Integration of Audit Data Analysis and Mining Techniques into Aide

2006 ◽  
Author(s):  
Sushi Jajodia
Keyword(s):  
Data Analysis ◽  
Audit Data

Updating Audit Standard—Enabling Audit Data Analysis

2013 ◽  
Vol 27 (1) ◽  
pp. 325-331 ◽  
Author(s):  
William R. Titera
Keyword(s):  
Data Analysis ◽  
Audit Process ◽  
Private Company ◽  
Continuous Auditing ◽  
External Auditors ◽  
Financial Statement Audit ◽  
Audit Data ◽  
Depth Analysis ◽  
Audit Standard ◽  
Audit Standards

ABSTRACT This paper highlights the emerging role of data analysis on the financial statement audit and its value throughout the audit process, particularly in providing audit evidence. It raises the issue of needed revisions to the Audit Standards, whether for public or private company audits, and illustrates how certain of the current Audit Standards inhibit the external auditors' use of enhanced data analysis and continuous auditing techniques. While this whitepaper identifies a few audit standards that could be revised in light of current technological capabilities, it does not purport to address all needed revisions. Rather, it recommends that a more in-depth analysis be undertaken to develop needed guidance, as well as a list of recommended changes to the standards.

scholarly journals Research on Audit Data Analysis under the Background of Big Data

2021 ◽  
Vol 5 (3) ◽  
pp. 28-33
Author(s):  
Li Zhang
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Rapid Development ◽  
Social Economy ◽  
Urgent Problem ◽  
Cloud Data ◽  
Audit Data ◽  
Audit Technology ◽  
Operation Status ◽  
Data Audit

With the arrival of the era of big data, the audit thinking mode has been promoted to change. Under the influence of big data, audit will become an activity of continuous behavior. Through cloud data, the staff can control the operation status and risk assessment of the whole enterprise, timely analyze, control and respond to risks, and protect the enterprise to reduce risks. With the advent of the era of big data, audit data analysis is becoming more and more important. At the same time, a large amount of data analysis also brings challenges to auditors. Methods to deal and solve the challenges has become an urgent problem to be solved at present. This paper mainly studies the challenges and countermeasures brought by the changes of audit approaches and methods to audit data analysis under the background of big data, so as to continuously innovate and practice the improvement of audit technology and promote the healthy and rapid development of social economy.

scholarly journals Audit Data Analysis and Application Based on Correlation Analysis Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Jifan Chen ◽  
Muhammad Talha
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Correlation Analysis ◽  
Massive Data ◽  
Data Mining Algorithm ◽  
Accounting Data ◽  
Analysis Algorithm ◽  
Audit Data ◽  
Study Results ◽  
Depth Analysis

Traditional audit data analysis algorithms have many shortcomings, such as the lack of means to mine the hidden audit clues behind the data, the difficulty of finding increasingly hidden cheating techniques caused by the electronic and networked environment, and the inability to solve the quality defects of the audited data. Correlation analysis algorithm in data mining technology is an effective means to obtain knowledge from massive data, which can complete, muffle, clean, and reduce defective data and then can analyze massive data and obtain audit trails under the guidance of expert experience or analysts. Therefore, on the basis of summarizing and analyzing previous research works, this paper expounds the research status and significance of audit data analysis and application; elaborates the development background, current status, and future challenges of correlation analysis algorithm; introduces the methods and principles of data model and its conversion and audit model construction; conducts audit data collection and cleaning; implements audit data preprocessing and its algorithm description; performs audit data analysis based on correlation analysis algorithm; analyzes the hidden node activation value and audit rule extraction in correlation analysis algorithm; proposes the application of audit data based on correlation analysis algorithm; discusses the relationship between audit data quality and audit risk; and finally compares different data mining algorithms in audit data analysis. The findings demonstrate that by analyzing association rules, the correlation analysis algorithm can determine the significance of a huge quantity of audit data and characterise the degree to which linked events would occur concurrently or sequentially in a probabilistic manner. The correlation analysis algorithm first inputs the collected audit data through preprocessing module to filter out useless data and then organizes the obtained data into a format that can be recognized by data mining algorithm and executes the correlation analysis algorithm on the sorted data; finally, the obtained hidden data is divided into normal data and suspicious data by comparing it with the pattern in the rule base. The algorithm can conduct in-depth analysis and research on the company’s accounting vouchers, account books, and a large number of financial accounting data and other data of various natures in the company’s accounting vouchers; reveal its original characteristics and internal connections; and turn it into an audit. People need more direct and useful information. The study results of this paper provide a reference for further researches on audit data analysis and application based on correlation analysis algorithm.

scholarly journals Research on Audit Data Analysis and Decision Tree Algorithm for Benefit Distribution of Enterprise Financing Alliance

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Jie Bai ◽  
Tian He
Keyword(s):  
Data Analysis ◽  
Decision Tree ◽  
Data Cleaning ◽  
Analysis Method ◽  
Decision Tree Algorithm ◽  
Tree Algorithm ◽  
Average Accuracy ◽  
Audit Data ◽  
Data Collection Process ◽  
C4.5 Algorithm

