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Cabarle, C (2018)

Using Benford’s law to predict the risk of financial statement fraud in equity crowd funding offerings

Proceedings of 2018 Engaged management scholarship conference, Philadelphia, PA..

ISSN/ISBN: Not available at this time. DOI: 10.2139/ssrn.3240900



Abstract: Purpose – This research will use Benford’s Law to identify high and low fraud risk in equity crowdfunders’ financial statements provided to investors. I also test whether nonconformity to Benford’s Law is more likely in startups, firms with annual losses reported, or related to the offer size, which determines the level of assurance and disclosure requirements. Design/methodology/approach – I identify anomalies in equity crowdfunding offerings’ financial statements that diverge from Benford’s Law. I use the Chi-square and Kolmogorov-Smirnoff (KS) statistics to determine which noncompliant statements diverge to the degree that indicates the likelihood of presence of fraud in the statements. I use the Mean Absolute Deviation (MAD) statistic to identify subgroups that have a greater likelihood of fraud risk. Additionally, I compare the KS statistic and MAD statistic of divergent equity crowdfunding firms in the study to other public companies. Findings – Regulation Crowdfunding firms are more at risk for fraudulent financial reporting than other public firms. Startups are a higher fraud risk than growing or maturing companies and positive or break-even earnings are riskier than firm-years reporting losses. No specific funding tier is indicative of a higher or lower fraud risk, however, fraud risk is equally pervasive in all tiers. The implication of these findings is that it raises awareness that this mechanism is extremely risky and the investor protections embedded in the current regulations are not enough to keep the fraudsters at bay. Fraudulent filings are not prevented through mandated assurance and the appeal of high rewards by the equity crowdfunders outweighs the risk of detection. Originality/Value – Regulation Crowdfunding is intended to facilitate capital formation in startups and small business while trying to protect investors (Securities and Exchange Commission, 2016). Although much concern has been expressed about the dangers of investing in equity crowdfunding issues, there have been no other studies analyzing the initial filings of equity crowdfunding offers and there have been no fraud risk assessments conducted on these filings, including the use of audit data analytics (ADA). Audit data analytics have been shown to predict or detect financial statement fraud in large, public companies (Amiram et al., 2015; Nigrini, 2017a) and auditors commonly use Benford’s Law to assess the risk of financial statement fraud in their audits.


Bibtex:
@inProceedings {, AUTHOR = {Carla Cabarle}, TITLE = { Using Benford’s law to predict the risk of financial statement fraud in equity crowd funding offerings}, BOOKTITLE = {Proceedings of 2018 Engaged management scholarship conference, Philadelphia, PA.}, YEAR = {2018}, URL = {https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3240900}, DOI = {10.2139/ssrn.3240900}, }


Reference Type: Conference Paper

Subject Area(s): Accounting