SlideShare a Scribd company logo
1 of 27
17.5th CarLab Advisory Board Meeting
Webex call
June 15, 2020
Agenda
• Weather, News, Sports Miklos Vasarhelyi
• Advancement of analytics in standards Helen Brown-Liburd
• Current research projects:
• -- Dark Owl/ Inbev/ B3 Arion Cheong
• -- RPA projects Abby Zhang
• -- Prefeitura Wenru Wang
• -- PIOB Kevin Moffitt
• -- GASB Ben Yoon
• -- Covid Kelly Duan
• Open Discussion
• Coming Events Annual CAR Lab Advisory
Board Meeting
• Proposed date: November 5, 2020
50 WCARS at RBS in Newark – Nov. 6 & 7, 2019 2
PCAOB Data and Technology Update
• PCAOB auditing standards are not precluding or detracting from firms’
ability to use, they acknowledge—that our current standards do not explicitly
encourage the use of such tools, indicate when their use might be
appropriate, or highlight related risks or pitfalls associated with their use.
• Technology based tools inform the auditor’s risk assessment by providing
different perspectives, exposing previously unidentified relationships that
may reveal new risks, and providing more information to be used when
assessing risks.
– However, when performing certain risk assessment procedures these
tools do not diminish the importance of addressing other requirements
related to risk assessment that do not necessarily lend themselves to
the use of tools
• The audit evidence standard does not preclude the auditor from using
technology-based tools to perform audit procedures more efficiently to
obtain audit evidence
3
CARLab Project Report
DarkOwl
(Darkweb Data
Collector)
B3
(Brazilian Stock
Exchange)
AB InBev
(Brewing Company)
Darknet market activity
monitoring and auditing
• Darknet market postings
(Blog+Forum+Paste)
• Data analysis
• Textual analysis
Machine driven market
manipulative activity
• Real-time Transactions
(All transactions – B3)
• Data analysis
(Time Series+ML)
Fraud detection model
development
• Investigation Report
• Free Beer
• Data analysis
• ML
RPA
• P1: - automated selected substantive testings in the Employee Benefit Plan
audits. This became Andrea's dissertation and we have some professional
articles about it.
• P2: - automated a type of confirmation procedure. The paper is published in
IJAIS.
• P3: - automated selected processes in audit planning of Single Audits. Chanta
and Abby are in the process of paper revision.
• P4: We automated a mundane task in the real estate audits. After going
through challenges of automation within virtual machines and dealing with an
audit software that is not automation-friendly, we are able to automate a process
that usually takes 15-20 min to 5 min. P4 is conducting tests now.
• P5. Potentially automate an audit documentation procedure that involves
moving data from word documents to a cloud-based internal audit software.
Now we are waiting for documentation and data. (new phd students, Fangbing
and Lanxin, will be in this project)
• P6: Potentially automate an administration task for auditors. We are in the
process of discussing potential solutions. (new phd students, Fangbing and
Lanxin will be in this project)
Continuous Monitoring and Audit
Methodology for Medication
Procurement
Wenru Wang – Rutgers University
Miklos A. Vasarhelyi – Rutgers University
June 15, 2020
Overview
• Prefeitura Rio de Janeiro
• 30,000+ Medication procurement data, 2017 – 2019
• Audit analytics for data preprocessing
• Continuous monitoring and audit system for exception and
anomaly detections
7
8
9
10
COVID-19 Procurement
• What has happened
(descriptive analytics)
• What will happen
(predictive analytics)
• What is the optimized
solution (prescriptive
analytics).
• Data cleaning
– Text mining, machine
learning.
11
GASB
Post-Implementation Review Project
Ben Yoon
(Ben Yoon, Kathy Wei, Huaxia Li, Prof. Kevin Moffitt,
Prof. Miklos Vasarhelyi, and Prof. Irfan Bora)
June 2020
• Are pensions safe?
 In 2012, the GASB announced the pension standards for
more transparent reporting (No. 67 and 68).
Background
• In 2012, the GASB announced the pension standards for more
transparent reporting (No. 67 and 68).
• Are all the entities following the GASB’s new pension standards?
- It would be useful if the GASB can monitor the CAFRs.
- But there are challenges:
1) The CAFR reports are PDF documents and long (100-300 pages).
2) Different CAFRs uses different formats.
3) CAFRs are scattered in the Internet.
Project objective
• This project consists of 4 steps.
Collect
CAFRs
Convert
CAFRs
Analyze CAFRs
(117 pre-defined
items)
Create
reports
• Rutgers has conducted initial pilot tests.
- Step1: Collecting CAFRs from multiple repositories
- Step2: Converting PDF documents
- Step3: Extracting items from the CAFRs
- Step4: Report with Excel format
4 steps of this project
Converting PDF
• Conversion into MS-Excel format
• Illustrative example
Extracting information
Continuous Intelligent Pandemic
Monitoring (CIPM)
18
Presented by: Huijue Kelly Duan
Background
19
• With the current outbreak of COVID-19 pandemic, authorities
are struggling for accurate and timely information in order to
control the spread of the epidemic and provide adequate
instructions to the communities.
• The fundamental issue is that the key metrics used to guide
policy and action are dimensionally incorrect for a multitude of
reasons
– The number of contaminated people
– Hospitalizations and heath cases
– The number of people who are asymptomatic
• Tremendous filtering on who gets tested; lacking in sufficient test kits
20
Research Objectives
21
• Use measurement science (accounting), assurance science
(auditing) to examine the situation
• Apply AI-based predictive analytics to epidemic research
• Accounting methodologies + machine learning algorithms
– Continuous Monitoring
– Multidimensional Audit Data Selection (MADS)
– Machine learning and artificial neural networks
• This study aims to
– the augment of information quality and timeliness
– the provision of adequate policy
Framework
22
Data Collection
• Establish a timely repository database of relevant exogenous and endogenous data sources
Office announcement, social media posts, personal GPS data, Google flu trend, fever data based on
thermometer reading apps, medical supplies purchase amount, economic related data, etc.
Model
Construction
• Create a systematic and continuous COVID-19 monitoring model by using different epidemic models
and machine learning algorithms
 Classic Epidemic Models (SIR, SEIR, separable-temporal exponential-family random graph models)
 AI predictions (SVM, XGBoost, Neural Network models)
 Economic Impact
Alerts
• Incorporate audit risk assessment to establish an alert system
Action
Recommendations
• Incorporate the knowledge obtained from different analysis to provide different levels of preventive
policies and strategies regarding the pandemic, economics, as well as medical resources related
recommendations.
23
Figure 1:Utilizing the SIR model to predict the total number of
confirmed cases in United States; and the inflection point after the
outbreak
(This model does not consider the exogenous variables)
Figure 2: simulating the impacts of different social distancing
policies on infected cases assuming the total number of
population is equal to 1000
(This model does not consider the exogenous variables)
Innovation and Strategic Advantages
• Following the accounting frameworks, this study aims to establish a
continuous monitoring system for COVID-19
– The continuous monitoring and alert activation process is close to real-
time, which enables earlier reaction to the signals
– The monitoring activities are continuous, which helps preventing future
outbreaks
• The model uses Internet of Things (IoT) to gather the relevant
exogenous data to perform comprehensive data analytics
• Depending on the specific contingencies, action recommendations
on quarantine and economy support will be predictively and
automatically provided
24
Conclusions
• We Have new leadership
• Many organizations are jumping into the fray
• We need to deal better with the bureaucratic
challenges of Rutgers
• COVID makes us more important but creates
many challenges
• Our teaching mission is becoming more
important
• Many opportunities are available
• WE NEED YOUR ADVICE
17.5th CarLab Advisory Board Meeting
17.5th CarLab Advisory Board Meeting

