(This article was updated on May 3, 2024 to add detail on Wirecard's short sellers, and more details behind Transparently.AI's findings on Wirecard's 2005, 2008, 2012 and 2018 financial statements.)
Psychologists tell us that we homo sapiens owe our evolutionary success to a culture of trust. Our ability to receive and believe information from others allows us to accumulate knowledge and, in the modern world, allows markets to flourish. It is a cornerstone of our civilization.
A culture of trust means that homo sapiens are an innately gullible species. Our instinctive desire to trust causes us to dismiss claims of fraud even when all evidence points to the contrary. Importantly, it explains why machines are more efficient at detecting fraud than humans.
Let’s consider an example to illustrate the gullibility problem: Wirecard. In this piece, we analyse how the Wirecard scandal unfolded, how the company got away with it, and how an AI fraud-detection system might have prevented it.
Table of contents
Wirecard: The beginning
In the 1990s, an Austrian businessman with a background in the porn industry builds a business to process wire transfers for internet porn. By the early 2000s, his business, built for the dial-up era, is struggling and cannot process credit cards. He needs an acquisition with better systems and access to credit cards or his business will die.
He negotiates with another payments business that can process credit cards. This company’s systems are not quite as advertised. Their key programmer, also Austrian and hired as a teenage hacker, caused a massive systems failure in 2000 after routing all of the company’s internet traffic to his own PC for reasons unknown. The acquisition target never recovers but rebuffs his offers.
In a stroke of luck, a burglary at the target’s office in 2002 brings it to insolvency. Our businessman buys the company and merges it with his own. He hires a consultant from KPMG, another Austrian, as the CEO. He keeps the company name, ‘Wirecard’, and keeps the hacker, who will become the COO in a few short years.
The rest of the Wirecard story is well known and is so intriguing that we cannot do it justice here. Those who like a good yarn should read the book. The full timeline is here, courtesy of the Financial Times.
The potted history is that under the new CEO, the company veers into online gambling. Some wags would say that this is a fertile field for payments since banks avoid gambling payments due to reputational risk, and for money laundering for those willing to circumvent national bans on online gaming.
Wirecard's global expansion
Global expansion requires capital. In 2005, Wirecard does a back-door listing on the Frankfurt exchange – a red flag. The owner subsequently sells all his shares – a larger red flag.
In 2006, Wirecard purchases a German bank, allowing it to issue cards under its own name and manage merchant money. The unusual merging of a banking and non-banking business muddies the numbers, forcing investors to rely on the company’s own ‘adjusted version’ of its accounts.
In 2010, the US government charges a German linked to Wirecard with money laundering. The prosecutor argues that Wirecard has laundered "at least" $1.5 billion of gambling proceeds. Wirecard stock plunges.
The company pivots to Asia, conducting a maze of roll-ups of Asian and Middle-eastern payments businesses in subsequent years. These businesses, located in dusty garages or paddy fields, are purchased for tens or hundreds of millions and become a key driver of Wirecard’s growth, now apparently enhanced by AI.
Within 12 years of the bank purchase, Wirecard has a larger market cap than Germany’s two largest banks and enters the Dax 30. Upon entry to the index of the country’s largest companies, Wirecard has no board committees, not even an audit committee.
Figure 1: Market value. Source: Bloomberg, Transparently.AI
Based on its early history alone, Wirecard should have provoked deep mistrust among investors and regulators. Subsequent revelations of money laundering and of the COO’s deep connection to Russian oligarchs, Russian organized crime and even Russian intelligence should perhaps also have aroused suspicion.
And yet, to the bitter end, this company was cheered as a national champion, constantly rated overweight or strong overweight by equity analysts, feted by investors, and staunchly defended and promoted by German regulators.
Wirecard is a classic example of homo sapiens’ gullibility.
Wirecard is a classic example of homo sapiens’ gullibility.
To be sure, the company had detractors over the years. Short-sellers repeatedly attacked the company. As early as 2008, for example, the head of a German shareholder association raised concerns about balance sheet irregularities.
Wirecard short sellers
Wirecard commissioned EY to undertake a special audit in response to the criticisms. The specific findings of this investigation were never fully disclosed to the public but the firm evidently found no evidence of material wrongdoing.
The German regulator subsequently charged two activist shareholders who made the allegations. EY became Wirecard's auditor and remained so or for the rest of the company's history.
