As the proportion of older adults continues to grow rapidly here in the U.S. and across the globe, aging adults may be required to make increasingly more independent health-related and financial decisions. Thus, it is increasingly imperative to better understand the impact of age-related psychological changes on decision making. Although a growing body of research has linked age-related deficits in attention, memory, and cognitive control to changes in medial temporal and lateral prefrontal cortical function, remarkably little research has investigated the influence of aging on valuation and associated mesolimbic function in the striatum and medial prefrontal cortex. Likewise, theoretical accounts link age-related declines in a number of basic cognitive abilities to dopamine function, but research has largely neglected age differences in value-based learning and decision making which also rely on the dopamine system. Recent findings reveal age-related declines in the structure of striatal and medial frontal circuits, however it was not previously clear whether these structural declines contribute to functional deficits in incentive processing. Thus, the seven experiments presented here explored potential age differences across a range of value-based tasks from basic anticipatory and consummatory responses to reward cues (Experiments 1--2) to probabilistic value-based learning (Experiments 2--5) to investment decision making (Experiments 6--7). The studies focus on both age-related and non-age-related individual differences in learning and decision making across the adult life span. Overall, three sets of key findings emerge. The first set of experiments on anticipatory affect reveal evidence for an age-related asymmetry in the anticipation of monetary gains and losses, such that older adults appear less sensitive to the prospect of financial loss than younger adults. In a subset of adults, this anticipatory affective bias contributes to loss avoidance learning impairments through the sensitivity of the anterior insula. Thus, although a relative lack of anxiety about potential loss may contribute to increased well-being, this asymmetry may put individuals with blunted loss anticipation at risk for certain types of financial mistakes. In fact, we show that individuals who perform poorly on the laboratory-based loss avoidance learning task accrue more financial debt in the real world. The second set of experiments focus on age differences in value-based learning and reveal that although older adults show intact neural representation of the actual value of reward outcomes, there is an age-related decline in the neural representation of prediction error at outcome in the striatum and medial prefrontal cortex. Age differences in learning are magnified when choice set size is increased, but when the number of trials is extended older adults reach the same performance criterion as younger adults. The third set of experiments focus on age differences in risky financial decision making and reveal that older adults make more suboptimal choices than younger adults when choosing risky assets. Neuroimaging analyses reveal that the representation of expected value in the nucleus accumbens and medial prefrontal cortex is correlated with optimal investment decisions, and that the age-related increase in risky investment mistakes is mediated by a novel neural measure of variability in nucleus accumbens activity. The presentation of value information through visual decision aids improves investment choices in both younger and older adults. These findings are consistent with the notion that mesolimbic circuits play a critical role in optimal choice, and imply that providing simplified information about expected value may improve financial risk taking across the adult life span. Across the experiments, the findings suggest that both age-related affective biases and probabilistic learning impairments can influence decision making both in the laboratory and in the real world through insular and mesolimbic brain regions. Importantly, age-related impairments are reduced under supportive task conditions (designed to target the brain systems identified using neuroimaging). Together, the set of experiments presented here suggests that understanding how the brain processes value information may eventually inform the design of more targeted and effective behavioral interventions for investors of all ages.