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Title: KapitalIntelligenz Akademie adds explainability to NovaMind AI 50 under the guidance of Thomas Bernhard

KapitalIntelligenz Akademie has announced the rollout of a major system enhancement to NovaMind AI 5.0, introducing a fully integrated Explainability Module that allows users to trace and interpret how each investment recommendation is derived. The module was developed under the leadership of financial technologist Thomas Bernhard and reflects the Akademie’s growing emphasis on transparency and user empowerment.The Explainability Module enables real-time access to the decision logic of NovaMind AI 5.0’s neural architecture. For every suggested trade, portfolio shift, or signal suppression, the module displays the core data clusters, behavioral indicators, and algorithmic logic branches that contributed to the recommendation. The system also provides simplified summaries for users without a technical background.“No AI should be a black box—especially when money is involved,” said Thomas Bernhard. “Explainability is not just a feature, it’s a principle. With this update, NovaMind AI 5.0 becomes a teaching tool as much as a trading system.”Key features of the new module include:Transparent signal origins: View the key factors driving buy/sell signalsReal-time logic flow: Trace decision paths in visual or tabular formBehavioral tagging: See which psychological market patterns influenced each moveRisk context overlays: Understand how the system adjusted based on volatility, drawdown zones, or macro shiftsUser mode control: Choose between expert and simplified views of the logic treeThis update comes amid rising demand for accountable AI systems, particularly in financial markets where transparency is crucial. According to early trial feedback, 88% of test users reported that the explainability feature improved their trust in the platform and made them more likely to use the...

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