From 2014 onwards, the FT began a long campaign against Wirecard , revealing increasingly damning evidence. In 2015, J Capital Research recommended shorting Wirecard's stock based on allegations that the company's Asian operations were much smaller than claimed. In a 2016 report, Zatarra Research detailed allegations of "widespread corruption and fraud", causing significant weakness in the share price, Once again BaFin, the German regulator, came to Wirecard's defense launching an investigation into possible market manipulation by the principals of Zatarra.
Wirecard hired a PR firm and private investigators to fend off its attackers and nothing stuck until the company finally admitted that €1.9 billion was “missing” from two Philippine bank accounts in June 2020.
Wirecard was arguably the most complex and multi-layered fraud operation of all time. It was a brazen high wire act, so interlaced with online gambling, organized crime, Russian oligarchs, and the shadowy world of intelligence that we may never fully understand the true extent of its wrongdoings.
The trial of Wirecard executives began in December 2022 and should eventually shed considerable light on the story.
Wirecard accounting fraud
The Wirecard fraud was unique. It combined accounting fraud with money laundering on an epic scale, meaning it simultaneously hid revenue and embezzled cash while also inflating its earnings.
Wirecard possessed the ideal attributes for accounting fraud:
- It engaged in millions of transactions across international borders using a web of escrow accounts and offshore affiliates, some of which appear to have been owned by officers of the company. This made it impossible for an external observer to track revenue and difficult for auditors to verify cash balances;
- It had non-existent margin on its legal business, making profits easy to manipulate;
- Its business activities were almost impossible to physically observe, making it difficult for an external observer to gauge the scale of activity undertaken within the firm;
- It was in a booming sector, meaning it could report exceptional growth without suspicion;
- Its accounts, being a mishmash of a banking and non-banking business clouded many of the red flags normally exposed by forensic accounting;
- It was seen as a national champion. Those who challenged the company were routinely investigated or even charged with market manipulation by German regulators. Being both a bank and a non-bank it crossed regulatory boundaries, making oversight difficult;
- Its operations were complex, making it difficult for an auditor to check if there really was cash in the bank.
Using AI to predict accounting fraud
We are often asked whether our AI-powered Manipulation Risk Analyzer (MRA) system works to predict manipulation and failure risk outside of the sample that we used in our testing.
There are several technical reasons why it does, and one very practical reason, which is that every fraud is unique.
Our machine is not trained on the same pattern that repeats over and over again. To be sure, certain events repeat, we rely on that, but they do so in diverse and complex ways. This complexity provides an incredibly rich foundation from which our system can learn.
Our system has taken learnings from 68,000 stocks with almost 700,000 stock-years of financial data, extending from 1994 through to 2024. There is virtually nothing out there that our system hasn’t seen before, albeit in different guises.
If ever a company might fool an AI-powered fraud-detection software, Wirecard had perhaps the greatest possibility.
That said, if ever a company might fool an AI-powered fraud-detection software, Wirecard had perhaps the greatest possibility.
And that’s because Wirecard was so well suited for hiding inflated earnings, because actual cash holdings were not verified by auditors in the last three years of operation, and because AI algorithms for fraud detection are typically used by banks, not trained to look for fraud in banks.
Provided cash holdings are not verified, and cash flows can be muddied by a complicit bank, a company will be free to engage in highly aggressive account manipulation with minimal trace.
Complicate that picture further with a maze of international escrow accounts, and some genuine high margin, but subsequently hidden and embezzled revenue from money laundering, and you have a near bullet-proof fraud machine, a veritable fortress, except perhaps for traces of working capital strain mixed with abnormal accruals or investment activity.
How Wirecard got away with it
Since equity analysts rarely look at working capital and accruals, and are always impressed by expansion plans, these traces are rarely negative for the stock price.
Wirecard’s formidable defences meant that attacks by short-sellers and the FT over the years were never conclusive. Most relied on close scrutiny of Wirecard’s offshore affiliates, entities operating at arm’s length to the business.
These attacks demonstrated that the activities of these affiliates did not tally with Wirecard’s reported numbers. They also revealed that Wirecard appeared to be overpaying for international affiliates.
But the attacks were piecemeal. They indicated accounting discrepancies at agencies in far-flung locations where fraud is prevalent. But there was always confusion whether the discrepancies originated at Wirecard, simply indicated misfeasance or whether the company itself was a victim of fraud. There was no killer blow.
None of the attacks drew on forensic problems that were neatly discernible in Wirecard’s published numbers. On the contrary, Wirecard's reported numbers were so Byzantine that it was virtually impossible to discern anything meaningful from them.