More Related Content

What's hot

Unified Clinical Operations - Ennov Presentation
Unified Clinical Operations - Ennov PresentationUnified Clinical Operations - Ennov Presentation
Unified Clinical Operations - Ennov PresentationEnnov
 
Predictive Maintenance with R
Predictive Maintenance with RPredictive Maintenance with R
Predictive Maintenance with Reoda GmbH
 
Auditing Systems Development
Auditing Systems DevelopmentAuditing Systems Development
Auditing Systems Developmentessbaih
 
Iiaic08 power point cs2-3_track_regulatory session v3
Iiaic08 power point cs2-3_track_regulatory session v3Iiaic08 power point cs2-3_track_regulatory session v3
Iiaic08 power point cs2-3_track_regulatory session v3Gene Kim
 
1 Qs Overview
1 Qs Overview1 Qs Overview
1 Qs Overviewrap36case
 
Process Intelligence In Dynamic Processes – Challenge Accepted
Process Intelligence  In Dynamic Processes – Challenge AcceptedProcess Intelligence  In Dynamic Processes – Challenge Accepted
Process Intelligence In Dynamic Processes – Challenge AcceptedNico Herzberg
 
Supplier vs EPC survey
Supplier vs EPC surveySupplier vs EPC survey
Supplier vs EPC surveyCarl Mueller
 
Accounting for non functional and project requirements - cosmic and ifpug dev...
Accounting for non functional and project requirements - cosmic and ifpug dev...Accounting for non functional and project requirements - cosmic and ifpug dev...
Accounting for non functional and project requirements - cosmic and ifpug dev...IWSM Mensura
 
Policy for Exporting Taiwan ICT Capacity
Policy for Exporting Taiwan ICT CapacityPolicy for Exporting Taiwan ICT Capacity
Policy for Exporting Taiwan ICT CapacityKenny Huang Ph.D.
 
Webinar: Hoe houdt u de marge op peil bij de huidige record hoge energieprijzen
Webinar: Hoe houdt u de marge op peil bij de huidige record hoge energieprijzenWebinar: Hoe houdt u de marge op peil bij de huidige record hoge energieprijzen
Webinar: Hoe houdt u de marge op peil bij de huidige record hoge energieprijzenStork
 
Measuring the value of ci1
Measuring the value of ci1Measuring the value of ci1
Measuring the value of ci1Dr. Avner Barnea
 
ITGC audit of ERPs
ITGC audit of ERPsITGC audit of ERPs
ITGC audit of ERPsJayesh Daga
 
UAT for a Major US Banking Conglomerate
UAT for a Major US Banking ConglomerateUAT for a Major US Banking Conglomerate
UAT for a Major US Banking ConglomerateThinksoft Global
 
