Only one in four German households has a plan for retirement and planning is significantly higher among individuals with high financial literacy (Bucher-Koenen and Lusardi 2011). Studying instruments for lowering information cost such as FinTech Apps, and Pensions Dashboards in particular, is thus particularly relevant in this context. Extant theory predicts that it is especially individuals with low financial literacy and little interest in personal finance that should benefit the most from such instruments, because it reduces information acquisition through greater convenience and transparency. For our field study, which launched in January 2017, we offered participants an app-based overview of their future pension claims from state, occupational and private pension contracts (digital pension dashboard). We randomize different information treatments among dashboard users. Two partnering banks helped us attract more than 12,000 of their clients as participants, which all participated in an initial survey on pension planning. Participants belonged to one of four treatment groups or one of two control groups. The banks also provide us with account balance and transaction data for all participants before and after the treatment period that we combine with the survey data and the dashboard data. The richness of the data permits us to test many of the main predictions of state of the art literature on individual pension planning and information processing (e.g. rational inattention). We focus on Matӗjka and McKay (2014) who propose a discrete-choice variant of the rational inattention approach.
