As AI and algorithmic systems increasingly mediate financial decision-making, the need to measure and optimize human cognitive states in real time is growing. Direct brain-computer communication is poised to transform financial decision-making by combining human intuition with machine intelligence and relentless work ethic and speed. This talk will showcase how cognitive data can optimize financial user interfaces, support adaptive trading environments, and will reveal new neural markers of decision quality, fatigue, and confidence. From System 1 and System 2 research, to quant trading to financial education, understanding how people think, not just what they choose, opens new frontiers in personalized finance, AI alignment, and risk modeling.

We examine how real‑time decoding of human cognitive states (enabled by a non‑invasive BCI platform) reconfigures financial decision making by uniting human and AI capabilities in a symbiotic system that reinforces desired financial outcomes.

Our platform, Arctop, makes neuroscience laboratory‑grade metrics, such as visual and auditory attention, cognitive workload, focus, enjoyment, and Brain ID, accessible to AI agents and other humans working in financial environments through consumer headsets that seamlessly fit into existing workflows without altering behavior. This innovation not only preserves existing best practices, but amplifies them by integrating neural markers into trading interfaces, adaptive environments, and risk assessments. By shifting the lens from “what decisions individuals make” to “how individuals and groups think,” our approach offers a transformative frontier in optimizing financial outcomes and enriching economic models.