Automated decision making in the finance sector – discrimination or discretion?

Abstract

This Master’s thesis seeks to find a course of legal reasoning and background to various legal problems considering automated decision-making, especially in crediting. Can data be used in the credit approval process in terms of the General Data Protection Regulation? Are the debtors using sensitive data in the process? Can we use statistical data in the process? Could the world find automated decision-making processes as a tool to further discriminate our world? This thesis is mainly a commentary analysis concentrating on the GDPR and its recitals and various academic research literacy sources. This thesis can be used as an interpretation guide for GDPR article 22 and how that can be utilized for normal businesses and companies in the GDPR era while also mirroring the challenges opposed by the non-discrimination regulation European wide. The legal structure is based on some fundamental values. One of these states that any infringement of our privacy and interface with our data necessitates a legal basis and must be limited to necessities and comparable to a legitimate aim. This regulation must be applied to AI technologies, mandating that data be gathered and processed only for specified reasons and that the quantity of data processing is restricted to a minimum necessary for the stated goals. Transparency and accountability are generally well-developed under the data protection rules. Individuals have a right to information, which they should be able to use in contact with regulators and judges