Stream D_Richard Hawkins, Patrick Reniers
Stream D_Richard Hawkins, Patrick ReniersStream D_Richard Hawkins, Patrick Reniers
Stream D_Richard Hawkins, Patrick ReniersBecarAsset
 

What's hot (15)

Unified Clinical Operations - Ennov Presentation
Unified Clinical Operations - Ennov PresentationUnified Clinical Operations - Ennov Presentation
Unified Clinical Operations - Ennov Presentation
 
Predictive Maintenance with R
Predictive Maintenance with RPredictive Maintenance with R
Predictive Maintenance with R
 
Auditing Systems Development
Auditing Systems DevelopmentAuditing Systems Development
Auditing Systems Development
 
Iiaic08 power point cs2-3_track_regulatory session v3
Iiaic08 power point cs2-3_track_regulatory session v3Iiaic08 power point cs2-3_track_regulatory session v3
Iiaic08 power point cs2-3_track_regulatory session v3
 
1 Qs Overview
1 Qs Overview1 Qs Overview
1 Qs Overview
 
Process Intelligence In Dynamic Processes – Challenge Accepted
Process Intelligence  In Dynamic Processes – Challenge AcceptedProcess Intelligence  In Dynamic Processes – Challenge Accepted
Process Intelligence In Dynamic Processes – Challenge Accepted
 
Supplier vs EPC survey
Supplier vs EPC surveySupplier vs EPC survey
Supplier vs EPC survey
 
Accounting for non functional and project requirements - cosmic and ifpug dev...
Accounting for non functional and project requirements - cosmic and ifpug dev...Accounting for non functional and project requirements - cosmic and ifpug dev...
Accounting for non functional and project requirements - cosmic and ifpug dev...
 
Bankauditin it env
Bankauditin it envBankauditin it env
Bankauditin it env
 
Policy for Exporting Taiwan ICT Capacity
Policy for Exporting Taiwan ICT CapacityPolicy for Exporting Taiwan ICT Capacity
Policy for Exporting Taiwan ICT Capacity
 
Webinar: Hoe houdt u de marge op peil bij de huidige record hoge energieprijzen
Webinar: Hoe houdt u de marge op peil bij de huidige record hoge energieprijzenWebinar: Hoe houdt u de marge op peil bij de huidige record hoge energieprijzen
Webinar: Hoe houdt u de marge op peil bij de huidige record hoge energieprijzen
 
Measuring the value of ci1
Measuring the value of ci1Measuring the value of ci1
Measuring the value of ci1
 
ITGC audit of ERPs
ITGC audit of ERPsITGC audit of ERPs
ITGC audit of ERPs
 
UAT for a Major US Banking Conglomerate
UAT for a Major US Banking ConglomerateUAT for a Major US Banking Conglomerate
UAT for a Major US Banking Conglomerate
 
Stream D_Richard Hawkins, Patrick Reniers
Stream D_Richard Hawkins, Patrick ReniersStream D_Richard Hawkins, Patrick Reniers
Stream D_Richard Hawkins, Patrick Reniers
 

Similar to 17.5th CarLab Advisory Board Meeting

“RAKTANCHAL” An Blood bank finder application (Priyanka Tiwari) (4) (1).docx
“RAKTANCHAL” An Blood bank finder application (Priyanka Tiwari) (4) (1).docx“RAKTANCHAL” An Blood bank finder application (Priyanka Tiwari) (4) (1).docx
“RAKTANCHAL” An Blood bank finder application (Priyanka Tiwari) (4) (1).docxArpitMishra139426
 
The Digital Twin For Production Optimization
The Digital Twin For Production OptimizationThe Digital Twin For Production Optimization
The Digital Twin For Production OptimizationYokogawa1
 
Six cigma AJAL
Six cigma AJALSix cigma AJAL
Six cigma AJALAJAL A J
 
Assocham global conference audit data standards - 28.10.2020
Assocham global conference   audit data standards - 28.10.2020Assocham global conference   audit data standards - 28.10.2020
Assocham global conference audit data standards - 28.10.2020Vinod Kashyap
 
IRJET-Financial Distress Prediction of a Company using Data Mining
IRJET-Financial Distress Prediction of a Company using Data MiningIRJET-Financial Distress Prediction of a Company using Data Mining
IRJET-Financial Distress Prediction of a Company using Data MiningIRJET Journal
 
AI in Modern Safety Regulators.pdf
AI in Modern Safety Regulators.pdfAI in Modern Safety Regulators.pdf
AI in Modern Safety Regulators.pdfJessie_N
 
Be a Junior Auditor! (call)
Be a Junior Auditor! (call)Be a Junior Auditor! (call)
Be a Junior Auditor! (call)adelina peltea
 
tranSMART Community Meeting 5-7 Nov 13 - Session 5: eTRIKS - Science Driven D...
tranSMART Community Meeting 5-7 Nov 13 - Session 5: eTRIKS - Science Driven D...tranSMART Community Meeting 5-7 Nov 13 - Session 5: eTRIKS - Science Driven D...
tranSMART Community Meeting 5-7 Nov 13 - Session 5: eTRIKS - Science Driven D...David Peyruc
 
