Imagine this: Two couples apply for a mortgage from the same broker to purchase a house. One couple is white, the other is black. The mortgage broker offers the white couple a prime rate loan, but steers the black couple to a subprime mortgage with higher interest rates and fees.

A clear case of discrimination based on race, right? In 2011, Bank of America paid $335 million to settle claims brought by the Department of Justice that one of their lending arms, Countrywide Financial, regularly charged black and Hispanic customers higher rates than equally qualified white customers for years during the height of the subprime mortgage boom. DoJ argued that Countrywide’s management should have caught the fact that brokers were pocketing fatter commissions by targeting minority borrowers. Closed and shut case (although Bank of America admitted no wrongdoing).

But what happens when an automated piece of software, like a creditworthiness algorithm, replaces the mortgage broker and begins negatively targeting a racial group even without being told to do so? Is the management equally at fault?

In his book The Black Box Society, lawyer Frank Pasquale discusses the many ethical and legal complications stemming from two converging trends: “the financialization of data, and the data-ization of finance.” With the enormous amounts of data now collected by technology companies, the opportunity for automation has become larger than ever before. Similarly, trendy fin-tech startups are using sophisticated creditworthiness algorithms to weed out applicants with higher default risk. This seems like a surefire way to improve the profitability of consumer lending for lenders and reduce the cost of borrowing for borrowers. But Pasquale warns that without aggressive policing by the public, large firms could easily abuse their access to troves of personal consumer data by denying credit on the basis of race, ethnicity, or gender.

And such discrimination happens not just in financial products. “Data brokers” such as Google allow for supposedly ‘precision targeting’ of customers in a variety of industries. In 2013, Harvard Law School professor Latanya Sweeney wrote a study detailing how Google AdSense returns ads suggesting an arrest record 81-95% of the time when a user searches for black-identified names (including her own) such as DeShawn, Darnell, and Jermaine compared to white-identified names. Assuming AdSense was not programmed with an explicit racial prejudice, its results display blatant biases. Some insiders in the tech industry believe that even the software engineers working for these companies have incomplete control over the results produced by their own algorithms.

How can our existing regulations keep up with these rapidly evolving technologies that blur the lines between personalized marketing and discrimination? After all, can a machine even be accused of racism? Is a company liable for not just the process, but also the outcome of its algorithms?

In the US, regulation for these new technologies has been nonexistent, with agencies like the Consumer Financial Protection Bureau taking a ‘wait and see’ approach. Indeed, the power of data brokers looms large – unlike a credit report, which consumers can actively monitor and exercise their right to correct errors, no such rights exist when it comes to maintaining the accuracy of online profile information collected by data brokers. In fact, the Government Accountability Office notes that “consumers generally do not have a right to control what personal information is collected, maintained, used, and shared about them—even where such information concerns personal or sensitive matters about an individual’s physical and mental health.”

Conversely, the European Court of Justice has taken a stance on at least one related issue. Car insurance firms in the EU can no longer consider a customer’s gender when calculating premiums, ending a common practice of offering discounts to female drivers. One UK insurance provider called Drive Like a Girl has already used the ruling to its advantage by charging a premium based on an individual driver’s behavior – a black box in the car engine tracks whether the driver (male or female) speeds, and offers cheaper insurance to drivers who don’t exceed the limit. As a result, many British women may still be eligible for the discount, but not simply on the basis of their gender.

And let’s not lose all hope in technology or technologists. Computer scientists at the University of Utah recently made a breakthrough on understanding how a self-learning algorithm becomes biased. This may well be the first step in improving the fairness of algorithms to reflect the society that we wish to have: one with a more even economic playing field.

By: Upasana Unni

read more

Uber’s Dead End – Germany

The global expansion of Uber’s transportation services is unparalleled. Within few years, Uber entered multiple markets across continents and today, serves customers in 63 countries[1]. However, conflicts with national transportation regulations have caused Uber headaches in several cities. One particularly difficult market for Uber is Germany. Multiple court cases have first slowed down the German market entry before on March 18 of this year, a nationwide ban[2] on UberPop was imposed. With fines as high as 250,000 EUR (approx. 272,000 USD) per violation, did Uber reach a dead end with its expansion in Germany – a key market in Europe?

[3]Key Challenges for Uber in the German Market


Germany’s taxi market is well known for its luxury cars. Indeed, most of German taxis are comfortable Mercedes. Not an easy environment for a taxi service business model that builds on the idea, that private drivers with their own cars provide taxi services. Nonetheless, the attractiveness of the German taxi market is high with yearly revenues of over 4.4bn EUR. Above that, an annual growth of over 4.3%[4] over the last decade underpins the potential for new players in the passenger transportation service market. Therefore, a successful expansion in the German market is quintessential for Uber to grow in Europe. However, there are three main challenges Uber is facing in the German market.


