ACC 331 – Course Individual Project
REQUIRED:
1. Select two of the topics listed below and write an executive summary (between 200 to 400 words; Times Roman font, 11 to 12 points, single or 1.5 space) on each topic selected.
In your summary, please include both why the topic is important and why anyone should care about the topic. (Write only two executive summaries.)
Write two executive summaries and choose one of the two topics to prepare 3-5 slides.
INDIVIDUAL SELECTION:
Write an executive summary (between 200 to 400 words; Times Roman font, 11 to 12 points, single or 1.5 space) on two of topics listed below. In your summary, you must include both why the topic is important and why anyone should care about the topic.
Topics:
Review the following topics:
► American Institute of Certified Public Accountants data standards
► Artificial intelligence (software of robots)
► Augmented reality and virtual reality
► Big data ethics (including data privacy)
► Big data storage (e.g., data lakes)
► Blockchain (internet of value) and cryptocurrencies (bitcoin)
► Cloud computing, including infrastructure as a service (IAAS), software as a service (SAAS) and platform as a service (PAAS)
► Cognitive computing
► Continuous auditing and monitoring
► Cybersecurity
► Unusual data and analytics
► Drones
► Internet of Things (IOT), Internet of People and sensors
► Machine learning
► Natural language generation
► Natural language processing, natural language generation, text analytics and sentiment analysis, chat apps (conversational bots and virtual agents)
► Neural networks, deep neural networks and deep learning
► Robotic process automation (RPA), automation, and man and machine
► Speech recognition
If there is another emerging technology that you believe would be appropriate, please recommend it to Prof. Askew is it can be included as an option for you.
Links for the topics are listed below.
► AICPA data standards: https://www.aicpa.org/interestareas/frc/assuranceadvisoryservices/pages/auditdatastandards.aspx
► Artificial intelligence:
– EY resources:
► “AI: welcome to the machines”
http://www.ey.com/gl/en/services/assurance/ey-reporting-ai-welcome-to-the-machines?utm_source=Weekly%20Chronicle&utm_medium=Email&utm_campaign=Reporting%3A%20June%202017
– Other resources:
► Forbes website: “Top 10 Hot Artificial Intelligence (AI) Technologies” https://www.forbes.com/sites/gilpress/2017/01/23/top-10-hot-artificial-intelligence-ai-technologies/#3f6199691928
► Entrepreneur website: “4 AI Technologies Impacting Business Operations Right Now” https://www.entrepreneur.com/article/284838
► Journal of Accountancy website: “Rethinking the audit” http://www.journalofaccountancy.com/issues/2017/apr/rethinking-the-audit.html
► Augmented reality and virtual reality:
– Other resources:
► Forbes website: “How Virtual Reality Will Impact Business In The Next Five Years”
https://www.forbes.com/sites/forbestechcouncil/2016/07/22/how-virtual-reality-will-impact-businesses-in-the-next-five-years/#3919e0de2607Big data ethics (including data privacy):
– Forbes website: “What’s Up with Big Data Ethics?” https://www.forbes.com/sites/oreillymedia/2014/03/28/whats-up-with-big-data-ethics/#274699743591
– Journal of Accountancy website: “Why accountants should own Big Data” http://www.journalofaccountancy.com/issues/2013/nov/20138590.html
– Association of Chartered Certified Accountants and Institute of Management Accountants: “Big data: Its power and perils”
http://www.accaglobal.com/bigdata
► Big data storage (e.g., data lakes):
– Computer Weekly.com website: “Big data storage: Defining big data and the type of storage it needs”
– http://www.computerweekly.com/podcast/Big-data-storage-Defining-big-data-and-the-type-of-storage-it-needs
– Forbes website: “Why Data Lakes Are Evil” https://www.forbes.com/sites/danwoods/2016/08/26/why-data-lakes-are-evil/#71b07a454f73
► Blockchain (internet of value) and cryptocurrencies (bitcoin):
– EY resources:
► “The next big thing: Blockchain”
► “Blockchain and the future of audit”
► “Blockchain’s potential win for the energy sector”
► Blockchain technology as a platform for digitization: implications for the insurance industry
► “Blockchain reaction: Tech plans for critical mass”
► “Building blocks of the future”
– Implementing blockchains and distributed infrastructure
– Other sources:
► Bitcoin Magazine website: Blockchain Commercialization: Real World Applications Get Real https://bitcoinmagazine.com/articles/blockchain-commercialization-real-world-applications-get-real/
► strategy+business website: “A Strategist’s Guide to Blockchain”
http://www.strategy-business.com/article/A-Strategists-Guide-to-Blockchain
► Thompson Reuters website: “Blockchain, Accounting and Audit: What Accountants Need to Know”
https://tax.thomsonreuters.com/blog/business/technology/blockchain-accounting-and-audit-what-accountants-need-to-know/
