This research work covers the necessary image processing workflow to facilitate online person identification for financial authentication, to be carried out in a fully automated way. This brings the advantage of fewer errors due to human failures. Moreover, it reduces the cost of a single identification by quite a significant factor. The relevant authentication and validation steps are modelled in BPMN. Validation and comparison of the person visible in the video stream is achieved utilizing a hybrid face recognition approach combined with OCR checking and model-derived individual instructions. To ensure authenticity of the identification card, security features like color-holograms are modelled for each version and supported country. The interconnection of the process sequence, which is individually and dynamically derived from the BPMN together with adaptive paradigms of human-computer-interaction, allow for a beyond the current state-of-the-art level of manipulation prevention and of user assistance. The results show that the process of person identification and authentication can be automated when legal aspects are clarified, thus allowing for a state-of-the-art of precision on face recognition and hologram checking, at a competitive level with human staff.