Eurisc analytics and big data solutions
Eurisc analytics and big data solutionsEurisc analytics and big data solutions
Eurisc analytics and big data solutionsmarcoxplace
 
Call for Junior Auditors! [JADE]
Call for Junior Auditors! [JADE]Call for Junior Auditors! [JADE]
Call for Junior Auditors! [JADE]adelina peltea
 
Predictive Test Planning to Improve System Quality
Predictive Test Planning to Improve System QualityPredictive Test Planning to Improve System Quality
Predictive Test Planning to Improve System QualityTechWell
 
Developing practical evidence-based solutions to prevent harm in the workplace
Developing practical evidence-based solutions to prevent harm in the workplace Developing practical evidence-based solutions to prevent harm in the workplace
Developing practical evidence-based solutions to prevent harm in the workplace Australian Institute of Health & Safety
 
Applying Capability Modelling in the Genomics Diagnosis Domain: Lessons Learned
Applying Capability Modelling in the Genomics Diagnosis Domain: Lessons Learned Applying Capability Modelling in the Genomics Diagnosis Domain: Lessons Learned
Applying Capability Modelling in the Genomics Diagnosis Domain: Lessons Learned CaaS EU FP7 Project
 
Covid-19 Data Analysis and Visualization
Covid-19 Data Analysis and VisualizationCovid-19 Data Analysis and Visualization
Covid-19 Data Analysis and VisualizationIRJET Journal
 
ISMA 9 - van Heeringen - Using IFPUG and ISBSG to improve organization success
ISMA 9 - van Heeringen - Using IFPUG and ISBSG to improve organization successISMA 9 - van Heeringen - Using IFPUG and ISBSG to improve organization success
ISMA 9 - van Heeringen - Using IFPUG and ISBSG to improve organization successHarold van Heeringen
 
Borys Pratsiuk "How to be NVidia partner"
Borys Pratsiuk "How to be NVidia partner"Borys Pratsiuk "How to be NVidia partner"
Borys Pratsiuk "How to be NVidia partner"Lviv Startup Club
 
The State of Open Source for Software Alliance Germany 2023-04-14
The State of Open Source for Software Alliance Germany 2023-04-14The State of Open Source for Software Alliance Germany 2023-04-14
The State of Open Source for Software Alliance Germany 2023-04-14Shane Coughlan
 

Similar to 17.5th CarLab Advisory Board Meeting (20)

“RAKTANCHAL” An Blood bank finder application (Priyanka Tiwari) (4) (1).docx
“RAKTANCHAL” An Blood bank finder application (Priyanka Tiwari) (4) (1).docx“RAKTANCHAL” An Blood bank finder application (Priyanka Tiwari) (4) (1).docx
“RAKTANCHAL” An Blood bank finder application (Priyanka Tiwari) (4) (1).docx
 
The Digital Twin For Production Optimization
The Digital Twin For Production OptimizationThe Digital Twin For Production Optimization
The Digital Twin For Production Optimization
 
Six cigma AJAL
Six cigma AJALSix cigma AJAL
Six cigma AJAL
 
Assocham global conference audit data standards - 28.10.2020
Assocham global conference   audit data standards - 28.10.2020Assocham global conference   audit data standards - 28.10.2020
Assocham global conference audit data standards - 28.10.2020
 
IRJET-Financial Distress Prediction of a Company using Data Mining
IRJET-Financial Distress Prediction of a Company using Data MiningIRJET-Financial Distress Prediction of a Company using Data Mining
IRJET-Financial Distress Prediction of a Company using Data Mining
 
AI in Modern Safety Regulators.pdf
AI in Modern Safety Regulators.pdfAI in Modern Safety Regulators.pdf
AI in Modern Safety Regulators.pdf
 
Be a Junior Auditor! (call)
Be a Junior Auditor! (call)Be a Junior Auditor! (call)
Be a Junior Auditor! (call)
 
tranSMART Community Meeting 5-7 Nov 13 - Session 5: eTRIKS - Science Driven D...
tranSMART Community Meeting 5-7 Nov 13 - Session 5: eTRIKS - Science Driven D...tranSMART Community Meeting 5-7 Nov 13 - Session 5: eTRIKS - Science Driven D...
tranSMART Community Meeting 5-7 Nov 13 - Session 5: eTRIKS - Science Driven D...
 
Eurisc analytics and big data solutions
Eurisc analytics and big data solutionsEurisc analytics and big data solutions
Eurisc analytics and big data solutions
 
Call for Junior Auditors! [JADE]
Call for Junior Auditors! [JADE]Call for Junior Auditors! [JADE]
Call for Junior Auditors! [JADE]
 
Predictive Test Planning to Improve System Quality
Predictive Test Planning to Improve System QualityPredictive Test Planning to Improve System Quality
Predictive Test Planning to Improve System Quality
 
Developing practical evidence-based solutions to prevent harm in the workplace
Developing practical evidence-based solutions to prevent harm in the workplace Developing practical evidence-based solutions to prevent harm in the workplace
Developing practical evidence-based solutions to prevent harm in the workplace
 
Applying Capability Modelling in the Genomics Diagnosis Domain: Lessons Learned
Applying Capability Modelling in the Genomics Diagnosis Domain: Lessons Learned Applying Capability Modelling in the Genomics Diagnosis Domain: Lessons Learned
Applying Capability Modelling in the Genomics Diagnosis Domain: Lessons Learned
 
Policy Implications of the 2020 Biennial Review Report: A focus on Mutual Acc...
Policy Implications of the 2020 Biennial Review Report: A focus on Mutual Acc...Policy Implications of the 2020 Biennial Review Report: A focus on Mutual Acc...
Policy Implications of the 2020 Biennial Review Report: A focus on Mutual Acc...
 
