Net valence analysis of iris recognition technology‑based FinTech

Iris recognition technology (IRT)-based authentication is a biometric fnancial tech‑ nology (FinTech) application used to automate user recognition and verifcation. In addition to being a controversial technology with various facilitators and inhibitors, the adoption of IRT-based FinTech is driven by contextual factors, such as customer perceptions, deployed biometric technology, and fnancial transaction settings. Due to its controversial and contextual properties, analyzing IRT-based FinTech accept‑ ance is challenging. This study uses a net valence framework to investigate the sali‑ ent positive and negative factors infuencing the intention to use IRT-based FinTech in automated teller machines (ATMs) in Jordan. This study is pertinent because there is a dearth of research on IRT-based FinTech in the relevant literature; most previ‑ ous research has taken purely engineering and technical approaches. Furthermore, despite considerable investments by banks and other fnancial institutions in this FinTech, target user adoption is minimal, and only 6% of Jordan's ATM transactions are currently IRT-enabled. This study employs mixed methods. In the frst qualita‑ tive study, 17 Jordanian customers were interviewed regarding the benefts and risks of IRT-based FinTech in ATMs. Content analyses determined the most important concepts or themes. The advantages include fnancial security, convenience, and Fin‑ Tech-enabled hygiene, whereas the concerns include performance, fnancial, privacy, and physical risks. The research model is constructed based on the qualitative study and theoretical underpinnings, wherein 631 Jordanian bank customers with active ATM accounts were surveyed to validate the research model. The fndings indicate that IRT based FinTech usage in ATMs is proportional to its perceived value. In descending order of efect, fnancial security, FinTech-enabled hygiene, and convenience benefts positively impact perceived value. Privacy, fnancial, and physical risks have nega‑ tive impacts on perceived value, whereas performance risk has no efect. This study contributes to the relatively untapped domain of biometric technology in information systems, with important theoretical and practical implications.