Contify
 
VKS-Python-FIe Handling text CSV Binary.pptx
VKS-Python-FIe Handling text CSV Binary.pptxVKS-Python-FIe Handling text CSV Binary.pptx
VKS-Python-FIe Handling text CSV Binary.pptx
Vinod Srivastava
 
Data Science Courses in India iim skills
Data Science Courses in India iim skillsData Science Courses in India iim skills
Data Science Courses in India iim skills
dharnathakur29
 
CTS EXCEPTIONSPrediction of Aluminium wire rod physical properties through AI...
CTS EXCEPTIONSPrediction of Aluminium wire rod physical properties through AI...CTS EXCEPTIONSPrediction of Aluminium wire rod physical properties through AI...
CTS EXCEPTIONSPrediction of Aluminium wire rod physical properties through AI...
ThanushsaranS
 
EDU533 DEMO.pptxccccvbnjjkoo jhgggggbbbb
EDU533 DEMO.pptxccccvbnjjkoo jhgggggbbbbEDU533 DEMO.pptxccccvbnjjkoo jhgggggbbbb
EDU533 DEMO.pptxccccvbnjjkoo jhgggggbbbb
JessaMaeEvangelista2
 
Defense Against LLM Scheming 2025_04_28.pptx
Defense Against LLM Scheming 2025_04_28.pptxDefense Against LLM Scheming 2025_04_28.pptx
Defense Against LLM Scheming 2025_04_28.pptx
Greg Makowski
 
Secure_File_Storage_Hybrid_Cryptography.pptx..
Secure_File_Storage_Hybrid_Cryptography.pptx..Secure_File_Storage_Hybrid_Cryptography.pptx..
Secure_File_Storage_Hybrid_Cryptography.pptx..
yuvarajreddy2002
 
DPR_Expert_Recruitment_notice_Revised.pdf
DPR_Expert_Recruitment_notice_Revised.pdfDPR_Expert_Recruitment_notice_Revised.pdf
DPR_Expert_Recruitment_notice_Revised.pdf
inmishra17121973
 
computer organization and assembly language.docx
computer organization and assembly language.docxcomputer organization and assembly language.docx
computer organization and assembly language.docx
alisoftwareengineer1
 
chapter3 Central Tendency statistics.ppt
chapter3 Central Tendency statistics.pptchapter3 Central Tendency statistics.ppt
chapter3 Central Tendency statistics.ppt
justinebandajbn
 
How iCode cybertech Helped Me Recover My Lost Funds
How iCode cybertech Helped Me Recover My Lost FundsHow iCode cybertech Helped Me Recover My Lost Funds
How iCode cybertech Helped Me Recover My Lost Funds
ireneschmid345
 
Molecular methods diagnostic and monitoring of infection - Repaired.pptx
Molecular methods diagnostic and monitoring of infection  -  Repaired.pptxMolecular methods diagnostic and monitoring of infection  -  Repaired.pptx
Molecular methods diagnostic and monitoring of infection - Repaired.pptx
7tzn7x5kky
 
Data Analytics Overview and its applications
Data Analytics Overview and its applicationsData Analytics Overview and its applications
Data Analytics Overview and its applications
JanmejayaMishra7
 
Medical Dataset including visualizations
Medical Dataset including visualizationsMedical Dataset including visualizations
Medical Dataset including visualizations
vishrut8750588758
 
GenAI for Quant Analytics: survey-analytics.ai
GenAI for Quant Analytics: survey-analytics.aiGenAI for Quant Analytics: survey-analytics.ai
GenAI for Quant Analytics: survey-analytics.ai
Inspirient
 
Adobe Analytics NOAM Central User Group April 2025 Agent AI: Uncovering the S...
Adobe Analytics NOAM Central User Group April 2025 Agent AI: Uncovering the S...Adobe Analytics NOAM Central User Group April 2025 Agent AI: Uncovering the S...
Adobe Analytics NOAM Central User Group April 2025 Agent AI: Uncovering the S...
gmuir1066
 
md-presentHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHation.pptx
md-presentHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHation.pptxmd-presentHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHation.pptx
md-presentHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHation.pptx
fatimalazaar2004
 