  1. Regulatory challenges:

The basis for transportation services is the ‘PBefG’ law in Germany. It regulates the taxi market and requires multiple safety and quality standards from taxi drivers. In the final court ruling (Frankfurt district court) in March 2015, the presiding judge declared[5] Uber violates the passenger transport law, and thus distorts competition. The main argument is that Uber drivers operate without necessary licenses as well as insurance levels to cover Uber’s services are not sufficient. As a consequence, Uber had to cease its UberPop service in the following weeks after the court ruling.


  1. Competition from Uber clones[6]2

Regulatory hurdles are not the only challenge for Uber in the German market. In fact, there exists a very strong competitor, mytaxi, which allows customers to call and pay taxis via an app. Mytaxi positions itself as the worldwide first taxi-app. They work only together with licensed taxi drivers and thus, circumvent the regulatory dead end Uber faces. Mytaxi claims to have 10m registered users and a network of 45,000[7] taxis. Thereby, they have a strong focus on business customers and also have partnerships with loyalty programs such as Miles & More. The functionality is quite alike Uber’s: one can see the available drivers in the neighborhood, book a trip, see the rote, and pay with the app. However, a distinctive difference – there is no surge pricing. German’s appear to prefer reliability and no surprises. A nice add-on of mytaxi is the option to request specific drivers.


  1. Traditional competitors beefing up:


Also the traditional taxi players become aware of the opportunities digitalization offers. Meanwhile, many larger regional taxi companies have launched their own apps. Apparently, the network effects of these apps are limited as they are bound to drivers of the same network. Thus, they are at a disadvantage compared to a mytaxi, who has taxis in every major city and across different taxi companies in the network. As the prices are the same, there is no real incentive for customers to choose a company specific app vs. apps that connect different taxi networks.




Key Learnings for Uber: Learn How Germans Think

First of all, Uber’s dogma ‘rather ask for forgiveness than for permission’ did not work out at all and heavily damaged the image / branding of Uber in Germany. My advice: ‘rather ask for permission than for forgiveness’, because Germans simply not good at forgiving mistakes. Secondly, proactively regulate oneself. Uber can offer an adjusted service that complies with German regulation. Similarly to mytaxi, Uber needs to partner up with licensed taxi drivers. The challenge will be to be more attractive for drivers than mytaxi. Uber could leverage its size to offer special services to drivers (e.g. better rates at car dealers, repair shops, or car washes) and aggressively offer bonuses when joining Uber as a driver (similarly to the 500 USD bonus in the US). Finally, Uber needs to step up to the high expectations of the German market. Linking Uber with Miles & More, the leading loyalty program in Germany, is quintessential (not only SPG as in the US). Moreover, Germans are accustomed to the option to request regular drivers as well as order taxis in advance. The latter option is particularly important for business travelers.




[4] Own calculation, based on numbers from: Deutscher Taxi- und Mietwagenverband; BMVI; Deutscher Taxi- und Mietwagenverband – Geschäftsbericht 2014/2015, Seite 113




By: Frederic Rupprecht

read more

Apps: The End of Browsing Freedom

Have no fear, apps are here!

Searching for an obscure website on Google will soon be part of the past. Studies show we are moving towards a world of mobile Internet. Mobile data—going through smartphones and tablets—is shifting from browsers to apps. Soon, apps will dominate Internet traffic…but don’t take my word for it. Let’s look at the data.

Internet Traffic is Going Mobile

According to Cisco’s Virtual Networking Index Study:

“Last year’s mobile data traffic was nearly 30 times the size of the entire global Internet in 2000.”

 In 2014, the number of mobile devices and connections reached 7.4 billion. Today, there are more mobile connected devices than people on Earth.

Global Mobile Devices and Connections Growth

Source: Cisco VNI Mobile, 2015


Apps are Dominating Mobile Internet

 In the figure above, we see that laptops are on the decline, while smartphone growth is exploding. Now that we know mobile devices appear to be the dominant form of accessing the Internet in the foreseeable future, let’s take a look at mobile Internet traffic trends.

Data from Nielsen shows that apps account for 89% of media consumption on smartphones, while only 11% goes through mobile browsers.

Source: Smart Insights, 2012

Implications of an App-Centered World

We’ve seen the exponential growth of mobile devices compared to traditional laptops and how Internet traffic on these mobile devices is primarily via apps. With these trends pointing to a future dominated by mobile applications, it’s hard not to ponder how that will impact larger technological trends.

The following are my 3 predictions for the future of an app-dominated Internet:

  1. Smart watches, phones, cars, TVs, and houses will tip the scale towards an app-only experience. With all computing devices running apps, operating systems will focus on integrated applications that don’t require a browser. Microsoft and Apple will push hard to cut Google’s search out of the user experience by redirecting traffic through apps with functions such as voice control/Siri. Eventually, developers will focus on apps rather than standalone websites.
  2. Governments will push to end “free browsing” in order to stop illegal activity, copyright infringement, and child pornography. With all traffic moving through apps, content can be more easily monitored and blocked.
  3. With all Internet activity directed through apps, the stage will be set for world domination by artificial intelligence robots. All hail Siri.

By: George Gonzalez

read more