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- All Subjects: Accounting
- All Subjects: artificial intelligence
- Creators: Chen, Yinong
The next question: What do these changes in the roles and responsibilities look like for the auditors of the future? Cognitive technology will assuredly present new issues for which humans will have to find solutions.
• How will humans be able to test the accuracy and completeness of the decisions derived by cognitive systems?
• If cognitive computing systems rely on supervised learning, what is the most effective way to train systems?
• How will cognitive computing fair in an industry that experiences ever-changing industry regulations?
• Will cognitive technology enhance the quality of audits?
In order to answer these questions and many more, I plan on examining how cognitive technologies evolved into their use today. Based on this historic trajectory, stakeholder interviews, and industry research, I will forecast what auditing jobs may look like in the near future taking into account rapid advances in cognitive computing.
The conclusions forecast a future in auditing that is much more accurate, timely, and pleasant. Cognitive technologies allow auditors to test entire populations of transactions, to tackle audit issues on a more continuous basis, to alleviate the overload of work that occurs after fiscal year-end, and to focus on client interaction.
Generating an astounding $110.7 billion annually in domestic revenue alone [1], the world of accounting is one deceptively lacking automation of its most business-critical processes. While accounting tools do exist for the common person, especially when it is time to pay their taxes, such innovations scarcely exist for many larger industrial tasks. Exceedingly common business events, such as Business Combinations, are surprisingly manual tasks despite their $1.1 trillion valuation in 2020 [2]. This work presents the twin accounting solutions TurboGAAP and TurboIFRS: an unprecedented leap into these murky waters in an attempt to automate and streamline these gigantic accounting tasks once entrusted only to teams of experienced accountants.
A first-to-market approach to a trillion-dollar problem, TurboGAAP and TurboIFRS are the answers for years of demands from the accounting sector that established corporations have never solved.
Generating an astounding $110.7 billion annually in domestic revenue alone [1], the world of accounting is one deceptively lacking automation of its most business-critical processes. While accounting tools do exist for the common person, especially when it is time to pay their taxes, such innovations scarcely exist for many larger industrial tasks. Exceedingly common business events, such as Business Combinations, are surprisingly manual tasks despite their $1.1 trillion valuation in 2020 [2]. This work presents the twin accounting solutions TurboGAAP and TurboIFRS: an unprecedented leap into these murky waters in an attempt to automate and streamline these gigantic accounting tasks once entrusted only to teams of experienced accountants.
A first-to-market approach to a trillion-dollar problem, TurboGAAP and TurboIFRS are the answers for years of demands from the accounting sector that established corporations have never solved.
"Generating an astounding $110.7 billion annually in domestic revenue alone [1], the world of accounting is one deceptively lacking automation of its most business-critical processes. While accounting tools do exist for the common person, especially when it is time to pay their taxes, such innovations scarcely exist for many larger industrial tasks. Exceedingly common business events, such as Business Combinations, are surprisingly manual tasks despite their $1.1 trillion valuation in 2020 [2]. This work presents the twin accounting solutions TurboGAAP and TurboIFRS: an unprecedented leap into these murky waters in an attempt to automate and streamline these gigantic accounting tasks once entrusted only to teams of experienced accountants.
A first-to-market approach to a trillion-dollar problem, TurboGAAP and TurboIFRS are the answers for years of demands from the accounting sector that established corporations have never solved."
In this dissertation, I propose a novel framework for performing semantic autograding, which analyzes student programs at a semantic level to help students learn with additional and systematic help. A general autograder is not practical for general programming languages, due to the flexibility of semantics. A practical autograder is possible in VIPLE, because of its simplified syntax and restricted options of semantics. The design of this autograder is based on the concept of theorem provers. To achieve this goal, I employ a modified version of Pi-Calculus to represent VIPLE programs and Hoare Logic to formalize program requirements. By building on the inference rules of Pi-Calculus and Hoare Logic, I am able to construct a theorem prover that can perform automated semantic analysis. Furthermore, building on this theorem prover enables me to develop a self-learning algorithm that can learn the conditions for a program’s correctness according to a given solution program.
uses an infrared camera to capture and detect the user’s face position and orient the
display accordingly. The second method utilizes gyroscopic and accelerometer data
as input to a machine learning model to classify correct and incorrect rotations.
Experiments show that these new methods achieve an overall success rate of 67%
for the first and 92% for the second which reaches a new high for this performance
category. The paper also discusses logistical and legal reasons for implementing this
feature into an end-user product from a business perspective. Lastly, the monetary
incentive behind a feature like irRotate in a consumer device and explore related
patents is discussed.
Moreover, most of these recommender systems suffer from the cold-start problems where insufficient data for new users or products results in reduced overall recommendation output. In the current study, we have built a recommender system to recommend movies to users. Biclustering algorithm is used to cluster the users and movies simultaneously at the beginning to generate explainable recommendations, and these biclusters are used to form a gridworld where Q-Learning is used to learn the policy to traverse through the grid. The reward function uses the Jaccard Index, which is a measure of common users between two biclusters. Demographic details of new users are used to generate recommendations that solve the cold-start problem too.
Lastly, the implemented algorithm is examined with a real-world dataset against the widely used recommendation algorithm and the performance for the cold-start cases.
In 2022, the revenue generated from accounting services hit an all-time high of 119.48 billion USD (“Accounting Services in the US - Market Size”, 2022). On top of this, research has shown that 45% of all accounting professionals would like to automate something about their workflow (Thomas, 2020). Indeed, a lot of bookkeeping accountancy has been phased out by simple automation. However, larger accounting tasks like business mergers still require a team of accountants despite being a largely iterative process. This project chronicles one such attempt at automating accounting events or transactions that are performed by businesses both large and small. With the help of accounting students Madeline Stolper and Heddie Liu we were able to build a fully-functioning website to automate accounting transactions. For this project, we used industry-standard software frameworks React and Express to build the site with dynamic accounting applications. These applications were built with reusable components, making the development of future applications very simple. We also leveraged cutting-edge technological solutions from Amazon Web Services to make the website available on the Internet with rapid response times. Lastly, we incorporated an agile approach to project management and communication, in order to create functionality in the most efficient and organized manner possible. On a large scale, something like this has never been attempted and TurboIFRS/GAAP represents a revolutionary leap in accounting automation.
In 2022, the revenue generated from accounting services hit an all-time high of 119.48 billion USD (“Accounting Services in the US - Market Size”, 2022). On top of this, research has shown that 45% of all accounting professionals would like to automate something about their workflow (Thomas, 2020). Indeed, a lot of bookkeeping accountancy has been phased out by simple automation. However, larger accounting tasks like business mergers still require a team of accountants despite being a largely iterative process. This project chronicles one such attempt at automating accounting events or transactions that are performed by businesses both large and small. With the help of accounting students Madeline Stolper and Heddie Liu we were able to build a fully-functioning website to automate accounting transactions. For this project, we used industry-standard software frameworks React and Express to build the site with dynamic accounting applications. These applications were built with reusable components, making the development of future applications very simple. We also leveraged cutting-edge technological solutions from Amazon Web Services to make the website available on the Internet with rapid response times. Lastly, we incorporated an agile approach to project management and communication, in order to create functionality in the most efficient and organized manner possible. On a large scale, something like this has never been attempted and TurboIFRS/GAAP represents a revolutionary leap in accounting automation.