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Fintech 22 Jun 2017

Ten Keys to a Data-Based Economy

It´s still too early to measure the implications of the so-called Fourth Industrial Revolution. The fusion of technologies has begun to erase the lines dividing the physical, digital and biological worlds. Elena Alfaro of BBVA explains how the success of digital companies is based on how they use data to create and improve services.

The products of digital companies are data engines or algorithms surrounded by a great customer experience. These algorithms are fuelled by data in an iterative process: the more customers they have, the better their algorithms get.

According to Alfaro, Amazon and Netflix are excellent examples of digital success, where the algorithm behind their operations has made their business model work. “Digital means data-driven: not only for digital native companies, but for any company or sector that wants to survive,” she says.

Data-driven, in a nutshell, means using data either to support decision-making or eliminating it through process automation. Every company should now consider how they use data engines in their products and processes.

But to allow the data-driven economy to flourish in Europe, Elena Alfaro says, we need to deal with data innovation and data protection in a coordinated way, without giving up either of the two.

Although the following is not an exhaustive list, Alfaro proposes 10 aspects that require particular focus:

  1. Data literacy for citizens: today we have a situation where people give away their data without control, but at the same time complain about data use that might be beneficial for the societies, like investigating health data.
  2. Transparency: there is a need for more transparency from companies and governments in how they use data. This should be promoted and seen as a business advantage, and not just a subject for legal compliance.
  3. Data security research coordination: we need global standards that guarantee protection against cybercrime, such as using blockchain technologies for distributed identity and data management.
  4. Data flow and data storage: a good effort has been made with the European Union’s free data flow initiative, but still we experience many delays when using cloud storage and cloud tools.
  5. Algorithm protection and interpretability: investments in algorithm development are high and companies should be able to decide whether they want to protect them or open them up. Interpretability of algorithms is also mandatory in the EU’s General Data Protection Regulation (GDPR), but further discussions are needed so that the industries can work on explaining complex models that work better than the traditional ones.
  6. The use of anonymized and aggregated data: there are many opportunities in the use of this kind of non-personal data, both for companies and for society as a whole. However, it is still unclear in which cases using this type of data is allowed.
  7. Promoting open data policies: this is essential, and not only for the public sector. Today, a company that opens its data faces many more risks than rewards. This is why only a few companies are actually doing this.
  8. Data portability: the right to data portability in all sectors is a way to promote fair competition and innovation in data services. Data portability will be mandatory in 2018 for the financial sector according to the Directive on payment services, but not for other sectors, although the GDPR introduces it as an important aspect of data innovation.
  9. Harmonization of data laws: this should take place across the EU so that digital businesses can operate in all of them without frontiers.
  10. Artificial intelligence: we need to examine the impact of AI on labor markets and what we can do to help them adapt as fast as possible.

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