Since AI-powered fraud-detection software relies on reported numbers, this is a possible stumbling block.
Moreover, it is rare for a company conducting legitimate business to hide, embezzle and inflate earnings all at the same time. This is the domain of fronts for organized crime. Unlike the FBI, AI software can’t use an army of IRS analysts to catch such a company on tax evasion. All the software has is the published numbers. It can’t use a complicated tax code.
Another complicating factor is the way that Wirecard evolved from a relatively simplistic payments company focused on porn and online gambling to a bank intertwined with a complex multinational entity.
The nature of Wirecard’s money laundering changed over time. The methods used to inflate earnings evolved over time. The nature of the embezzlement also changed. As a consequence, Wirecard's numbers were never directly comparable from one year to the next, making it difficult to trace monkey business.
To be sure, we were uncertain how an AI system to detect fraud would cope with Wirecard.
Wirecard fraud: What the AI reveals
Wirecard betrayed the trust of gullible homo sapiens but would it also fool untrusting AI fraud-detection algorithms? We decided to put it to the test.
Using Transparently.AI's MRA, we reviewed how Wirecard looked on our system in 2005, 2008, 2012, and 2018.
We chose these years because 2005 gives us the first full year of results after the company listed, 2008 gives the first year of ‘adjusted’ results after the bank acquisition, 2012 was when the company began to pivot to Asia after the US money-laundering case in late 2010, and 2018 shows what the accounts looked like after four years of damaging investigative reporting by the FT and two major short-seller reports.
Wirecard after listing: 2005
Directly after listing in 2005, the Transparently Manipulation Risk Analyzer (MRA) awarded Wirecard an accounting manipulation risk score of 86%. This was a back-door listing into a dormant company, so the 2005 results were pure Wirecard.
Now, 86% is an exceptionally poor score, representing an "F" for accounting quality on our system and putting Wirecard in the 100th percentile for risk of account manipulation globally. In other words, in 2005, the AI software ranked Wirecard as one of the worst companies globally for account manipulation risk. It doesn't get much clearer than that.
The system awarded Wirecard such a poor score because the company exhibited an exceptional number of patterns indicating potential manipulation, Wirecard was so bad that the list of risk signals for 2005 ran to almost two full pages in the Transparently.AI risk report. Enron, by comparison, ran to just over a page.
The AI software gave Wirecard the worst possible risk score on a number of categories including asset quality, growth signals, smoothing activity, investing activity, credit and working capital. It registered the second-highest risk score for accruals management, margin signals and corporate governance. It also warranted extreme care in other key risk clusters such as business manipulation, cash quality, income quality and gearing.
It would be difficult to find a company with a worse pattern of account manipulation risk than was evident in Wirecard's financial statements for 2005.
Basically, our MRA likened Wirecard to a shadowy figure in an alley with a gun; something to be avoided.
Wirecard income manipulation
High on the list of concerns, the MRA advocated extreme care in relation to business manipulation, income quality and cash quality.
Possible business manipulation was evident in abnormal cash flow and production patterns, and in unusual fixed asset sales: all classic signs of potential revenue manipulation. In relation to income quality, effective tax paid was absurdly low in relation to reported earnings and non-operating income was abnormally high. Among the cash quality signals, net change in working capital did not align with reported sales growth.
When added together, these signals suggested that the relationship between income and cash generation in Wirecard's numbers did not make sense. Evidence of possible manipulation risk in any one of these risk clusters represents a serious concern. Evidence of possible manipulation in all three greatly magnifies the danger.
Even worse, the system identified that Wirecard's reported growth appeared unrealistic. The system often flags this growth signal with high growth tech companies. In many cases, growth is genuine.
However, if growth is genuine, a company will not need to manipulate income or cash generation. When a growth signal combines with signals for business manipulation, income quality and cash quality, it signals extreme risk of manipulation. This was the case with Wirecard.
Making matters worse, the system identified risk in relation to income smoothing, accruals and margin signals. Wirecard's reported return on productive assets in 2005 was 69.26%, almost 10 times higher than the regional sector median.
Only the top 5% of companies demonstrate this degree of profitability and rarely for more than a year due to exceptional earnings. Companies that achieve this level of ROA typically have a highly efficient workforce generating high sales in relation to the number of workers. Unfortunately, Wirecard generated below average sales per employee in the period shown in the figure. This was a very strong warning that earnings were indeed overstated.
