Artikel

You Are What You Pay: Personal Profiling with Alternative Payment Data and the Data Protection Law

The global trend toward cashless payment started well before the corona pandemic. Along with it, investors in the data-driven tech industry are inspired by the promise of targeted behavioral scoring based on big data. It seems economically tempting to combine these two trends by using all data generated by the payment services to create personal profiles. However, this business model conflicts with the individual's right of in- formational self-determination and raises questions regarding inaccuracies, discrimination, and the non-transparency of the algorithms underlying these profiles. Our article provides a short overview over the recent economic developments in the financial service industry and a legal assessment in light of the GDPR. Not everything that is feasible with big data scoring using alternative payment data is legally allowed in Europe. Nevertheless, traditional banks could have the opportunity to improve their internal credit scoring systems and use individual customer profiles to further market their financial services.

Language
Englisch

Bibliographic citation
Journal: Vierteljahrshefte zur Wirtschaftsforschung ; ISSN: 1861-1559 ; Volume: 89 ; Year: 2020 ; Issue: 4 ; Pages: 73-88

Classification
Wirtschaft
Financial Institutions and Services: General
Pension Funds; Non-bank Financial Institutions; Financial Instruments; Institutional Investors
Financial Institutions and Services: Government Policy and Regulation
Subject
alternative payment data
personal profiling
credit scoring
GDPR
data protection law

Event
Geistige Schöpfung
(who)
Affeldt, Pauline
Krüger, Ulrich
Event
Veröffentlichung
(who)
Duncker & Humblot
(where)
Berlin
(when)
2020

DOI
doi:10.3790/vjh.89.4.73
Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Object type

  • Artikel

Associated

  • Affeldt, Pauline
  • Krüger, Ulrich
  • Duncker & Humblot

Time of origin

  • 2020

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