Identifying Financial Fraud in Corporate Earnings Reports: A Quantitative Perspective
/Recently, publicly listed companies have entered a period of intensive earnings report disclosures. Earnings report data is a key input for fundamental quantitative strategies. By analyzing financial statements, we can identify undervalued yet high-quality companies while also avoiding companies with potential financial “blow-ups.” These blow-ups typically fall into two categories:
Financial distress risk: Companies suffering from poor operational performance.
Financial fraud risk: Companies manipulating or falsifying financial statements to mislead investors.
Among these, financial fraud is often more concealed, requiring a strong accounting background to detect. In this article, we will explore several high-profile financial fraud cases both domestically and internationally. We will also introduce how Jasper Capital, through an in-depth understanding of accounting principles, has developed an automated tool—the “Earnings Blow-Up Detector”—to identify stocks with negative alpha risks.
Case 1: Luckin Coffee – A Sleight of Hand in Coffee Sales
In 2020, short-seller Muddy Waters Research published a report accusing Luckin Coffee of financial fraud. A few months later, Luckin admitted to inflating its revenue by $2.2 billion. As a result, its stock price plummeted by 75% in a single trading session.
How did Luckin commit fraud? Primarily, they artificially inflated both sales volume and unit prices. By altering the sequence of order numbers (e.g., changing consecutive numbers like 1, 2, 3… into a seemingly random sequence like 1, 3, 5, 6…), they created the illusion of higher order volume. Additionally, they inflated the unit price of each product in their financial reports.
In reality, due to extensive coupon distribution, the actual price per cup of coffee was only 46% of the original price, rather than the reported 55%. Luckin also fabricated sales transactions and exaggerated marketing expenses to balance its inflated revenues and costs, ensuring its fraudulent activities went undetected.
Through these manipulations, Luckin projected an image of rapid revenue growth while concealing its mounting losses. A closer examination of their financial statements from that period reveals discrepancies, such as a mismatch between revenue growth and store expansion, as well as a decline in inventory despite rising sales.
image from jasper.
Case 2: Kangmei Pharmaceutical – The “High Cash, High Debt” Deception
Kangmei Pharmaceutical’s financial fraud is one of the most infamous cases in China’s A-share market. Once considered a leading company in traditional Chinese medicine, Kangmei was found to have falsified various financial metrics over multiple years, including cash balances and revenue figures. The company was subsequently labeled “the biggest fraud in A-shares,” leading to a collapse in both its stock price and reputation.
Between 2016 and 2018, Kangmei inflated its reported revenue and operating profits. At the same time, it overstated assets such as cash balances, fixed assets, and construction-in-progress. Notably, in its 2018 semi-annual report, Kangmei falsely reported RMB 36.19 billion in cash holdings.
Kangmei employed multiple fraudulent techniques. Initially, it exaggerated cash balances to offset its fake revenue growth. Later, it inflated fixed assets and construction-in-progress to “absorb” the fictitious cash, creating a closed-loop fraud.
A fundamental accounting principle states: every debit entry must have a corresponding credit entry of equal value. For instance, if I borrow RMB 100 from a friend, my cash increases by RMB 100, but I also incur an equivalent liability of RMB 100.
In 2017, Kangmei’s uncorrected annual report showed cash holdings of RMB 34.15 billion while also having interest-bearing liabilities of RMB 24.48 billion. Under normal circumstances, a company with ample liquidity does not need to take on large-scale debt, as borrowing incurs unnecessary interest expenses. This anomaly—having both high cash reserves and high debt—is a clear red flag in financial accounting.
Building an "Earnings Blow-Up Detector" from a Quantitative Fundamental Perspective
As seen in the cases above, financial fraud comes in various forms, often hidden and difficult to detect. Different industries may use different fraudulent tactics to balance inflated revenues. For example:
Agriculture companies may use inventory manipulations.
Technology, Media, and Telecommunications (TMT) firms may inflate goodwill or intangible assets.
Even within the same industry, companies may adopt different methods based on their business strategies and customer bases.
However, one lie often leads to another. Due to the cross-validation of financial statements—across the balance sheet, income statement, cash flow statement, changes in equity statement, and footnotes—inflated revenue and profits usually come with other suspicious adjustments. Identifying these anomalies is the key entry point for quantitative models.
Jasper Capital’s quantitative fundamental research team, with expertise in both finance and technology, has developed a comprehensive earnings report evaluation system for A-share companies. Using big data and AI, the firm has built an automated financial statement analysis system that continuously monitors corporate earnings reports and flags potential financial manipulation.
Additionally, by analyzing financial distress, corporate governance issues, and other company-specific risk factors, we have developed an "Earnings Blow-Up Detector." This tool identifies stocks at risk of significant negative returns, enabling us to proactively avoid such stocks and significantly enhance the robustness of our quantitative models against financial fraud risks.
image from jasper.
Why Avoiding Financial Fraud is Critical for Quantitative Strategies
For market-wide stock selection models, including a company with fabricated financials in the investment universe is akin to planting a time bomb. Once the fraud is exposed, the entire portfolio’s performance suffers. Avoiding these financial “traps” is crucial for ensuring the long-term stability and success of a quantitative strategy.
Even when financial fraud appears seamless, experienced analysts can still spot inconsistencies in the underlying logic.
As the "New National Nine Guidelines" (新国九条) lower the thresholds for delisting due to financial fraud—shortening the required time frame and reducing the financial thresholds—China’s A-share market is expected to see stronger regulatory enforcement and a firmer foundation for corporate integrity.