Decision fatigue refers to the declining capacity or willingness to sustain effortful choice after repeated acts of decision-making. In financial settings, where decision makers must compare uncertain outcomes, weigh delayed consequences, and process dense information, fatigue can shift behavior toward defaults, procrastination, heuristics, or impulsive risk taking. This essay synthesizes theoretical, experimental, field, and neuroeconomic research on decision fatigue in financial judgment. Additionally, this essay forms part of a broader project investigating AI-assisted literature synthesis across multiple domains of decision fatigue. Preliminary literature reviews were generated using a specialized scientific AI system (Science42: DORA / Insilico Medicine) and subsequently consolidated into structured essays with ChatGPT, followed by human validation. Across studies, the most consistent findings are increased reliance on easier options, reduced tolerance for complexity, and context-dependent changes in risk preference. The essay also identifies key moderators, including age, financial literacy, numeracy, socioeconomic strain, choice overload, time pressure, and stress. A major conceptual challenge is that decision fatigue is often inferred indirectly from sequence, time-of-day, or workload rather than measured directly, which makes causal claims more fragile than broad summaries sometimes imply. Overall, the literature supports decision fatigue as a meaningful but heterogeneous influence on financial behavior. The most promising countermeasures combine simplification, well-designed defaults, targeted education, and supportive decision technologies that conserve cognitive resources without obscuring important trade-offs.