► economia website: “How blockchain will impact accountants and auditors”
http://economia.icaew.com/features/july-2016/how-blockchain-will-impact-accountants-and-auditors
► SF Strategic Finance website: “Get Ready for Blockchain”
http://sfmagazine.com/post-entry/january-2017-get-ready-for-blockchain/
► NASDAQ.com website: “Blockchain Promises Accountants, Auditors and Their Clients Better Data Sooner And Cheaper”
http://www.nasdaq.com/article/blockchain-promises-accountants-auditors-and-their-clients-better-data-sooner-and-cheaper-cm726746
► Innovation Enterprise website: “Will Blockchain Render Accountants Irrelevant?” https://channels.theinnovationenterprise.com/articles/will-blockchain-render-accountants-irrelevant
► Cloud computing, including infrastructure as a service (IAAS), software as a service (SAAS) and platform as a service (PAAS):
– EY resources:
► “Cloud taxation issues and impacts”
► “Worldwide digital tax guide”
http://www.ey.com/gl/en/services/tax/ey-digital-tax-guide
► “Governing the cloud”
► Cognitive computing:
– Forbes website: “What Everyone Should Know About Cognitive Computing” https://www.forbes.com/sites/bernardmarr/2016/03/23/what-everyone-should-know-about-cognitive-computing/#6be118675088
► Continuous auditing and monitoring:
– AICPA website: “The Current State of Continuous Auditing and Continuous Monitoring” https://www.aicpa.org/InterestAreas/FRC/AssuranceAdvisoryServices/DownloadableDocuments/Whitepaper_Current-State-Continuous-Auditing-Monitoring.pdf
► Cybersecurity:
– EY resources:
► “How is ransomware causing threats to organizations?”
► “Cybersecurity and the Internet of Things”
► “The state of cyber resilience”
– Center for Audit Quality website: “The CPA’s Role in Addressing Cybersecurity Risk” http://thecaq.org/cpas-role-addressing-cybersecurity-risk
► Dark data and dark analytics:
– Gartner website: “Dark Data”
http://www.gartner.com/it-glossary/dark-data
– Bloomberg website: “Dark Data Management: The Next Frontier in Information Governance” https://www.bloomberg.com/company/announcements/dark-data-management-next-frontier-information-governance/
► Drones:
– EY website: “EY scaling the use of drones in the audit process”
► Internet of Things (IOT), Internet of People and sensors:
– EY resources:
► “Human-machine interactions that unlock possibilities in media and entertainment”
► “Helping demystify Industrie 4.0 and IoT: an intro to the world of machine-to-machine talk”
► “The power of the IoT: how oil and gas CIOs can introduce intelligence into the supply chain”
– Other resources:
► AICPA website: “How the Internet of Things will impact CPAs” http://www.aicpastore.com/Content/media/PRODUCER_CONTENT/Newsletters/Articles_2015/CPA/MAY/impact_CPAs.jsp
► Harvard Business Review website: “How People Are Actually Using the Internet of Things” https://hbr.org/2015/10/how-people-are-actually-using-the-internet-of-things
► NPR website: “The Internet Of Things Is Becoming More Difficult To Escape” http://www.npr.org/sections/alltechconsidered/2017/06/06/531747037/the-internet-of-things-is-becoming-more-difficult-to-escape
► The Guardian website: “Forget the internet of things – we need an internet of people” https://www.theguardian.com/technology/2015/may/25/forget-internet-of-things-people
► Machine learning:
– AccountingWEB website: “The State of AI, Machine Learning, and Accounting” https://www.accountingweb.com/technology/trends/the-state-of-ai-machine-learning-and-accounting
► Natural language processing and natural language generation, text analytics, and sentiment analysis and chat apps (conversational bots and virtual agents):
– EY resources:
► “Your customers are trying to text you something. Are you listening?”
– Harvard Business Review website: “Sentiment Analysis Can Do More than Prevent Fraud and Turnover”
https://hbr.org/2016/01/sentiment-analysis-can-do-more-than-prevent-fraud-and-turnover
– ACCA website: Text analytics mines corporate reports for fraud http://www.accaglobal.com/us/en/member/member/accounting-business/2016/02/insights/text-analytics.html
► Neural networks, deep neural networks and deep learning:
– Forbes website: “Why Is Deep Learning Is Suddenly Changing Your Life”
– http://fortune.com/ai-artificial-intelligence-deep-machine-learning/
► Robotic process automation (RPA), automation, and man and machine
– EY resources:
► “What is Robotic Process Automation?” http://players.brightcove.net/1066292269001/BJmSlObm_default/index.html?videoId=5206910658001
► Robotic process automation: automation’s next frontier :
https://assets.ey.com/content/dam/ey-sites/ey-com/en_gl/topics/digital/ey-robotic-process-automation.pdf
► “Will robots change the future of outsourcing? Is Robotic Process Automation (RPA) the new Business Process Outsourcing (BPO)?”
