The importance of unconscious, automatic processes in judgment and decision-making is increasingly recognized today. However, it remains unclear whether and how intuitive decisions differ from controlled, deliberate decisions in terms of the underlying cognitive processes. In an online experiment with N = 140 participants, a cognitive modelling approach was used to investigate how the instruction to make intuitive or deliberate decisions affects the choice between two stocks based on probabilistic information from four experts. Across analyses, results indicated that the information integration process underlying both intuitive and deliberate decisions can be modeled by an automatic consistency maximization process, as formalized in the parallel constraint satisfaction model of decision making (PCS-DM). PCS-DM with per-person fitted parameters (PCS_fitted) effectively accounted for choices, decision times, and confidence in both decision modes. Strategy classification analyses revealed no significant difference in the distribution of decision strategies between conditions, with around 80% of participants using weighted compensatory strategies (PCS_fitted, PCS_fix, WADD_c) compared to simpler, serial heuristics (TTB, EQW). This was found despite observed differences such as longer decision times and higher average performance in the deliberate condition. We interpret our results as supporting the assumption of comparable basic cognitive mechanisms underlying both intuitive and deliberate decisions. We argue that future studies should further investigate individual and task differences and emphasize the potential of computational modeling approaches to provide evidence for or against the assumption of dual processes.