Covid-19 Data Analysis and Visualization
Covid-19 Data Analysis and VisualizationCovid-19 Data Analysis and Visualization
Covid-19 Data Analysis and Visualization
 
ISMA 9 - van Heeringen - Using IFPUG and ISBSG to improve organization success
ISMA 9 - van Heeringen - Using IFPUG and ISBSG to improve organization successISMA 9 - van Heeringen - Using IFPUG and ISBSG to improve organization success
ISMA 9 - van Heeringen - Using IFPUG and ISBSG to improve organization success
 
Borys Pratsiuk "How to be NVidia partner"
Borys Pratsiuk "How to be NVidia partner"Borys Pratsiuk "How to be NVidia partner"
Borys Pratsiuk "How to be NVidia partner"
 
New WHO Guidance on CS Validation
New WHO Guidance on CS ValidationNew WHO Guidance on CS Validation
New WHO Guidance on CS Validation
 
The State of Open Source for Software Alliance Germany 2023-04-14
The State of Open Source for Software Alliance Germany 2023-04-14The State of Open Source for Software Alliance Germany 2023-04-14
The State of Open Source for Software Alliance Germany 2023-04-14
 
Future of Audit by Pieter de Kok
Future of Audit by Pieter de KokFuture of Audit by Pieter de Kok
Future of Audit by Pieter de Kok
 

Recently uploaded

RABBIT: A CLI tool for identifying bots based on their GitHub events.
RABBIT: A CLI tool for identifying bots based on their GitHub events.RABBIT: A CLI tool for identifying bots based on their GitHub events.
RABBIT: A CLI tool for identifying bots based on their GitHub events.natarajan8993
 
Defining Constituents, Data Vizzes and Telling a Data Story
Defining Constituents, Data Vizzes and Telling a Data StoryDefining Constituents, Data Vizzes and Telling a Data Story
Defining Constituents, Data Vizzes and Telling a Data StoryJeremy Anderson
 
Predictive Analysis for Loan Default Presentation : Data Analysis Project PPT
Predictive Analysis for Loan Default  Presentation : Data Analysis Project PPTPredictive Analysis for Loan Default  Presentation : Data Analysis Project PPT
Predictive Analysis for Loan Default Presentation : Data Analysis Project PPTBoston Institute of Analytics
 
办美国阿肯色大学小石城分校毕业证成绩单pdf电子版制作修改#真实留信入库#永久存档#真实可查#diploma#degree
办美国阿肯色大学小石城分校毕业证成绩单pdf电子版制作修改#真实留信入库#永久存档#真实可查#diploma#degree办美国阿肯色大学小石城分校毕业证成绩单pdf电子版制作修改#真实留信入库#永久存档#真实可查#diploma#degree
办美国阿肯色大学小石城分校毕业证成绩单pdf电子版制作修改#真实留信入库#永久存档#真实可查#diploma#degreeyuu sss
 
Decoding the Heart: Student Presentation on Heart Attack Prediction with Data...
Decoding the Heart: Student Presentation on Heart Attack Prediction with Data...Decoding the Heart: Student Presentation on Heart Attack Prediction with Data...
Decoding the Heart: Student Presentation on Heart Attack Prediction with Data...Boston Institute of Analytics
 
Generative AI for Social Good at Open Data Science East 2024
Generative AI for Social Good at Open Data Science East 2024Generative AI for Social Good at Open Data Science East 2024
Generative AI for Social Good at Open Data Science East 2024Colleen Farrelly
 
Thiophen Mechanism khhjjjjjjjhhhhhhhhhhh
Thiophen Mechanism khhjjjjjjjhhhhhhhhhhhThiophen Mechanism khhjjjjjjjhhhhhhhhhhh
Thiophen Mechanism khhjjjjjjjhhhhhhhhhhhYasamin16
 
Semantic Shed - Squashing and Squeezing.pptx
Semantic Shed - Squashing and Squeezing.pptxSemantic Shed - Squashing and Squeezing.pptx
Semantic Shed - Squashing and Squeezing.pptxMike Bennett
 
English-8-Q4-W3-Synthesizing-Essential-Information-From-Various-Sources-1.pdf
English-8-Q4-W3-Synthesizing-Essential-Information-From-Various-Sources-1.pdfEnglish-8-Q4-W3-Synthesizing-Essential-Information-From-Various-Sources-1.pdf
English-8-Q4-W3-Synthesizing-Essential-Information-From-Various-Sources-1.pdfblazblazml
 
The Power of Data-Driven Storytelling_ Unveiling the Layers of Insight.pptx
The Power of Data-Driven Storytelling_ Unveiling the Layers of Insight.pptxThe Power of Data-Driven Storytelling_ Unveiling the Layers of Insight.pptx
The Power of Data-Driven Storytelling_ Unveiling the Layers of Insight.pptxTasha Penwell
 
Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...
Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...
Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...Boston Institute of Analytics
 
Identifying Appropriate Test Statistics Involving Population Mean
Identifying Appropriate Test Statistics Involving Population MeanIdentifying Appropriate Test Statistics Involving Population Mean
Identifying Appropriate Test Statistics Involving Population MeanMYRABACSAFRA2
 
NO1 Certified Black Magic Specialist Expert Amil baba in Lahore Islamabad Raw...
NO1 Certified Black Magic Specialist Expert Amil baba in Lahore Islamabad Raw...NO1 Certified Black Magic Specialist Expert Amil baba in Lahore Islamabad Raw...
NO1 Certified Black Magic Specialist Expert Amil baba in Lahore Islamabad Raw...Amil Baba Dawood bangali
 
Predicting Salary Using Data Science: A Comprehensive Analysis.pdf
Predicting Salary Using Data Science: A Comprehensive Analysis.pdfPredicting Salary Using Data Science: A Comprehensive Analysis.pdf
Predicting Salary Using Data Science: A Comprehensive Analysis.pdfBoston Institute of Analytics
 
Student profile product demonstration on grades, ability, well-being and mind...
Student profile product demonstration on grades, ability, well-being and mind...Student profile product demonstration on grades, ability, well-being and mind...
Student profile product demonstration on grades, ability, well-being and mind...Seán Kennedy
 
Learn How Data Science Changes Our World
Learn How Data Science Changes Our WorldLearn How Data Science Changes Our World
Learn How Data Science Changes Our WorldEduminds Learning
 
Conf42-LLM_Adding Generative AI to Real-Time Streaming Pipelines
Conf42-LLM_Adding Generative AI to Real-Time Streaming PipelinesConf42-LLM_Adding Generative AI to Real-Time Streaming Pipelines
Conf42-LLM_Adding Generative AI to Real-Time Streaming PipelinesTimothy Spann
 
Bank Loan Approval Analysis: A Comprehensive Data Analysis Project
Bank Loan Approval Analysis: A Comprehensive Data Analysis ProjectBank Loan Approval Analysis: A Comprehensive Data Analysis Project
Bank Loan Approval Analysis: A Comprehensive Data Analysis ProjectBoston Institute of Analytics
 

Recently uploaded (20)

Data Analysis Project: Stroke Prediction
Data Analysis Project: Stroke PredictionData Analysis Project: Stroke Prediction
Data Analysis Project: Stroke Prediction
 
RABBIT: A CLI tool for identifying bots based on their GitHub events.
RABBIT: A CLI tool for identifying bots based on their GitHub events.RABBIT: A CLI tool for identifying bots based on their GitHub events.
RABBIT: A CLI tool for identifying bots based on their GitHub events.
 
Defining Constituents, Data Vizzes and Telling a Data Story
Defining Constituents, Data Vizzes and Telling a Data StoryDefining Constituents, Data Vizzes and Telling a Data Story
Defining Constituents, Data Vizzes and Telling a Data Story
 
Predictive Analysis for Loan Default Presentation : Data Analysis Project PPT
Predictive Analysis for Loan Default  Presentation : Data Analysis Project PPTPredictive Analysis for Loan Default  Presentation : Data Analysis Project PPT
Predictive Analysis for Loan Default Presentation : Data Analysis Project PPT
 
办美国阿肯色大学小石城分校毕业证成绩单pdf电子版制作修改#真实留信入库#永久存档#真实可查#diploma#degree
办美国阿肯色大学小石城分校毕业证成绩单pdf电子版制作修改#真实留信入库#永久存档#真实可查#diploma#degree办美国阿肯色大学小石城分校毕业证成绩单pdf电子版制作修改#真实留信入库#永久存档#真实可查#diploma#degree
办美国阿肯色大学小石城分校毕业证成绩单pdf电子版制作修改#真实留信入库#永久存档#真实可查#diploma#degree
 
Decoding the Heart: Student Presentation on Heart Attack Prediction with Data...
Decoding the Heart: Student Presentation on Heart Attack Prediction with Data...Decoding the Heart: Student Presentation on Heart Attack Prediction with Data...
Decoding the Heart: Student Presentation on Heart Attack Prediction with Data...
 
Generative AI for Social Good at Open Data Science East 2024
Generative AI for Social Good at Open Data Science East 2024Generative AI for Social Good at Open Data Science East 2024
Generative AI for Social Good at Open Data Science East 2024
 
Thiophen Mechanism khhjjjjjjjhhhhhhhhhhh
Thiophen Mechanism khhjjjjjjjhhhhhhhhhhhThiophen Mechanism khhjjjjjjjhhhhhhhhhhh
Thiophen Mechanism khhjjjjjjjhhhhhhhhhhh
 
Semantic Shed - Squashing and Squeezing.pptx
Semantic Shed - Squashing and Squeezing.pptxSemantic Shed - Squashing and Squeezing.pptx
Semantic Shed - Squashing and Squeezing.pptx
 
English-8-Q4-W3-Synthesizing-Essential-Information-From-Various-Sources-1.pdf
English-8-Q4-W3-Synthesizing-Essential-Information-From-Various-Sources-1.pdfEnglish-8-Q4-W3-Synthesizing-Essential-Information-From-Various-Sources-1.pdf
English-8-Q4-W3-Synthesizing-Essential-Information-From-Various-Sources-1.pdf
 
The Power of Data-Driven Storytelling_ Unveiling the Layers of Insight.pptx
The Power of Data-Driven Storytelling_ Unveiling the Layers of Insight.pptxThe Power of Data-Driven Storytelling_ Unveiling the Layers of Insight.pptx
The Power of Data-Driven Storytelling_ Unveiling the Layers of Insight.pptx
 
Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...
Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...
Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...
 
