Behavioural Finance (BF) is an approach for studying Finance and Economics, based on the interactions among cognitive sciences and decision-making models. Orthodox-Economic theory fails in representing the decisional process of individuals in a realistic way, especially regarding the non-rational component of their behavior. By moving beyond those approaches, which assume a completely rational behavior, BF explores the main cognitive distortions that could lead to sub-optimal decisions and behaviors. Traditional Finance considers non-rational behaviors like anomalies, but the effects observed in the real world indicate that new modeling efforts are required for the emotional components. This paper analyzes the most frequent behavioural distortions (biases, heuristics and framing effects) in terms of BF, and proposes their use within computational models, employed as tools for better understanding the aggregate and complex effects of emotionally distorted behaviors, as opposed to pure rational ones, when dealing with financial topics.