Research on financial decision aids, systems designed to help people make financial decisions, is sparse. Previous research has often focused on the theoretical soundness of the advice that the systems provide.The original contribution of this doctoral thesis is a set of empirical studies of how non-expert people understand the advice provided by financial decision aids. Since every piece of advice must be interpreted by a receiver, the accuracy of the advice can be corrupted along the way if the receiver does not understand complicated terminology, probabilistic reasoning, or abstract concepts.The design concept resulting from the studies visualizes a unique combination of short-term and long-term variables that are usually treated as separate and not interacting with each other; loans and amortizations, insurance, retirement saving, and consumption. The aim is to visualize the consequences of different decisions and possible adverse events in terms of their effect on the user’s future consumption, rather than abstract numbers detached from the user’s lived experience.The design concept was tested and evaluated by personal finance experts and professional financial advisors, as well as students and people without financial education, who represented the target users of the system. Results indicate that the system has a learning curve, but that once users understand how to read the graph, they find it more informative than conventional financial planning tools.