Introduction to CaseWare IDEA - Designed by Auditors for Auditors

  • 1. INTRODUCTION TO CASEWARE IDEA DESIGNED BY AUDITORS FOR AUDITORS
  • 2. AGENDA • Introduction to CaseWare IDEA Inc.
  • 3. ABOUT CASEWARE IDEA INC. • Founded in 1988 • Industry leader in solutions for finance, accounting, governance, risk and audit professionals • Over 400,000 users of our technologies across 150 countries and 16 languages • Customers include Fortune 500 companies, Global 500 companies, 9 governments of the 15 largest economies
  • 4. WHY DATA ANALYTICS? 1. Volume of transactions has increased 2. Absence of physical evidence (all electronic) 3. Regulatory focus on fraud and controls 4. Audit standards recommend using CAATs 5. Need to test 100% of transactions
  • 5. WHY DATA ANALYTICS? 6. Pressure on costs and efficiency 7. Manage risks more effectively 8. Pressure from the auditees to use more analytics 9. Value added (methodology)
  • 6. CHALLENGES • Data acquisition • Retrieving data from different software and ERP systems • Lack of standards • Skills • Acceptance and mindset • Fundamental change in audit techniques • Changes in auditing standards • Which manual tests can be replaced
  • 7. AGENDA • Introduction to CaseWare IDEA Inc. • Introduction IDEA Data Analysis software
  • 8. DATA ANALYSIS PROCESS RETRIEVAL IMPORT CLEAN PREPARE VALIDATE ANALYSIS REPORTING
  • 9. DATA ACQUISITION IDEA allows you to import and export data in a multitude of formats, including files originating from large mainframe computers and accounting software IDEA
  • 10. GETTING/UNDERSTANDING DATA • Import from CSV, Excel, PDF, Reports • Import directly from accounting software • Connectors to ERP • Different format = TAGGING • Participating in data standards AIS SAF-T Audit Data Standard Audit Data Collection
  • 11. DATA ANALYSIS Pivot Tables Reports Charts Exports History Project Overview Automate Import from virtually any source – from PDF to ERP Extract • Sort • Search • Group Calculated Fields • Stratify • Summarize Age • Gaps Duplicates • Sample Statistics • Join • Append • Compare 1. Import Data 2. Perform Analysis 3. Review Results
  • 12. AGENDA • Introduction to CaseWare IDEA Inc. • Introduction IDEA Data Analysis software • Case studies
  • 13. CASE 1 - PAYMENTS • Import • Reconciliation / Field Stats • Discover and Visualize the data • Check on missing cheque numbers • Check on duplicate cheque numbers • Check on fuzzy duplicate suppliers • Join with Authorization table • Perform a stratified random Sample
  • 14. CASE 2 – JOURNAL ENTRIES • Import • Exceptions (unbalanced entries) • Summary by Accounts (sent to Working Papers)
  • 15. CASE 3 - INVOICES • Import • Calculation accuracy • Benford’s Law (Mark J. Nigrini PhD)
  • 16. AGENDA • Introduction to CaseWare IDEA Inc. • Introduction IDEA Data Analysis software • Case studies • Benefits of CaseWare IDEA Data Analysis software
  • 17.  Complicated equations  No data integrity  User friendly interface  Data integrity  Enter a few values and receive a result Use the Age Band column as the column field in the Pivot Table. The oldest (i.e., first) date should be older than the oldest record. For simplicity, use “1” (1/1/1900) as the date. This will represent the “X days +” band. EXCEL VS. IDEA: AGING
  • 18.  Not intuitive  Can easily override values  No drill down feature  No custom graph  User friendly  Read-only access  Drill down feature  Custom graph Frequencies predicted by Benford’s Law for First Digit, Second Digit, and First Three Digit tests. EXCEL VS. IDEA: BENFORD’S LAW
  • 19. EXCEL VS IDEA – DATA PROTECTION With protected data, you can do the following:  Duplicate Detection  Apply Benford’s Law  Summarization  Stratification  Gap Detection  Quick Extraction  Several Sampling Methods  Key Extraction  Advanced Statistical Methods  Multitask  Various Imports  Structure Reports
  • 20. WHY USE CASEWARE IDEA? 1. IDEA protects the source data by allowing read only access to the client's data to avoid any unwanted changes, and maintain data integrity. 2. IDEA creates a record of all changes made to a file (database) and maintains an audit trail or log of all operations carried out on a database, including the import and each audit test. 20
  • 21. WHY USE CASEWARE IDEA? 3. IDEA can do the following: • Compare, join, append, connect different files from different sources • Extract specific transactions, identifies gaps (e.g. check number) or duplicates • Profile data by summarizing, stratifying or aging the files • Create useful File Statistics automatically • Create samples using several different sampling methods 21
  • 22. WHY USE CASEWARE IDEA? 4. IDEA allows you to import and export data into a multitude of formats, including files originating from large mainframe computers and accounting software. 5. Allows you to easily manage your files and results and shows the source of your results 6. IDEA can read and process millions of records in seconds. There is no limit to the number of records that IDEA can process. 22
  • 23. Change can be difficult for anyone. Inventor Charles Kettering once said, “The world hates change, yet it is the only thing that has brought progress.” (IIA GTAG16)
  • 24. SUMMARY: BENEFITS OF USING IDEA 1. Work more efficiently ... lower your costs 2. Work more effectively … add more quality 3. Improve your capabilities … add more value
  • 25. INTERESTED IN A DEMO OF IDEA? Contact us at [email protected] to schedule a demonstration
  • 26. INTRODUCTION TO CASEWARE IDEA DESIGNED BY AUDITORS FOR AUDITORS Visit casewareanalytics.com Email [email protected]