Figure 2: An excerpt from Transparently.AI's Wirecard risk report for 2005
The bottom line is that Wirecard triggered almost every risk signal for income manipulation in 2005.
Wirecard asset quality
Asset quality is among the top priorities for assessing a firm's financial health.
Asset quality at Wirecard was low because the balance sheet was packed with intangible assets. The ratio of intangible to total assets was more than six times higher than the regional sector average, representing an anomaly of more than three standard deviations.
Since the original Wirecard purchased was for a song and run from a basement, and since the company used for the listing held no assets, anyone with more than passing knowledge of Wirecard must have questioned what meaningful intangibles the company possibly own?
In 2018, short-sellers accused Wirecard of inflating the value of intangible assets, such as its customer relationships and intellectual property, to make the company appear more valuable than it actually was. We would argue it was doing this for more than a decade before 2018.
One possible explanation for the large level of intangibles is that the owner overpaid for other acquisitions before listing. This would make sense if a majority owner wanted to back out immediately after listing. Investors familiar with backdoor listings by Chinese companies in Hong Kong will have seen this kind of activity a number of times.
It is simple asset stuffing. Usually the acquisitions are already owned by the controlling owner. This kind of activity is common in companies engaged in money laundering.
Figure 3: An excerpt from Transparently.AI's Wirecard risk report for 2005
This suspicion was reinforced in the MRA because Wirecard demonstrated a pattern of remarkably high discontinued operations for a small, young company. High levels of discontinued operations can also be a tell-tale sign of manipulated earnings but in this case we suspect that it was a means of washing money from money-laundering operations since most of the discontinued operations were sold for a profit.
Other Wirecard concerns in 2005
This discussion provides a snapshot of the concerns raised by the MRA in relation to Wirecard shortly after listing in 2005. This list is by no means complete. For example, the MRA identified several red flags for poor corporate governance, the strongest being the high frequency of account restatement, abnormalities in the accounting standard used and the high level of audit fees.
The company showed investing risk due to extremely rapid capex growth. This would not be abnormal for a genuine tech company. However, at this stage of its development, Wirecard was not actively acquiring fixed assets and the company’s hardware was in the basement of a small building along with our hacker/soon-to-be COO.
A site visit would have raised an enormous red flag. Fake capex is a great way to embezzle cash and has been especially popular in restaurant chains and agricultural companies over the years. In this case, however, it is more probable that Wirecard was inflating its capex to hide operating costs and inflate its margins.
The company reported extremely low net debt to equity, in fact it was negative, and yet interest expense in 2005 in relation to borrowings was three times the regional median. Strange for a net cash company to pay punitive interest unless it is understating its debt.
The bottom line is that Wirecard’s 2005 accounts were frankly unbelievable. Virtually nothing in the financial statements made sense.
The bottom line is that Wirecard’s 2005 accounts were frankly unbelievable . Virtually nothing in the financial statements made sense.
Our system showed that the company was exceptionally high risk. When combined with some human understanding of the company’s business, the software showed that Wirecard was not investable and probably a fraud
Wirecard after its bank acquisition: 2008-2011
After the 2006 bank purchase, Wirecard’s accounts became increasingly muddied. The net effect was to water down the visibility of Wirecard’s account manipulation. We expected Wirecard’s risk score to decline after the bank purchase and this proved to be the case. The risk score for 2007 was 84% but fell to 70% in 2008 when Wirecard began offering its ‘adjusted’ accounts. The risk score subsequently fell to 66% in 2009, 57% in 2010 and 52% in 2011.
(It’s worth noting that according to our research, the risk that a company is manipulating its accounts and is at risk of failure jumps significantly when its MRA score exceeds 50%, so Wirecard is by no means out of the woods by 2011. If you would like our test data, please contact us.)
Regardless, subsequent events suggest that Wirecard’s account manipulation was not lessening. Rather, Wirecard was getting better at muddying its accounts and engaging in fraud practices that were less visible in its accounts.
In 2008, the AI software still suggested Wirecard was exceptionally high risk. Figure 2 shows an excerpt of the summary from the full company risk report that our system generates. Wirecard required extreme care on four categories and high caution on three further risk categories. On the basis of the MRA score, Wirecard was in the 95th percentile globally for account manipulation risk - still an exceptionally high risk proposition.
Figure 4: A snapshot from Transparently.AI's full Wirecard risk report for 2008
All of the red flags evident in the 2005 accounts were still present in 2008 and subsequent years, but slowly moderated.
