Understanding reaction time as a process-level Indicator of financial risk perception: An experimental framework for...

This paper presents a theoretically grounded methodological framework utilising Reaction Time (RT) measure as a process level indicator of financial risk perception. A pilot within subjects' experimental study (N = 28), implemented using PsychoPy v2026.1.1 was conducted to measure decision latency across three critical dimensions; emotional priming, risk framing, and social peer influence. A structured 40 trial sequence was employed to capture behavioural responses, recognising the constraints of pilot level experimental design. Traditional economic models often do not represent the psychological dimensions that influence financial decision making. This paper examines how financial risk perception is influenced by individuals' belief systems and emotions. The framework is designed to provide a structure and replicable approach for implementing reaction time paradigms in behavioural economics and experimental psychology. The paper outlines key considerations in experimental design, data acquisition, and statistical analysis for RT-based financial decision research. Pilot findings suggest that risk framing and social cues influence reaction time patterns. Decisions involving loss frames were associated with longer response latencies (M = 5.42 s) compared to gain frames (M = 3.93 s), reflecting increased cognitive conflict or processing time. Peer influence cues were associated with reduced reaction time (RT) in high-risk scenarios and increased risk seeking tendencies. The findings suggest that reaction time may serve as an indirect proxy for cognitive processes associated with psychological constructs such as regret and social conformity. The study contributes to bridging the gap between outcomes based financial model and process oriented cognitive approaches to decision making. The framework further facilitates transparent implementation and reproducible adaptation across diverse experimental contexts.