Profiloimisen

Profiloimisen, commonly translated as profiling, is the process of inferring characteristics, preferences, or behaviors of a person or group by analyzing data from diverse sources. It encompasses both explicit profiling, where attributes are directly solicited, and implicit profiling, where attributes are inferred from patterns in data. The term is used in Finnish to describe this practice across various sectors.

Data sources include online activity logs, purchase history, demographics, social networks, geolocation, and public records. Analysts apply statistical methods, machine learning, and rule-based systems to construct a profile that can be used for prediction or segmentation. Profiles may relate to interests, risk level, likelihood of action, or eligibility for services, often combining multiple attributes into a scoring model.

Profiloimisen is used in marketing for targeting, in finance for credit scoring, in security for risk assessment, and in public administration for program design and service delivery. It also raises concerns when used in law enforcement or surveillance, where outcomes may affect rights or opportunities. Debates focus on accuracy, bias, transparency, and the potential for discrimination.

Legal frameworks in the Nordic and broader European context govern profiling activities. In the European Union, the General Data Protection Regulation restricts processing of personal data and requires safeguards such as purpose limitation, data minimization, and rights to access and rectify information. Finnish data protection law complements GDPR; organizations may perform assessments to manage privacy risks and ensure accountability.