The discovery and quantification of adverse drug reactions has long relied on the careful analysis of spontaneously reported cases. Causality assessment (imputation) was a fundamental feature of individual case report analysis. This was complemented by analysis of aggregated cases, and of disproportionality analyses in spontaneous reports databases. In the absence of more specific information sources, these have resulted in the discovery of many new adverse reactions, altering drug information. It has led to the withdrawal from the market of many drugs, but its use for risk quantification remains fraught with uncertainty. The recent access to population-wide claims or electronic health records databases have confirmed for spontaneous reporting a predominant role in hypothesis generation for serious adverse drug reactions, notably those that result in hospital admission or death. In these cases, the events are identifiable at the population level, and can be quantified precisely using the tools of modern pharmacoepidemiology, to generate specific benefit-risk analyses. Spontaneous reporting remains irreplaceable in signal and alert generation in drug safety, despite its inherent limitations. For signal strengthening and assessment, more systematic and quantitative methods should be sought, such as claims databases for reactions resulting in hospital admissions.