Insurance Churn Prediction Data Analysis Project
Insurance Churn Prediction Data Analysis ProjectInsurance Churn Prediction Data Analysis Project
Insurance Churn Prediction Data Analysis Project
 
Identifying Appropriate Test Statistics Involving Population Mean
Identifying Appropriate Test Statistics Involving Population MeanIdentifying Appropriate Test Statistics Involving Population Mean
Identifying Appropriate Test Statistics Involving Population Mean
 
NO1 Certified Black Magic Specialist Expert Amil baba in Lahore Islamabad Raw...
NO1 Certified Black Magic Specialist Expert Amil baba in Lahore Islamabad Raw...NO1 Certified Black Magic Specialist Expert Amil baba in Lahore Islamabad Raw...
NO1 Certified Black Magic Specialist Expert Amil baba in Lahore Islamabad Raw...
 
Predicting Salary Using Data Science: A Comprehensive Analysis.pdf
Predicting Salary Using Data Science: A Comprehensive Analysis.pdfPredicting Salary Using Data Science: A Comprehensive Analysis.pdf
Predicting Salary Using Data Science: A Comprehensive Analysis.pdf
 
Student profile product demonstration on grades, ability, well-being and mind...
Student profile product demonstration on grades, ability, well-being and mind...Student profile product demonstration on grades, ability, well-being and mind...
Student profile product demonstration on grades, ability, well-being and mind...
 
Learn How Data Science Changes Our World
Learn How Data Science Changes Our WorldLearn How Data Science Changes Our World
Learn How Data Science Changes Our World
 
Conf42-LLM_Adding Generative AI to Real-Time Streaming Pipelines
Conf42-LLM_Adding Generative AI to Real-Time Streaming PipelinesConf42-LLM_Adding Generative AI to Real-Time Streaming Pipelines
Conf42-LLM_Adding Generative AI to Real-Time Streaming Pipelines
 
Bank Loan Approval Analysis: A Comprehensive Data Analysis Project
Bank Loan Approval Analysis: A Comprehensive Data Analysis ProjectBank Loan Approval Analysis: A Comprehensive Data Analysis Project
Bank Loan Approval Analysis: A Comprehensive Data Analysis Project
 

