Lessons From The Wirecard Case
Taking A Closer Look At The Big Picture
Recently I looked into a lot of annual reports to back a certain argument with real data. What struck me in one particular company was that the sequence of numbers seem to be too good to be real. This was the very same strange feeling I had more than a year ago when inspecting Wirecards annual reports. Do we have not learned anything from this case?
Is Fraud Detectable?
Last year on June 23 we were having our usual coffee break. At that time Covid rules seem to be changing daily. However, we were not discussing how long we would still be able to come into the office. Instead the business news were the chosen topic. The day before Wirecard had made headlines for reporting nearly two billion missing and their stock price had plumbed significantly.
With the money missing and the former CPO on the run there was not much doubt possible that this would be one of the largest fraud cases in Germany.
Was this foreseeable?
There was a lot of noise around the case and various warnings were issued over the years. Unfortunately, most of the people involved had economic interests and were likely biased. An objective answer should not rely on any third party.
But, there might be traces of fraud in their annual reports. However, it is quite easy to hide certain business decisions within hundredths of pages of well formulated prose. But will the numbers lie as well?
Let’s find this out by looking at a few charts.
Revenue
At a first glance the revenue numbers look perfectly. The revenue is growing exponentially. A curve any investor dares to see. However, they went even further. Between 2009 and 2017 their growth factor increased exponentially as well.
This behaviour is completely counter intuitive:
- For every other startup it gets harder to grow over time as markets get saturated, organisations get less effective, and new products have to be developed. For Wirecard it got easier and easier instead.
- Companies typically depend on external factors they do not control. Like the overall economy, the labor market, changes in regulation or a global financial crisis. Nothing is visible here.
- Startups grow in phases. Going to a new market or offering a novel product can restart a viral loop that leads to hyper-growth and catapults one to new heights. Compared to examples like Paypal, Facebook or LinkedIn they had a very smooth ride.
In one sentence: these numbers look too polished to be real.
Profitability
While they were growing with 20%+ each year, they were actually making money. For every single year. Furthermore, they were also able to grow their margin at the same time. This looks like perfect execution.
There are only two blips in the data. Exactly 4 MEUR were missing in 2011 and another 9 MEUR in 2013. We could not find a reason for the former. Whereas the later was attributed to an investment into “Mobile Payment”.
This behaviour is completely counter intuitive:
- Any startup that has found product-market-fit uses all the available resources to scale as fast as it can. Instead they decided to make money and even pay dividends.
- High-potential areas like mobile-payment got a one-time investments of barely 7% of their EBITDA. That was neither enough to turn the needle nor long-term enough to lead to success as developing new products is typically a multi-year process. It looks more like a distraction than following a business opportunity.
- Margins normally drop during high growth phases. There is just no time to optimise for them. Instead they were able to increase them.
Wirecard never really tried to grow faster. Instead they followed a plan that maximised their stock valuations.
Predictions
In their annual reports they were always predicting a single KPI for the ongoing year: the EBITDA. The following charts compares the median of the predicted range with the actually result they reported a year later.
The predictions are surprisingly accurate:
- They never missed a target albeit a rapidly growing business.
- For the first five years they were able to perfectly predict the EBITDA.
- For the next five years they slightly under predicted the value but only to issue ad-hoc announcements to move the prediction a tiny bit up.
Its really hard for any company to make forward-looking statements. For them predictions were easy, even though their progress depend on customer behaviour and the acquisitions of other companies, that were often not finished when they issued the predictions.
Learnings
Our coffee break turned out to be one of the longest in June. But the results were just stunning:
- Their numbers have little entropy — they are too good to be real.
- They made irrational moves by pleasing investors instead of trying to grow faster.
- They were able to perfectly predict the future over many years.
Thus, fraud clearly shines through their annual reports. Following the traces further reveals that it started well before 2010 and was clearly visible by 2013.
Lying is intellectually difficult.
People prefer simple settings to avoid getting caught in the complexities of live. The plan they followed was therefore relatively easy: to please investors they would emulate exponential revenue, slowly bump-up the margin and report more-and-more earnings every year.
Unfortunately, growing exponentially is not sustainable. They had to be caught one day. Whats special here is that it took so long before the house of cards fall apart and many people lost a lot of money.
To avoid a similar fate in the future you have to look beyond the latest quarterly and annual results. Just zoom further out. A decade may tell you a completely different story.
