AI 기반 핀테크 서비스에서 데이터 인식 요인이 개인정보 보호행동에 미치는 영향

This study investigates how users’ privacy concerns drive protective behaviors in AI-based financial services. As fintech algorithms automate decision-making, they increase data processing opacity, heightening concerns about data ownership and control. A structural model was developed where perceived Data Ownership (DO), Data Control (DC), and Data Risk (DR) affect Privacy Concern (PC), which in turn shapes five types of privacy-protective behaviors: Service Avoidance, Passive Acceptance, Technical Control, Information Minimization, and Complaint Expression. Survey data from 548 South Korean fintech users (Kakao Pay, Naver Pay, Toss) were analyzed using PLS-SEM. Results reveal that DO, DC, and DR significantly raise privacy concerns, with DO and DC exerting stronger effects. Privacy concern positively influences all five behaviors, with Technical Control and Information Minimization being most prominent. This indicates that users prefer active management strategies—such as adjusting privacy settings or limiting data sharing—over abandoning services. Multi-group analysis shows that AI awareness level does not alter the data perception–behavior link. The findings highlight the need for fintech platforms to enhance transparency, provide explicit explanations of AI operations, and offer granular control options to reduce user anxiety and foster sustainable trust in intelligent financial systems.