Abstract
The banking sector has undergone transformations within a rapidly evolving banking ecosystem driven by fintech and AI, demanding empirical studies using realistic simulations to understand how consumers weigh different service attributes in a new competitive landscape. This research investigates customer trade-offs and segment heterogeneity via a Choice-Based Conjoint (CBC) survey with 208 respondents. Data analysis was conducted using Hierarchical Bayes estimation with 20,000 MCMC iterations to capture individual-level preferences. The Results show that service response time is the most valued attribute (20.22%), followed by financial product yields (17.65%) and credit card fees (15.92%). Together, these factors account for 53.8% of the total importance. A central finding is the low utility of personalized service, which contradicts the expectations of relationship banking theory. Having an exclusive relationship manager had the lowest relative importance (4.81%). This suggests that, in the current competitive environment, operational and technological efficiency may replace personal contact as a decisive factor for the general consumer. The analysis also identified clear differences between customer segments. Customers with more than seven years of tenure exhibit a stronger preference for traditional banks (p = 0.003). Price-sensitive customers prioritize digital banks (p=0.013), whereas those willing to pay for an exclusive relationship manager still favor traditional institutions (p=0.002). These findings suggest that while digital banks can focus on speed and cost-efficiency, traditional banks can maintain relevance by targeting mature, long-tenure segments that still value high-touch service.