data Testing for Variations in Audited and Disclosed Financial Statement Information
- Peter Johnson
- Dec 13, 2023
- 3 min read
This experiment was quite memorable. It started out as an attempt to uncover any discrepancies that could be used for trading, but eventually changed its focus to uncover financial irregularities with the process of accounting forensics. The person who conducted this research went on to found a FinTech business that, judging from what I can tell, is still going strong.
This experiment seeks to investigate if it is feasible to identify potential red flags from a firm's openly accessible information, such as its financial declarations, corporate measures notices and other news outlets (e.g. conversation with high-ranking management, news bulletins, or stock analyst predictions). Such red flags might be exploited by wrongdoers to carry out a shady short plan against the firm.
Companies, particularly public listed companies, generate a substantial amount of data as part of their disclosure commitments. The necessity to produce returns on equity for their shareholders entails a constant drive to put their best face forward in many cases. This blend of factors leads to both intended (for instance, aggressive or excessively upbeat accounting practices which skirts the blurry area) and inadvertent (for instance, the manner in which financial data is presented may give interested parties the impression that the firm might be concealing certain details) representation of data in publicly available datasets.
The most frequent way in which unintended disclosure is acted on by persons of interest is through a public and contentious short selling activity conducted by traders. These traders make their opinions known on the weak points of the company, widely publicizing them and profiting from the resulting price fluctuation.
Besides those with more sinister motives, there are others with more legitimate and harmless reasons to find out such information.
It was determined by FinTech that the financial statement, whether public or private, is likely to be the origin of intentional or unintended camouflage. Through this, analysts have the greatest influence when attempting to showcase the monetary status of the company.
"Earning smoothing" is a common type of intentional masking, during which a company will spread the announcement of its earnings over multiple quarters in an effort to appear as though it has a consistent and predictable cash flow.
Earning smoothing results in a striking level of uniformity in the company's cash flow that may not be readily apparent to the human eye but can be identified through a comparison of statistical trends of firms in the same industry. Specifically, an unwavering statistical pattern could be a sign of earning smoothing.
If the experiment is successful, it could result in a new method of market monitoring, which allows stakeholders to keep a constant watch for the possibility of adverse events (e.g. early signs of corporate insolvency, which could be used by short sellers). This could offer further protection for companies from unscrupulous investors.
This can provide external auditors with an independent means of quantifying their intuition that something may be wrong, with the technology helping to direct the external auditor in looking at the matter from a particular perspective.
If investors can successfully incorporate this approach into their entire collection of holdings, it has the potential to reveal the dependability of the companies’ financial wellbeing, as well as provide a more accurate depiction of if a portfolio company is unfairly receiving a bad reputation.
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