Questões de Concurso Público CGE-PB 2024 para Auditor de Contas Públicas - Auditoria de Tecnologia da Informação

Foram encontradas 100 questões

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Q2387707
Inglês Interpretação de texto | Reading comprehension ,
Ano: 2024 Banca: FGV Órgão: CGE-PB Provas: FGV - 2024 - CGE-PB - Auditor de Contas Públicas - Auditoria Contábil e Finanças Públicas | FGV - 2024 - CGE-PB - Auditor de Contas Públicas - Auditoria Governamental | FGV - 2024 - CGE-PB - Auditor de Contas Públicas - Auditoria de Obras Públicas | FGV - 2024 - CGE-PB - Auditor de Contas Públicas - Auditoria de Tecnologia da Informação |
Q2387707 Inglês
Audit data analytics, machine learning, and full population testing


Technologies are evolving at an unprecedented pace and pose significant challenges and opportunities to companies and related parties, including the accounting profession. In today’s business environment, it is inevitable for companies to react quickly to changing conditions and markets. Many companies are seeking better ways to utilize emerging technologies to transform how they conduct business. We live in an age of information explosion, with technologies capable of making revolutionary changes in various industries and reshaping business models. At present, many companies view data as one of their most valuable assets. They amass an unprecedented amount of data from their daily business operation and strive to harness the power of data through analytics. Emerging technologies like robotic process automation, machine learning, and data analytics also impact the accounting profession. It is important for the profession to understand the impacts, opportunities, and challenges of these technologies.


Specifically, in audit and assurance areas, data analytics and machine learning will lead to many changes in the foreseeable future. Audit sampling is one such potential change. The use of sampling in audits has been criticized since it only provides a small snapshot of the entire population. To address this major issue, this study introduces the idea of applying audit data analytics and machine learning for full population testing through the concept of “audit-by-exception” and “exceptional exceptions.” In this way, the emphasis of audit work shifts from “transaction examination” to “exception examination” and prioritizes the exceptions based on different criteria. Consequently, auditors can assess the associated risk based on the entire population of the transactions and thus enhance the effectiveness and efficiency of the audit process.


Adapted from the introduction to a study published in: https://www.sciencedirect.com/science/article/pii/S240591882200006X
Based on the text, mark the statements below as TRUE (T) or FALSE (F):

( ) Many companies nowadays tend to overlook data gathering.
( ) The accounting profession has managed to resist the impact of technology.
( ) In the study mentioned by the text, full population testing is to be preferred to sampling.

The statements are, respectively:
Alternativas
Q2387708
Inglês Pronomes | Pronouns ,
Ano: 2024 Banca: FGV Órgão: CGE-PB Provas: FGV - 2024 - CGE-PB - Auditor de Contas Públicas - Auditoria Contábil e Finanças Públicas | FGV - 2024 - CGE-PB - Auditor de Contas Públicas - Auditoria Governamental | FGV - 2024 - CGE-PB - Auditor de Contas Públicas - Auditoria de Obras Públicas | FGV - 2024 - CGE-PB - Auditor de Contas Públicas - Auditoria de Tecnologia da Informação |
Q2387708 Inglês
Audit data analytics, machine learning, and full population testing


Technologies are evolving at an unprecedented pace and pose significant challenges and opportunities to companies and related parties, including the accounting profession. In today’s business environment, it is inevitable for companies to react quickly to changing conditions and markets. Many companies are seeking better ways to utilize emerging technologies to transform how they conduct business. We live in an age of information explosion, with technologies capable of making revolutionary changes in various industries and reshaping business models. At present, many companies view data as one of their most valuable assets. They amass an unprecedented amount of data from their daily business operation and strive to harness the power of data through analytics. Emerging technologies like robotic process automation, machine learning, and data analytics also impact the accounting profession. It is important for the profession to understand the impacts, opportunities, and challenges of these technologies.


Specifically, in audit and assurance areas, data analytics and machine learning will lead to many changes in the foreseeable future. Audit sampling is one such potential change. The use of sampling in audits has been criticized since it only provides a small snapshot of the entire population. To address this major issue, this study introduces the idea of applying audit data analytics and machine learning for full population testing through the concept of “audit-by-exception” and “exceptional exceptions.” In this way, the emphasis of audit work shifts from “transaction examination” to “exception examination” and prioritizes the exceptions based on different criteria. Consequently, auditors can assess the associated risk based on the entire population of the transactions and thus enhance the effectiveness and efficiency of the audit process.


Adapted from the introduction to a study published in: https://www.sciencedirect.com/science/article/pii/S240591882200006X
In “They amass” (1st paragraph), the pronoun refers to:
Alternativas
Q2387709
Inglês Palavras conectivas | Connective words , Preposições | Prepositions ,
Ano: 2024 Banca: FGV Órgão: CGE-PB Provas: FGV - 2024 - CGE-PB - Auditor de Contas Públicas - Auditoria Contábil e Finanças Públicas | FGV - 2024 - CGE-PB - Auditor de Contas Públicas - Auditoria Governamental | FGV - 2024 - CGE-PB - Auditor de Contas Públicas - Auditoria de Obras Públicas | FGV - 2024 - CGE-PB - Auditor de Contas Públicas - Auditoria de Tecnologia da Informação |
Q2387709 Inglês
Audit data analytics, machine learning, and full population testing


Technologies are evolving at an unprecedented pace and pose significant challenges and opportunities to companies and related parties, including the accounting profession. In today’s business environment, it is inevitable for companies to react quickly to changing conditions and markets. Many companies are seeking better ways to utilize emerging technologies to transform how they conduct business. We live in an age of information explosion, with technologies capable of making revolutionary changes in various industries and reshaping business models. At present, many companies view data as one of their most valuable assets. They amass an unprecedented amount of data from their daily business operation and strive to harness the power of data through analytics. Emerging technologies like robotic process automation, machine learning, and data analytics also impact the accounting profession. It is important for the profession to understand the impacts, opportunities, and challenges of these technologies.


