Happiness is one of the most important aspects of human lives, yet the literature on emotional well-being indicates that people often fail to correctly anticipate the hedonic consequences of future events. As a result, individuals end up being not as happy as they thought they would be. This phenomenon also applies to the domain of personal finance where people make bad decisions about purchases. In this paper, we identified a new opportunity for the research on recommender systems in personal finance and through analysis demonstrated that intelligent recommenders can help to minimize errors in affective forecasts and enhance happiness of people in the domain of consumption. Furthermore, we reviewed problems associated with design of such recommenders and proposed approaches to overcome them.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 655723
