The availability of big data is also indispensable for the use of artificial intelligence and machine learning – both future technologies of critical importance and both technologies where the US and China have a clear head start in development and deployment.
Nothing works without data: they are at the heart of value creation
in a digital economy and now more than ever a strategic production and
competitive factor that is decisive to a company’s economic success. The
availability of big data is also indispensable for the use of
artificial intelligence and machine learning – both future technologies
of critical importance and both technologies where the US and China have
a clear head start in development and deployment. Access to data and
the ability to reuse them are therefore rightly seen as key
prerequisites for the technology leadership of tomorrow and for a
competitive EU data economy that will strengthen Europe’s digital
sovereignty and benefit both consumers and businesses throughout Europe.
When it comes to data-driven innovation, it is becoming increasingly
important for companies not only to use data they have generated
themselves or to exchange data within a certain industry but also to
better understand and satisfy customer needs with the help of data from
very different areas of application. For many reasons, however, this
still poses practical difficulties for banks and other businesses. These
reasons include a lack of access to data outside a firm’s own business
or lack of knowledge thereof, heterogeneous data formats, non-existent
technical interfaces and uncertainty about the legal framework governing
the use of data, especially with regard to personal data. All of this
means companies have to expend huge resources before seeing or realising
a commercial benefit, which is why they often do not even attempt to
generate new added value for customers by consolidating data from
diverse sources. On top of that, many companies ask themselves whether
they themselves would benefit at all from a data economy or whether they
might ultimately suffer competitive disadvantages from giving up their
data and while others capitalised on greater data mobility.
What can be concluded from these observations? The framework
governing a data economy must be created in such a way that it gives all
market participants equal opportunities. It should not further market
asymmetries but instead help to eliminate existing imbalances. It should
enable as many companies as possible to exploit the enormous potential
of big data analytics and artificial intelligence. This will require an
appropriate legal framework that promotes data sharing under fair
conditions for all market participants. The goal should equally be to
preserve trade secrets and the protection of personal data, thus
strengthening data sovereignty.
The Association of German Banks believes the first step should be to
create a European legal framework that enables data to be shared across
different businesses and industries while taking a differentiated
approach.
1. A cross-sector (B2B) data sharing framework should be established for personal and non-personal data.
Businesses in all industries should be required to share the data
provided to them by a natural or legal person via standardised
mechanisms in real time if the person so requests. To safeguard a level
playing field and preserve proprietary rights, care should be taken to
ensure that this obligation applies only to data provided by the data
subject and not to derived or refined data processed by the company. The
latter category should be reserved for disclosure on a separate
contractual basis. Further conditions will also need to be set with
respect to aspects such as security and liability.
2. Existing technical and legal barriers to the exchange of non-personal data
(= anonymised data, non-confidential business data) should be removed.
This should be achieved, among other things, by creating greater legal
clarity in areas such as anonymisation and, where necessary, easing data
protection rules. Data cooperation in the form of data pooling, for
example, is a major success factor for gaining new insights from the
analysis of a wide range of data and for tapping the potential of
artificial intelligence and machine learning for research and business
in Europe. Ultimately, this also benefits consumers and society as a
whole. Where corporate data are involved, it will continue to be the
company in its capacity as the owner of a trade secret that decides
whether or not to permit access to its data.
3. National and European open data strategies should rigorously promote access to public data.
To this end, electronic access options should be established,
interfaces with public data sources standardised and access points in
the public sector consolidated to reduce transaction costs and make the
data available for the broadest possible use. In some areas, the public
sector could also take on the role of a central data intermediary by
establishing a data exchange platform, especially in spheres where it
operates corresponding central infrastructures to perform its public
responsibilities.
To stimulate a European data economy, there is not least a need for
appropriate collaboration platforms or forums that encourage dialogue
between different sectors and stakeholders, promote the establishment of
cross-sector data ecosystems and provide valuable impetus for the
further development of a legal and institutional framework. The European
Gaia-X[1]
data and infrastructure platform is a promising example. This and
similar initiatives should continue to be supported by policymakers and
the public sector.
BDB
© BDB - Bundesverband Deutscher Banken
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