Specifically, in audit and assurance areas, data analytics and machine learning will lead to many changes in the foreseeable future. Audit sampling is one such potential change. The use of sampling in audits has been criticized since it only provides a small snapshot of the entire population. To address this major issue, this study introduces the idea of applying audit data analytics and machine learning for full population testing through the concept of “audit-by-exception” and “exceptional exceptions.” In this way, the emphasis of audit work shifts from “transaction examination” to “exception examination” and prioritizes the exceptions based on different criteria. Consequently, auditors can assess the associated risk based on the entire population of the transactions and thus enhance the effectiveness and efficiency of the audit process.


Adapted from the introduction to a study published in: https://www.sciencedirect.com/science/article/pii/S240591882200006X
In the sentence “Emerging technologies like robotic process automation” (1st paragraph), “like” expresses:
Alternativas
Q2387710
Inglês Verbos | Verbs ,
Ano: 2024 Banca: FGV Órgão: CGE-PB Provas: FGV - 2024 - CGE-PB - Auditor de Contas Públicas - Auditoria Contábil e Finanças Públicas | FGV - 2024 - CGE-PB - Auditor de Contas Públicas - Auditoria Governamental | FGV - 2024 - CGE-PB - Auditor de Contas Públicas - Auditoria de Obras Públicas | FGV - 2024 - CGE-PB - Auditor de Contas Públicas - Auditoria de Tecnologia da Informação |
Q2387710 Inglês
Audit data analytics, machine learning, and full population testing


Technologies are evolving at an unprecedented pace and pose significant challenges and opportunities to companies and related parties, including the accounting profession. In today’s business environment, it is inevitable for companies to react quickly to changing conditions and markets. Many companies are seeking better ways to utilize emerging technologies to transform how they conduct business. We live in an age of information explosion, with technologies capable of making revolutionary changes in various industries and reshaping business models. At present, many companies view data as one of their most valuable assets. They amass an unprecedented amount of data from their daily business operation and strive to harness the power of data through analytics. Emerging technologies like robotic process automation, machine learning, and data analytics also impact the accounting profession. It is important for the profession to understand the impacts, opportunities, and challenges of these technologies.


Specifically, in audit and assurance areas, data analytics and machine learning will lead to many changes in the foreseeable future. Audit sampling is one such potential change. The use of sampling in audits has been criticized since it only provides a small snapshot of the entire population. To address this major issue, this study introduces the idea of applying audit data analytics and machine learning for full population testing through the concept of “audit-by-exception” and “exceptional exceptions.” In this way, the emphasis of audit work shifts from “transaction examination” to “exception examination” and prioritizes the exceptions based on different criteria. Consequently, auditors can assess the associated risk based on the entire population of the transactions and thus enhance the effectiveness and efficiency of the audit process.


Adapted from the introduction to a study published in: https://www.sciencedirect.com/science/article/pii/S240591882200006X
A “foreseeable future” (2nd paragraph) is one that:
Alternativas
Q2387711
Inglês Verbos | Verbs , Presente perfeito | Present perfect ,
Ano: 2024 Banca: FGV Órgão: CGE-PB Provas: FGV - 2024 - CGE-PB - Auditor de Contas Públicas - Auditoria Contábil e Finanças Públicas | FGV - 2024 - CGE-PB - Auditor de Contas Públicas - Auditoria Governamental | FGV - 2024 - CGE-PB - Auditor de Contas Públicas - Auditoria de Obras Públicas | FGV - 2024 - CGE-PB - Auditor de Contas Públicas - Auditoria de Tecnologia da Informação |
Q2387711 Inglês
Audit data analytics, machine learning, and full population testing


Technologies are evolving at an unprecedented pace and pose significant challenges and opportunities to companies and related parties, including the accounting profession. In today’s business environment, it is inevitable for companies to react quickly to changing conditions and markets. Many companies are seeking better ways to utilize emerging technologies to transform how they conduct business. We live in an age of information explosion, with technologies capable of making revolutionary changes in various industries and reshaping business models. At present, many companies view data as one of their most valuable assets. They amass an unprecedented amount of data from their daily business operation and strive to harness the power of data through analytics. Emerging technologies like robotic process automation, machine learning, and data analytics also impact the accounting profession. It is important for the profession to understand the impacts, opportunities, and challenges of these technologies.


Specifically, in audit and assurance areas, data analytics and machine learning will lead to many changes in the foreseeable future. Audit sampling is one such potential change. The use of sampling in audits has been criticized since it only provides a small snapshot of the entire population. To address this major issue, this study introduces the idea of applying audit data analytics and machine learning for full population testing through the concept of “audit-by-exception” and “exceptional exceptions.” In this way, the emphasis of audit work shifts from “transaction examination” to “exception examination” and prioritizes the exceptions based on different criteria. Consequently, auditors can assess the associated risk based on the entire population of the transactions and thus enhance the effectiveness and efficiency of the audit process.


Adapted from the introduction to a study published in: https://www.sciencedirect.com/science/article/pii/S240591882200006X
The verb form in “has been criticized” (2nd paragraph) is in the:
Alternativas
Respostas
16: C
17: D
18: E
19: B
20: D
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