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Artificial Intelligence or Dumbing Down the Population?

At stock exchanges around the globe, human fear or greed has always had a considerable influence on prices. It's a good thing we have computers and algorithms that are devoid of all emotions. However, the fintechs often touted as safe to individual investors also carry significant risks.

An article by Katharina Schüller.

At least when considering the energy consumption of Bitcoin, it becomes clear that the digitization of the financial world also raises questions about sustainability. When cryptocurrencies are mined using cheap coal power, the resulting environmental damage isn't confined to the producing country. But sustainability concerns much more than just bees and flowers. The United Nations (UN) defines at least two other Sustainable Development Goals (SDGs) related to crypto and similar technologies: The tenth SDG targets the "reduction of inequalities," and the fourth SDG focuses on "quality education"—and thus also financial literacy, although it is not explicitly mentioned.

Digitization holds significant opportunities for society. For example, innovative fintechs now also give "average savers" access to investment opportunities that were previously only available to a few very wealthy individuals. However, a recent study published in "Die Zeit" reveals that one's own financial situation is also closely linked to economic and financial competencies. Those who do not understand what the data from companies and markets mean cannot benefit from it.

Can artificial intelligence manage capital better?

The financial industry has been using data since time immemorial. With the development of powerful computers in the 1980s, algorithms became powerful tools in investment decisions. This also spurred financial econometricians at universities. Sophisticated statistical methods were employed to better understand the dynamics of financial markets, which in turn made financial instruments increasingly complex. Algorithms today are supposed to generate higher returns and also recognize and minimize risks. Can artificial intelligence really do it better? Its proponents argue that human decisions are often driven by fear or greed. Therefore, they can never be as objective (actually meant: systematically correct) as decisions based on data and mathematical models. Nobel laureates are often quoted without mentioning that Myron Scholes and Robert Merton with their quantitatively managed hedge fund LTCM made a spectacular crash landing. Academic awards thus do not guarantee that the theories will actually work in the long run. In the last ten years, a counter-movement has emerged that understands the 2007 financial crisis primarily as a crisis of models. "The managers delegated their responsibility to technology and thereby also the control over the financial system," summarizes star banker Leonhard Fischer.

But why does this concern us all? Because more and more fintechs claim they want to "transform the traditional money management industry to make the financial markets accessible to everyone, everywhere" (eToro) or "offer the most comfortable form of investing"—a "service that was previously reserved for very wealthy investors" (Scalable Capital). If these promises are kept, then fintechs actually contribute to narrowing the gap between rich and poor. But platforms like eToro and digital asset managers like Scalable Capital go further. They also want to enhance the financial competence of their customers, whether through blogs on financial topics or their own "academies," which are explicitly aimed also at beginners.

Lack of financial competence is extremely dangerous

eToro, for example, lists a number of advantages that give the impression that sustainable investing is the highest purpose of the fintech: they claim to be responsible, transparent, (naturally) innovative, and focus on education. A prime example of a contribution to the fourth SDG? eToro creates an individual risk assessment for each user. This is "a great opportunity to see if you are a responsible trader. Keeping a risk rating of 3 or lower is recommended at eToro." Those who do not want to continuously manage their portfolio are advised to consider their own professionally managed "CopyFunds." However, of the 24 funds offered on the platform, only 14 have a risk rating of 3. All others are rated as riskier, two even with the highest rating of 8. According to the above recommendation, therefore, more than 40 percent of the funds, among them two cryptocurrency funds, do not qualify as responsible investment products. Yet the impression is created that the "CopyFunds" are somehow safe. They are "designed as an investment channel for investments with relatively low risk" and "therefore aim to generate annual returns of up to double digits." Herein lies the great problem of many fintechs. What comes across is a message that once led us into a financial crisis. Namely, that it is normal and reasonable to expect double-digit returns permanently with minimal loss risk. Last time, the professionals fell for it, and you can't even blame them unequivocally. Because the interest rate difference between (we now know: bad) U.S. mortgage bonds and U.S. Treasury bonds was sometimes several percent, but both received the highest possible risk rating from rating agencies. Georg Zoche sums it up in his book "World Power Money": "From the perspective of that time, it was quite reasonable to buy U.S. mortgage bonds instead of U.S. Treasury bonds. And that's why everyone did it." Lack of financial competence has extremely dangerous effects today when non-professionals suddenly mix in all markets. That's why it's so important


Copy Funds

(1) The maximum drawdown represents the maximum loss that an investor could have suffered within a given period. Specifically, it would occur if the investor bought at the peak and sold at the trough. It is expressed as a percentage.

(2) The return-drawdown ratio is a metric that measures the return-risk ratio of an investment. It is calculated by dividing the annual return of the investment by its maximum drawdown. The rule is: the higher the return-drawdown ratio, the better the return-risk ratio.

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(This article appeared in April 2018 in a print version of „Tichys Einblick“.)

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