Business manipulation at Wirecard
Business manipulation provides a good example of this. In the 2008 accounts, the MRA suggested extreme caution in relation to discretionary expenses, abnormal cash generation and asset sales. As noted, whenever the system flags business manipulation risk in conjunction with other red flags, we have found that it usually points to deep problems.
SG&A expenses, asset sales, and abnormal cash generation and all rose dramatically in the wake of the bank purchase.
As it turns out, this was the period when Wirecard executives are reported to have routinely carried home bags of cash from the company safe.
Depending on the context, frenetic asset turnover can be a way to boost earnings, to mask accumulated fake revenue or to launder money.
At this stage, we suspect asset sales were used to extract money laundering profits from the business while aggressive accruals management had become the principal tool used to inflate earnings. It is difficult to see why a payments company would have any need for accruals and this was an enormous red flag.
Figure 5: An excerpt from Transparently.AI's Wirecard risk report for 2008
Discretionary spending and SG&A can be used to boost revenue or can be used to mask embezzlement. They can also signal channel stuffing, although in the case of Wirecard, where turnover could be whatever the company claimed, it is difficult to see a need for channel stuffing.
The bottom line is that in 2008 the risk signals for Wirecard remained extreme. A prudent investor would only invest in such a company if management were holding their child hostage.
A prudent investor would only invest in such a company if management were holding their child hostage.
The risk scores for margin signals and for cash and income quality improved markedly in 2005. This is the key area where the addition of the bank improved Wirecard's ability to mask its fraud. Banks do not have operating cash flow in the traditional sense, they generate cash by adding leverage. Since Wirecard never had any true margin or cash generation on its main business, the addition of the bank was able to greatly improve its ability to show cash flow.
Valuations were low in 2008 because in June of that year the stock price plummeted after the German shareholder association SDK accused Wirecard of having falsified its accounts for 2007. SDK said the company held customer cash in its own accounts to satisfy audit checks of its 2007 accounts. SDK also claimed that Wirecard inflated its near zero margins, probably the weakest accusation they could make and the toughest to prove.
The accusations instigated a legal battle that resulted in Wirecard being cleared by an audit by EY and the director of SDK resigning and facing prison time for share price manipulation. Round 1 went decisively to Wirecard.
Wirecard after the US money laundering case: 2012
As noted previously, Wirecard was implicated in a US money-laundering law suit in 2010. A subsequent shift away from online gaming and a lengthy audit inspection by EY after the allegations forced Wirecard to alter its business focus between 2010 and 2012.
From 2011 onwards, Wirecard raised a total of EUR 500 million in equity from investors to fund a variety of obscure acquisitions across the globe, including its regional headquarters in Singapore. In later years, it also issued bonds. The company pivoted to channeling funds from Russia as the revenue from gaming fell away.
In spite of the curtailment of manipulation due to the EY audit, Transparently.AI's MRA gave Wirecard a risk score of 58% for its 2012 accounts. This put Wirecard in the 81st percentile for risk globally. The risk score remained high because Wirecard was engaged in new suspicious activities.
As the company gained experience with using its bank and escrow accounts for offshore acquisitions, a less visible approach to account manipulation became available.
Specifically, Singaporean authorities have accused Wirecard of using the proceeds of offshore acquisitions to engage in “round-tripping” – a practice whereby sales and profits are inflated by sending money to a third party, usually by purchasing an asset for a highly inflated price. The proceeds are then used to buy fake services at inflated prices.
Famously, in 2015 Wirecard agreed to pay €300 million for an Indian business only weeks after it had changed hands for €37 million.
By 2012, offshore purchases were not quite at this scale. Nevertheless, reported transactions were sufficiently high to allow a market capitalization of €2.4 billion.
Wirecard continued to flash high-risk signals in critical areas
The capital raisings and associated round-tripping eased the squeeze on operating cash flow and interest payments. As a consequence cash quality and income quality appeared quite good.
Nevertheless, Wirecard's risk report for 2012 offered a full page of high-risk signals in critical areas such as asset quality, working capital, growth signals, accruals management, gearing, credit, business manipulation and margin signals. The MRA risk score of 58% was high for a well-established and widely owned mid-cap company.
As noted, absent the imposition of the bank on Wirecard’s numbers, we expect Wirecard’s risk score would have been far higher.
Figure 6: An excerpt from Transparently.AI's full Wirecard risk report for 2012
Given Wirecard’s background, well known to investors at this stage and given its implication in a very large US money laundering lawsuit, a prudent investor would have avoided Wirecard based on the risk scores from the AI system in 2012. Given the mixing of bank results, we think it remarkable that our system was able to capture the extent of manipulation risk that it did.
