Greece\u2019s new state credit scoring framework brings together financial regulation, personal data protection and algorithmic decision-making in a new and increasingly important way.<\/p>\n
In a recent interview with the Athens-Macedonian News Agency (ANA-MPA) 104.9<\/strong>, we discussed what the new framework entails and what its practical implications may be for individuals and businesses.<\/p>\n The new system allows for the generation of a credit assessment based on financial data and information concerning a person\u2019s payment behaviour vis-\u00e0-vis the State.<\/p>\n The key development is that the process goes beyond the mere recording of outstanding debts. The system relies on algorithmic models and machine learning techniques to assess credit risk and estimate the likelihood of future default.<\/p>\n One of the most important distinctions in the public debate is the difference between credit scoring<\/strong> and social scoring<\/strong>.<\/p>\n Credit scoring is intended to assess a person\u2019s creditworthiness on the basis of financial information. Social scoring, by contrast, involves a much broader evaluation of a person\u2019s behaviour or personal characteristics, potentially affecting access to services or social opportunities.<\/p>\n As currently designed, the Greek system concerns financial and creditworthiness assessment and does not amount to a general system of social scoring.<\/p>\n The real red line, however, is to prevent the future expansion of a credit score into areas unrelated to the purposes for which it was originally created.<\/p>\n The introduction of such a system raises significant data protection issues.<\/p>\n Key questions include:<\/p>\n The European data protection framework, and the GDPR in particular, imposes heightened safeguards where automated processing may have significant effects on individuals.<\/p>\n At the same time, the EU AI Act<\/strong> places AI systems used to assess the creditworthiness of natural persons within the high-risk category, subject to enhanced governance, oversight and transparency requirements.<\/p>\n A well-designed credit scoring system may offer tangible benefits: more accurate credit risk assessment, reduced over-indebtedness and potentially improved access to finance for individuals who have limited traditional banking history.<\/p>\n The key issue, therefore, is not to treat technology itself as a threat.<\/p>\n What matters is ensuring a clearly defined purpose, proportionality, transparency, meaningful rights of challenge, human oversight and effective safeguards against misuse<\/strong>.<\/p>\n The full discussion (in Greek) is available here:<\/p>\nWhat is state credit scoring?<\/h3>\n
Credit scoring is not the same as social scoring<\/h3>\n
Personal data, GDPR and algorithms<\/h3>\n
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Technology is not the problem in itself<\/h3>\n