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Rice University research finds market outliers at risk of misreporting

Research shows that some corporate executives skew earnings to influence the market and inflate share price. Photo via Pexels

Say a company called CoolConsumerGoodsCo has just released its quarterly earnings report, revealing significantly higher profits than its consumer goods industry counterparts.

That result might spur analysts to slap a buy rating on the stock and investors to snap up shares. In an ideal world, the market wouldn't have to consider the possibility that the numbers aren't legit — but then again, it's not an ideal world. (Enron, anyone?)

Rice Business professors Brian R. Rountree and Shiva Sivaramakrishnan, along with Andrew B. Jackson at UNSW in Australia, studied what makes business leaders more likely to engage in fraudulent earnings reporting. Specifically, they focused on the relationship between this kind of misrepresentation and the degree to which a company's earnings are in line with the rest of its industry — a variable the researchers term "co-movements."

Many people are familiar with a similar variable, calculated using stock returns often referred to as a company's beta. The authors adapted the stock return beta to corporate earnings to see how a company's earnings move with earnings at the industry level.

The researchers hypothesized that the less in sync a company's earnings are with its industry, the higher the chance a company's leaders will manipulate earnings reports. They started with the well-accepted premise that corporations try to skew earnings reports to influence the market. The primary motive is typically to raise the company's stock price, as when an executive tries to "choose a level of bias" that balances potential fallout of getting caught against the benefits of a higher stock price.

To test their prediction, the professors analyzed a sample of enforcement actions taken by the U.S. Securities and Exchange Commission against companies for problematic financial reporting from 1970 to 2011 — although they noted that given the SEC's limited resources, the number of enforcement actions probably underestimates the actual amount of earnings manipulation in the market.

Their analysis revealed that firms with low earnings co-movements (meaning their earnings were out of sync with industry peers) were more likely to be accused by the SEC of reporting misdeeds. They concluded that the degree of earnings co-movement determines the probability of earnings manipulation. Put another way, earnings co-movements are a "causal factor" in the chances of earnings manipulations — and to a significant degree. The researchers found that firms who don't co-move with the market are more than 50 percent more likely to face an SEC enforcement action, compared with firms who are perfectly aligned with the market.

The researchers drilled deeper into the data to study whether the odds changed depending on the industry, since past research has indicated that the amount of competition in an industry works to constrain misreporting. That premise seems to hold true, the researchers concluded. In industries with more competitive markets, the impact of low co-movement on earnings manipulation is moderated.

They also studied whether the age of a firm played a part in the likelihood of earnings manipulation. Newer firms often rely more on stock compensation, which could be a motive for manipulating earnings reporting to drive up share price. Indeed, younger firms were more susceptible to misreporting when their earnings were out of whack with the rest of the marketplace.

Every firm faces some risk of misreporting, however. Even for public companies under analyst scrutiny, low co-movement proved to be a driver of earnings manipulation. But companies known for conservative reporting tend to be less likely to exaggerate their earnings, in general; these firms typically recognize losses in a more timely manner, the professors found.

These findings suggest a number of future lines of research. For example: When do executives underreport earnings? And can analyzing patterns related to cash flow reporting help better isolate earnings manipulation?

In the meantime, if you come across a company like CoolConsumerGoodsCo with an earnings report that's widely out of sync with the rest of its industry, you might think twice before rushing to buy in.

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This article originally ran on Rice Business Wisdom and is based on research from Brian R. Rountree, an associate professor of accounting at the Jones Graduate School of Business at Rice University, and Shiva Sivaramakrishnan is the Henry Gardiner Symonds Professor of Accounting at Rice Business.

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Sieve Health is an AI cloud-based SaaS platform designed to automate and accelerate matching patients with clinical trials. Photo via Getty Images

On many occasions in her early career, Dr. Arti Bhosale, co-founder and CEO of Sieve Health, found herself frustrated with having to manually sift through thousands of digital files.

The documents, each containing the medical records of a patient seeking advanced treatment through a clinical trial, were always there to review — and there were always more to read.

Despite the tediousness of prescreening, which could take years, the idea of missing a patient and not giving them the opportunity to go through a potentially life-altering trial is what kept her going. The one she didn’t read could have slipped through the cracks and potentially not given someone care they needed.

“Those stories have stayed with me,” she says. “That’s why we developed Sieve.”

When standard health care is not an option, advances in medical treatment could be offered through clinical trials. But matching patients to those trials is one of the longest standing problems in the health care industry. Now with the use of new technology as of 2018, the solution to the bottleneck may be a new automated approach.

“Across the globe, more than 30 percent of clinical trials shut down as a result of not enrolling enough patients,” says Bhosale. “The remaining 80 percent never end up reaching their target enrollment and are shut down by the FDA.”

In 2020, Bhosale and her team developed Sieve Health, an AI cloud-based SaaS platform designed to automate and accelerate matching patients with clinical trials and increase access to clinical trials.

Sieve’s main goal is to reduce the administrative burden involved in matching enrollments, which in turn will accelerate the trial execution. They provide the matching for physicians, study sponsors and research sites to enhance operations for faster enrollment of the trials.

The technology mimics but automates the traditional enrollment process — reading medical notes and reviewing in the same way a human would.

“I would have loved to use something like this when I was on the front lines,” Bhosale says, who worked in clinical research for over 12 years. “Can you imagine going through 10,000 records manually? Some of the bigger hospitals have upwards of 100,000 records and you still have to manually review those charts to make sure that the patient is eligible for the trial. That process is called prescreening. It is painful.”

Because physicians wear many hats and have many clinical efforts on their plates, research tends to fall to the bottom of the to-do list. Finding 10-20 patients can take the research team on average 15-20 months to find those people — five of which end up unenrolling, she says.

“We have designed the platform so that the magic can happen in the background, and it allows the physician and research team to get a jumpstart,” she says.” They don’t have to worry about reviewing 10,000 records — they know what their efforts are going to be and will ensure that the entire database has been scanned.”

With Sieve, the team was able to help some commercial pilot programs have a curated data pool for their trials – cutting the administrative burden and time spent searching to less than a week.

Sieve is in early-stage start up mode and the commercial platform has been rolled out. Currently, the team is conducting commercial projects with different research sites and hospitals.

“Our focus now is seeing how many providers we can connect into this,” she says. “There’s a bigger pool out there who want to participate in research but don’t know where to start. That’s where Sieve is stepping in and enabling them to do this — partnering with those and other groups in the ecosystem to bring trials to wherever the physicians and the patients are.”

Arti Bhosale is the co-founder and CEO of Sieve Health. Photo courtesy of Sieve

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