Wirecard as the end approaches: 2018
By 2018, Wirecard had entered the Dax 30, was trading at an incredible valuation and was able to raise capital at will. It was able to recycle capital raising into inflated offshore acquisitions, using the proceeds to fund round-tripping and possibly embezzle funds.
This is the line of argument that prosecutors in Germany and Singapore have taken.
By 2018, however, the methods that Wirecard had developed and employed since 2011 to implement fraud were becoming fully extended.
Fraudulent accounting depletes future earnings and can only persist for so long before becoming unsustainable. By 2018, Wirecard had become increasingly reliant on bond finance. The company had been under attack from the FT and various short-seller reports for years. It is probable that those engaged in fraud at the highest levels had a sense that the writing was on the wall.
To the very end, the AI algorithms suggested that the risk of fraud at Wirecard remained high.
To the very end, the AI algorithms suggested that the risk of fraud at Wirecard remained high. The accounting manipulation risk score for 2018, the final year that the company published in accounts, was 53% - in the 75th percentile globally and very high for such a large cap company.
Although the overall risk score was somewhat lower in 2018 than in 2012, closer inspection reveals that Wirecard was flashing more extreme risk signals in latter years than between 2011 and 2015. That is because it was now showing signs of risk of corporate failure. It could no longer hide its fragility.
Figure 7 shows the summary of key risk signals in the Wirecard's risk report for 2018. Many of the risk signals from 2012 remain, notably those relating to margin signals, growth signals, asset quality, accruals and working capital.
By 2018, the signals for business manipulation signals had ceased, suggesting the scrutiny from the FT was making it difficult for the company pursue its old tricks to inflate its cash flow generation.
Figure 7: An excerpt from Transparently.AI's Wirecard risk report for 2018
With scope for manipulation reduced, the 2018 accounts showed increased evidence of financial strain. Relative to 2012, the 2018 report showed deterioration on a number of fronts, notably income quality, cash quality, and corporate governance.
Years of fraudulent activity and increased reliance on debt left Wirecard in a weakened state. This is why signals for income and cash had begun to begun to re-emerge as serious concerns and why the collapse in investing activity was suspicious.
The AI fraud-detection software identified Wirecard as a highly dubious prospect from the moment it listed
It would be a stretch to say that Wirecard was a basket case with a risk score of 53% but interpretation has to be adjusted for that fact that the bank numbers seriously clouded the true picture of Wirecard’s numbers.
Moreover 48% is an ominously high risk score for a large cap.
Based on the company’s history, the frequency of attacks on its veracity, its nosebleed valuation, and its ‘adjusted’ accounting method, Wirecard was still not investable in 2019 on the basis of the AI system’s risk assessment.
Wirecard failed to fool an untrusting machine. The AI fraud-detection software identified Wirecard as a highly dubious prospect from the moment it listed until the time that it failed.
We are confident that any prudent investor presented with the risk analysis we have discussed would have felt compelled to undertake deeper due diligence on Wirecard and found the company deeply suspect.
Wirecard: Aftermath
The Wirecard collapse led to criminal proceedings in Germany, Singapore, Philippines and other locations.
The main trial of Markus Braun, the former CEO of Wirecard, began in late 2022 and is being held at a high-security courtroom at Stadelheim prison in Munich. Braun has already lost two civil cases.
His trial is proving exceeding complex due to a lack of hard evidence and is expected to last until the end of 2024 at the earliest. Markus Braun is accused of misrepresenting Wirecard’s accounts and of market manipulation by falsifying income from transactions with so-called third-party acquirers.
Oliver Bellenhaus, the head of Wirecard’s Dubai subsidiary, and Stephan von Erffa, who was in charge of accounting, are also on trial. Jan Marsalek, the former COO, is a fugitive and believed to be in Russia.
There have been many twists and turns since the prosecutions began. In a recent article, the FT revealed allegations that Marsalek ran a Russian spy ring across Europe. The plot, as they say, thickens.
Disclaimer: Views presented in this blog are the author’s own opinion and do not constitute financial research or advice. Both the author and Transparently Pte Ltd do not have trading positions in the companies it expresses a view of. In no event should the author or Transparently Pte Ltd be liable for any direct or indirect trading losses caused by any information contained in these views. All expressions of opinion are subject to change without notice, and we do not undertake to update or supplement this report or any of the information contained herein.
