Evidence map›Paper›PMID 35685167›Full record

ArticleComputational intelligence and neuroscience2022

Monitoring and Analysis of Venture Capital and Corporate Fraud Based on Deep Learning.

Ruijun Zhang, Lina Zheng

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Ruijun ZhangSchool of Business, Renmin University of China, Beijing 100872, China.
Lina ZhengSchool of Business, Renmin University of China, Beijing 100872, China.ORCID https://orcid.org/0000-0002-8242-0871

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the continuous expansion of global investment institutions, the development of the investment industry is gradually accelerating, but the risks behind the investment are also constantly increasing. Using the data of A-share companies in China's capital market from 2010 to 2019, this paper studies the impact of venture capital on corporate fraud. Empirical results show that venture capital holdings reduce the probability and frequency of corporate fraud. These findings remain robust after mitigating endogeneity using PSM, Heckman's two-step, one-step approach, suggesting a causal relationship between venture capital holdings and fraud reduction. Further research shows that the way venture capital holdings reduce corporate fraud is to suppress corporate fraud by improving the company's internal and external information environment. Furthermore, venture capital holdings play an important role in the governance of corporate disclosure fraud and operational fraud, but not in the governance of TMT fraud. In addition, the venture capital has better inhibitory effects on the supervision and governance of the fraud frequency of nonstate-owned enterprises compared with state-owned enterprises. The results of this research imply that venture capital shareholding plays an important role in preventing corporate fraud. This study contributes to the researches about the value-added role of venture capital and reveals the governance effect of venture capital on corporate fraud. Besides, it provides the theoretical evidence for capitals to better serve the real economy.

Indexed as

Deep LearningFraudIndustryInvestments

Identifiers

PMID35685167
PMCPMC9173969

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.