17.5th CarLab Advisory Board Meeting

  • 1. 17.5th CarLab Advisory Board Meeting Webex call June 15, 2020
  • 2. Agenda • Weather, News, Sports Miklos Vasarhelyi • Advancement of analytics in standards Helen Brown-Liburd • Current research projects: • -- Dark Owl/ Inbev/ B3 Arion Cheong • -- RPA projects Abby Zhang • -- Prefeitura Wenru Wang • -- PIOB Kevin Moffitt • -- GASB Ben Yoon • -- Covid Kelly Duan • Open Discussion • Coming Events Annual CAR Lab Advisory Board Meeting • Proposed date: November 5, 2020 50 WCARS at RBS in Newark – Nov. 6 & 7, 2019 2
  • 3. PCAOB Data and Technology Update • PCAOB auditing standards are not precluding or detracting from firms’ ability to use, they acknowledge—that our current standards do not explicitly encourage the use of such tools, indicate when their use might be appropriate, or highlight related risks or pitfalls associated with their use. • Technology based tools inform the auditor’s risk assessment by providing different perspectives, exposing previously unidentified relationships that may reveal new risks, and providing more information to be used when assessing risks. – However, when performing certain risk assessment procedures these tools do not diminish the importance of addressing other requirements related to risk assessment that do not necessarily lend themselves to the use of tools • The audit evidence standard does not preclude the auditor from using technology-based tools to perform audit procedures more efficiently to obtain audit evidence 3
  • 4. CARLab Project Report DarkOwl (Darkweb Data Collector) B3 (Brazilian Stock Exchange) AB InBev (Brewing Company) Darknet market activity monitoring and auditing • Darknet market postings (Blog+Forum+Paste) • Data analysis • Textual analysis Machine driven market manipulative activity • Real-time Transactions (All transactions – B3) • Data analysis (Time Series+ML) Fraud detection model development • Investigation Report • Free Beer • Data analysis • ML
  • 5. RPA • P1: - automated selected substantive testings in the Employee Benefit Plan audits. This became Andrea's dissertation and we have some professional articles about it. • P2: - automated a type of confirmation procedure. The paper is published in IJAIS. • P3: - automated selected processes in audit planning of Single Audits. Chanta and Abby are in the process of paper revision. • P4: We automated a mundane task in the real estate audits. After going through challenges of automation within virtual machines and dealing with an audit software that is not automation-friendly, we are able to automate a process that usually takes 15-20 min to 5 min. P4 is conducting tests now. • P5. Potentially automate an audit documentation procedure that involves moving data from word documents to a cloud-based internal audit software. Now we are waiting for documentation and data. (new phd students, Fangbing and Lanxin, will be in this project) • P6: Potentially automate an administration task for auditors. We are in the process of discussing potential solutions. (new phd students, Fangbing and Lanxin will be in this project)
  • 6. Continuous Monitoring and Audit Methodology for Medication Procurement Wenru Wang – Rutgers University Miklos A. Vasarhelyi – Rutgers University June 15, 2020
  • 7. Overview • Prefeitura Rio de Janeiro • 30,000+ Medication procurement data, 2017 – 2019 • Audit analytics for data preprocessing • Continuous monitoring and audit system for exception and anomaly detections 7
  • 8. 8
  • 9. 9
  • 10. 10
  • 11. COVID-19 Procurement • What has happened (descriptive analytics) • What will happen (predictive analytics) • What is the optimized solution (prescriptive analytics). • Data cleaning – Text mining, machine learning. 11
  • 12. GASB Post-Implementation Review Project Ben Yoon (Ben Yoon, Kathy Wei, Huaxia Li, Prof. Kevin Moffitt, Prof. Miklos Vasarhelyi, and Prof. Irfan Bora) June 2020
  • 13. • Are pensions safe?  In 2012, the GASB announced the pension standards for more transparent reporting (No. 67 and 68). Background
  • 14. • In 2012, the GASB announced the pension standards for more transparent reporting (No. 67 and 68). • Are all the entities following the GASB’s new pension standards? - It would be useful if the GASB can monitor the CAFRs. - But there are challenges: 1) The CAFR reports are PDF documents and long (100-300 pages). 2) Different CAFRs uses different formats. 3) CAFRs are scattered in the Internet. Project objective
  • 15. • This project consists of 4 steps. Collect CAFRs Convert CAFRs Analyze CAFRs (117 pre-defined items) Create reports • Rutgers has conducted initial pilot tests. - Step1: Collecting CAFRs from multiple repositories - Step2: Converting PDF documents - Step3: Extracting items from the CAFRs - Step4: Report with Excel format 4 steps of this project
  • 16. Converting PDF • Conversion into MS-Excel format • Illustrative example
  • 18. Continuous Intelligent Pandemic Monitoring (CIPM) 18 Presented by: Huijue Kelly Duan
  • 19. Background 19 • With the current outbreak of COVID-19 pandemic, authorities are struggling for accurate and timely information in order to control the spread of the epidemic and provide adequate instructions to the communities. • The fundamental issue is that the key metrics used to guide policy and action are dimensionally incorrect for a multitude of reasons – The number of contaminated people – Hospitalizations and heath cases – The number of people who are asymptomatic • Tremendous filtering on who gets tested; lacking in sufficient test kits
  • 20. 20
  • 21. Research Objectives 21 • Use measurement science (accounting), assurance science (auditing) to examine the situation • Apply AI-based predictive analytics to epidemic research • Accounting methodologies + machine learning algorithms – Continuous Monitoring – Multidimensional Audit Data Selection (MADS) – Machine learning and artificial neural networks • This study aims to – the augment of information quality and timeliness – the provision of adequate policy
  • 22. Framework 22 Data Collection • Establish a timely repository database of relevant exogenous and endogenous data sources Office announcement, social media posts, personal GPS data, Google flu trend, fever data based on thermometer reading apps, medical supplies purchase amount, economic related data, etc. Model Construction • Create a systematic and continuous COVID-19 monitoring model by using different epidemic models and machine learning algorithms  Classic Epidemic Models (SIR, SEIR, separable-temporal exponential-family random graph models)  AI predictions (SVM, XGBoost, Neural Network models)  Economic Impact Alerts • Incorporate audit risk assessment to establish an alert system Action Recommendations • Incorporate the knowledge obtained from different analysis to provide different levels of preventive policies and strategies regarding the pandemic, economics, as well as medical resources related recommendations.
  • 23. 23 Figure 1:Utilizing the SIR model to predict the total number of confirmed cases in United States; and the inflection point after the outbreak (This model does not consider the exogenous variables) Figure 2: simulating the impacts of different social distancing policies on infected cases assuming the total number of population is equal to 1000 (This model does not consider the exogenous variables)
  • 24. Innovation and Strategic Advantages • Following the accounting frameworks, this study aims to establish a continuous monitoring system for COVID-19 – The continuous monitoring and alert activation process is close to real- time, which enables earlier reaction to the signals – The monitoring activities are continuous, which helps preventing future outbreaks • The model uses Internet of Things (IoT) to gather the relevant exogenous data to perform comprehensive data analytics • Depending on the specific contingencies, action recommendations on quarantine and economy support will be predictively and automatically provided 24
  • 25. Conclusions • We Have new leadership • Many organizations are jumping into the fray • We need to deal better with the bureaucratic challenges of Rutgers • COVID makes us more important but creates many challenges • Our teaching mission is becoming more important • Many opportunities are available • WE NEED YOUR ADVICE