This manuscript proposes a new model that integrates neurotechnology with machine learning techniques in an attempt to boost the statistical analysis of big data streams, specifically in relation to the turbulent financial marketplace. The proposed model enables real-time processing, real time anomaly detection, and predictive analysis, and in doing so, helps in strengthening decision-making processes and minimizing financial vulnerabilities. Empirical evaluations exhibit high predictive accuracy, adaptability, and high potential for personalized financial interventions, in tune with current trends and future trends in the financial marketplace.
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