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Keywords = auditors’ life cycle

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26 pages, 1102 KB  
Article
Auditors’ Life Cycle in Clients and Auditor Independence
by Emeka T. Nwaeze
J. Risk Financial Manag. 2025, 18(2), 55; https://doi.org/10.3390/jrfm18020055 - 26 Jan 2025
Viewed by 1593
Abstract
This study hypothesizes that, in client firms, audit teams or auditors go through life cycle phases—entry, adjustment, and recursion—that give rise to distinct patterns of independence across time. The life cycle paradigm depicts the auditors as facing pressures during [...] Read more.
This study hypothesizes that, in client firms, audit teams or auditors go through life cycle phases—entry, adjustment, and recursion—that give rise to distinct patterns of independence across time. The life cycle paradigm depicts the auditors as facing pressures during entry to adhere strongly to their professional mandate, including the strict exercise of independence. The result is tense auditor–client relations and an increased likelihood of auditor turnover during the entry phase. Auditors that gain entry will “loosen up” and adjust their stance on independence due to the reduced entry pressures. As a result, the adjustment phase will witness a decline in auditor–client disagreements and a lower likelihood of auditor turnover. Over protracted periods, the audit process becomes tightly structured and recursive; the repetitive nature of the processes leads to audit fatigue, less attention to the independence mandate, and greater reliance on clients. The phenomenon portends an even further decline in auditor–client tension and a diminished likelihood of auditor turnover. These predictions are tested using auditor turnovers following auditor–client disputes as surrogates for auditor independence. The results confirm the life cycle phenomena and show that the level of auditor independence peaks during the early years of the auditors’ tenure and declines afterwards. Full article
(This article belongs to the Special Issue Judgment and Decision-Making Research in Auditing)
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26 pages, 1482 KB  
Article
Prediction and Visualisation of SICONV Project Profiles Using Machine Learning
by Adriano de Oliveira Andrade, Leonardo Garcia Marques, Osvaldo Resende, Geraldo Andrade de Oliveira, Leandro Rodrigues da Silva Souza and Adriano Alves Pereira
Systems 2022, 10(6), 252; https://doi.org/10.3390/systems10060252 - 10 Dec 2022
Cited by 4 | Viewed by 2299
Abstract
Background: Inefficient use of public funds can have a negative impact on the lives of citizens. The development of machine learning-based technologies for data visualisation and prediction has opened the possibility of evaluating the accountability of publicly funded projects. Methods: This study describes [...] Read more.
Background: Inefficient use of public funds can have a negative impact on the lives of citizens. The development of machine learning-based technologies for data visualisation and prediction has opened the possibility of evaluating the accountability of publicly funded projects. Methods: This study describes the conception and evaluation of the architecture of a system that can be utilised for project profile definition and prediction. The system was used to analyse data from 20,942 System of Management of Agreements and Transfer Contracts (SICONV) projects in Brazil, which are government-funded projects. SICONV is a Brazilian Government initiative that records the entire life cycle of agreements, transfer contracts, and partnership terms, from proposal formalisation to final accountability. The projects were represented by seven variables, all of which were related to the timeline and budget of the project. Data statistics and clustering in a lower-dimensional space calculated using t-SNE were used to generate project profiles. Performance measures were used to test and compare several project-profile prediction models based on classifiers. Results: Data clustering was achieved, and ten project profiles were defined as a result. Among 25 prediction models, k-Nearest-Neighbor (kknn) was the one that yielded the highest accuracy (0.991±0.002). Conclusions: The system predicted SICONV project profiles accurately. This system can help auditors and citizens evaluate new and ongoing project profiles, identifying inappropriate public funding. Full article
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43 pages, 2467 KB  
Review
Fantastic Beasts: Blockchain Based Banking
by Dulani Jayasuriya Daluwathumullagamage and Alexandra Sims
J. Risk Financial Manag. 2021, 14(4), 170; https://doi.org/10.3390/jrfm14040170 - 9 Apr 2021
Cited by 20 | Viewed by 12103
Abstract
Blockchain is one of the primary digital technologies utilised in the finance industry with huge future potential. This study conducts a systematic literature review of a final sample of 407 prior literature from an initial set of 1979 records for the sample period [...] Read more.
Blockchain is one of the primary digital technologies utilised in the finance industry with huge future potential. This study conducts a systematic literature review of a final sample of 407 prior literature from an initial set of 1979 records for the sample period of 2013–2020 with regard to blockchain adoption in banking. This review is further supplemented by a machine learning based textual analysis that identifies key themes, trends, divergences and gaps between academic and practitioner led industry literature. Moreover, the study highlights present, future use cases, adoption barriers and misconceptions of blockchains in banking, especially given COVID-19. Furthermore, this study identifies behavioural, social, economic, regulatory and managerial implications of blockchain based banking. In addition, our study identifies the cross-industry potential of blockchains via banking, thus, linking much disconnected prior literature. Finally, we develop a blockchain adoption framework and an adoption life cycle for banking. This study would be of interest to academics, bankers, regulators, investors, auditors and other stakeholders in financial markets. Full article
(This article belongs to the Special Issue Advances in Banking and Finance)
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