When traditional methods analyze the audit data of enterprise financing alliance, there are some problems, such as long algorithm modeling time and low accuracy of interest distribution algorithm of enterprise financing alliance. Therefore, this paper proposes an analysis method of interest distribution of enterprise audit data financing alliance based on the decision tree algorithm. The audit data collection process of enterprise financing alliance is given, and the continuous attributes of audit data are discretized by the C4.5 algorithm. We perform enterprise financing alliance audit data analysis, remove inconsistencies from audit data through data cleaning, and finally realize enterprise financing alliance audit data analysis based on the improved C4.5 algorithm. The experimental results show that this method can shorten the modeling time and improve the accuracy of interest distribution algorithm of enterprise financing alliance. We achieved an average accuracy of 84.7% with the C4.5 algorithm while 84.35% with NBTree.

Microchemical imaging in biomedical research

1992 ◽  
Vol 50 (2) ◽  
pp. 1118-1119
Author(s):  
P. Ingram
Keyword(s):  
Data Analysis ◽  
Electron Probe ◽  
The Other ◽  
X Ray ◽  
Cell Element ◽  
Physiological Information ◽  
Functional States ◽  
Elemental Maps ◽  
Electron Energy Loss ◽  
Secondary Ion

It is well established that unique physiological information can be obtained by rapidly freezing cells in various functional states and analyzing the cell element content and distribution by electron probe x-ray microanalysis. (The other techniques of microanalysis that are amenable to imaging, such as electron energy loss spectroscopy, secondary ion mass spectroscopy, particle induced x-ray emission etc., are not addressed in this tutorial.) However, the usual processes of data acquisition are labor intensive and lengthy, requiring that x-ray counts be collected from individually selected regions of each cell in question and that data analysis be performed subsequent to data collection. A judicious combination of quantitative elemental maps and static raster probes adds not only an additional overall perception of what is occurring during a particular biological manipulation or event, but substantially increases data productivity. Recent advances in microcomputer instrumentation and software have made readily feasible the acquisition and processing of digital quantitative x-ray maps of one to several cells.

Perceptions of a Collaborative Professional Learning Program: Seeing the “Bigger Picture”

2020 ◽  
Vol 5 (1) ◽  
pp. 290-303
Author(s):  
P. Charlie Buckley ◽  
Kimberly A. Murza ◽  
Tami Cassel
Keyword(s):  
Data Analysis ◽  
Professional Learning ◽  
Social Communication ◽  
Special Educators ◽  
Service Providers ◽  
Integrative Approach ◽  
Theory Approach ◽  
Learning Program ◽  
Speech Language Pathologists ◽  
Related Service

Purpose The purpose of this study was to explore the perceptions of special education practitioners (i.e., speech-language pathologists, special educators, para-educators, and other related service providers) on their role as communication partners after participation in the Social Communication and Engagement Triad (Buckley et al., 2015 ) yearlong professional learning program. Method A qualitative approach using interviews and purposeful sampling was used. A total of 22 participants who completed participation in either Year 1 or Year 2 of the program were interviewed. Participants were speech-language pathologists, special educators, para-educators, and other related service providers. Using a grounded theory approach (Glaser & Strauss, 1967 ) to data analysis, open, axial, and selective coding procedures were followed. Results Three themes emerged from the data analysis and included engagement as the goal, role as a communication partner, and importance of collaboration. Conclusions Findings supported the notion that educators see the value of an integrative approach to service delivery, supporting students' social communication and engagement across the school day but also recognizing the challenges they face in making this a reality.

Communicative Performance of Adolescents with Severe Speech Impairment

1989 ◽  
Vol 54 (3) ◽  
pp. 403-421 ◽  
Author(s):  
Beth M. Dalton ◽  
Jan L. Bedrosian
Keyword(s):  
Data Analysis ◽  
Peer Interactions ◽  
Consistent Pattern ◽  
Clinical Implications ◽  
Speech Impairment ◽  
Communication Mode ◽  
Mode Function ◽  
Communicative Performance ◽  
Therapy Room ◽  
Communication Board

The communicative performance of 4 preoperational-level adolescents, using limited speech, gestures, and communication board techniques, was examined in a two-part investigation. In Part 1, each subject participated in an academic interaction with a teacher in a therapy room. Data were transcribed and coded for communication mode, function, and role. Two subjects were found to predominantly use the speech mode, while the remaining 2 predominantly used board and one other mode. The majority of productions consisted of responses to requests, and the initiator role was infrequently occupied. These findings were similar to those reported in previous investigations conducted in classroom settings. In Part 2, another examination of the communicative performance of these subjects was conducted in spontaneous interactions involving speaking and nonspeaking peers in a therapy room. Using the same data analysis procedures, gesture and speech modes predominated for 3 of the subjects in the nonspeaking peer interactions. The remaining subject exhibited minimal interaction. No consistent pattern of mode usage was exhibited across the speaking peer interactions. In the nonspeaking peer interactions, requests predominated. In contrast, a variety of communication functions was exhibited in the speaking peer interactions. Both the initiator and the maintainer roles were occupied in the majority of interactions. Pertinent variables and clinical implications are discussed.

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