Financial Risk Assessment of Enterprise Management Accounting Based on Association Rule Algorithm under the Background of Big Data

Yue, Huabo; Liao, Haojie; Liu, Dong; Chen, Ling

doi:10.1155/2022/8041623

Cited by 5 publications

(2 citation statements)

References 9 publications

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“…Accounting for receivables should become one of the key areas of analysis for enterprises seeking to carry out their activities effectively. In today's world, accounting is a key tool for achieving sustainable business intelligence (Lin et al, 2022). Receivables are usually checked according to the established audit scheme and is mandatory for every enterprise.…”

Section: Resultsmentioning

confidence: 99%

Untitled

2023

Scientific Bulletin of Mukachevo State University Series “Economics”

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The study of the influence of socio-demographic factors on the development of marketing communications is relevant, as it helps businesses to interact more effectively with the changing needs and behaviour of consumers in the context of global demographic changes. The purpose of this study was to investigate marketing communications that are preferred by different segments of the population. During the study, the following methods were used: analysis of statistical data, logical, graphic, and generalization methods. The study covers various categories of families and their influence on the consumption and perception of advertising. Large families, Muslims, gay people, and serial monogamists were found to have their own unique characteristics and preferences in advertising. Specifically, large families can be targeted by advertising aimed at children's goods and services, which can be encountered while walking with children. Muslim families who are allowed to have multiple wives may be interested in advertising that reflects the values and needs of this religious group. Gay people and serial monogamists may show a greater interest in branded clothing and higherpriced goods. Furthermore, the age and income level of the population influence the perception of advertising. Young and middle-aged people may be more trusting of advertising, while older people may show less trust in it. It was also found that advertising in the media and Internet advertising are effective channels of communication with various categories of the population. The results of the study can be used to adjust marketing strategies, from the correction of advertising messages to the selection of platforms for advertising promotion, which, considering the demographic characteristics of the target audience, can significantly increase the effectiveness of marketing activities and business profitability

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Section: Resultsmentioning

confidence: 99%

Untitled

2023

Scientific Bulletin of Mukachevo State University Series “Economics”

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“…It was used as a quality control tool in the commitment review stage and to analyze variables that affect the probability of obtaining a qualified opinion. Reference [ 4 ] constructed a multicategory audit opinion prediction model based on the back propagation (BP) neural network method and tested it. Reference [ 5 ] used multiple financial indicators as eigenvalues of modeling data for the four types of audit opinions issued by companies and established a multicategory audit opinion prediction model based on error correction output coding and support vector machine (SVM).…”

Section: Introductionmentioning

confidence: 99%

Intelligent Financial Auditing Model Based on Deep Learning

Xiao-feng

Zhu

2022

Computational Intelligence and Neuroscience

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The entire auditing process is complicated and tedious and requires a lot of human resources. Therefore, the intelligent development of auditing is the general trend. In order to improve the audit quality, this paper establishes an intelligent financial audit model that can predict the audit opinion of the consolidated financial statements. This paper proposes an audit opinion prediction model based on the fusion of deep belief neural network (DBN) and long-short term memory (LSTM). First, an indicator system is established for audit opinions, and multiple financial parameters are used to describe possible audit opinions. On this basis, a DBN network is designed to complete deep feature extraction and used for LSTM training. According to the prediction model obtained by training, the subsequent audit opinion can be scientifically predicted. In the experiment, the method in this paper is tested based on financial audit related data sets and compared with the prediction results of traditional multilayer perceptron (MLP), convolutional neural network (CNN), and LSTM models. The results verify the validity and reliability of the model in this paper.

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