Crediting Humans: A Systematic Assessment of Influencing Factors for Human-in-the-Loop Figurations in Consumer Credit Lending Decisions

The concept of "human-in-the-loop" (Hilo) has gained prominence as a regulatory mechanism for ensuring human control in automated systems, particularly in the context of automated decision-making mechanisms or AI-supported systems. However, despite its increasing use in regulatory discourse, there is a lack of empirical understanding regarding the real-world conditions and influencing factors that affect decision-making processes in such hybrid systems. This paper aims to address this gap by focusing on the use of automation, and the inclusion of humans, in consumer-facing credit lending decisions, a key industry use case. By employing an interdisciplinary approach that combines legal perspectives, social sciences, and architectural modeling—a methodology rooted in computer science—this research offers a first systematic analysis of the factors that influence meaningful human control in (semi-)automated decision processes. Specifically, it contributes to the field by broadening the understanding of the Hilo concept and providing empirical insights into the factors that influence machine-human interaction in co-decisionary architectures. Referencing existing literature that proposes to differentiate various roles for Hilos, the paper proposes two additional roles of Hilos to be considered, due to its empirical findings, namely a Special Case Handling Role and a broader understanding of the Resilience Role of Hilos.