► https://humanengineers.com/will-robots-change-future-outsourcing-robotic-process-automation-rpa-new-business-process-outsourcing-bpo/
► “Get ready for robots”
http://www.ey.com/gl/en/industries/financial-services/insurance/ey-get-ready-for-robots
► Robotic process automation in the Finance function of the future https://blog.dataart.com/how-robotic-process-automation-is-transforming-financial-services#:~:text=There%20is%20a%20great%20promise%20for%20robotic%20process,specifically%20in%20labor-intensive%20areas%20of%20a%20business%E2%80%99s%20process.
► “Tax workers and robots: teammates, not enemies” https://betterworkingworld.ey.com/digital/tax-workers-and-robots-teammates-not-enemies
► “Analytics and intuition: Why health care big data needs both” https://betterworkingworld.ey.com/better-questions/analytics-intuition-healthcare-big-data
– Other resources:
► Forbes website: Looking Ahead: How Automation Will Change The Accounting Industry https://www.forbes.com/sites/forbesfinancecouncil/2017/05/16/looking-ahead-how-automation-will-change-the-accounting-industry/#320dcb4e7f30
► https://www.youtube.com/watch?v=tnUSN2JLDOI
– EY resources:
► Audio analytics: new opportunities in litigation and investigation
https://www.ey.com/en_gl/webcasts/2021/04/how-digital-forensics-is-defined-in-litigation-and-investigation
Written Assignment Evaluation Rubric
Criteria Level 4 Level 3 Level 2 Level 1 Unacceptable
Percentage 90 – 100% 80 – 89% 70 – 79% 60 – 69% < 60%
Assignment Student completely fulfills assignment requirements
-Process Complete
-Due Dates Met
-Final Copy Submitted
-Format Correct
-Works Cited Incl. Student completely fulfills assignment requirements Student partially fulfills assignment requirements (almost all) Student partially fulfills assignment requirements (almost all) Student’s work in no way relates to assignment
Thesis
Student’s thesis is a clear, arguable, well developed, and definitive statement of position. It answers a why or how question Student’s thesis is a clear and arguable statement of position that answers a why or how question Student’s thesis is a clear, arguable statement of position Student’s thesis is an outline of points; it is not an arguable statement of position Student’s work does not have a thesis
Development Student’s paper demonstrates a logical, mature, and thorough development of points that support the thesis Student’s paper demonstrates adequate development of points that support the thesis Student’s paper demonstrates an adequate development of points that support the thesis Student’s paper presents a superficial development of points, many of which do not support the thesis Student’s paper does not present any evidence of development of points that support the thesis
Evidence:
Analysis
Synthesis Student presents relevant and fully analyzed textual evidence to support the thesis following the evidence formula-16-17pts.
Student synthesizes textual evidence and points back to thesis statement Student presents relevant and adequately analyzed textual evidence to support the thesis-14pts.
Student makes an attempt at synthesis Student presents relevant and partially analyzed textual evidence to support the thesis-13pts.
Student makes an attempt at synthesis Student’s textual evidence is irrelevant and is not analyzed-11pts.
Student makes no attempt at synthesis Student provides no textual evidence to support the thesis—under 11 pts.
Student makes no attempt at synthesis
Opposition/
Refutation Student clearly and fully explains opposition and persuasively refutes it Student explains opposition and gives refutation Student explains opposition and gives refutation Student does not include op./ref. in paper Student does not include op./ref. in paper
Citation Student follows citation format with meticulous care. Includes proper footnoting technique, along with a complete works cited list. Student follows citation format with care. Includes proper footnoting technique, along with a complete works cited list. Student follows citation format with meticulous care. Includes proper technique, along with a partial/mediocre works cited list. Student does not follow citation format. Does not include proper footnoting technique, works cited list is missing. Incomplete or Missing
Mechanics
Sentence structure is correct. Punctuation and capitalization are correct. Sentence structure is generally correct. Some awkward sentences do appear. 1 or 2 errors in punctuation and/or capitalization. Work contains structural weaknesses and grammatical errors. There are 3 or 4 errors in punctuation and/or capitalization. Work contains multiple incorrect sentence structures.
4 or more errors in punctuation and/or capitalization. Too many errors – more than 7 exist.
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