The financial services sector faces a critical paradox: while computational power drives modern operations from credit assessments to fraud prevention, regulatory frameworks demand complete transparency in decision-making processes. This creates what industry professionals term the "black box" challenge—sophisticated systems that produce outcomes without revealing their analytical pathways. Traditional machine learning models operate beyond human comprehension, making oversight nearly impossible for institutions managing vast asset portfolios under rigorous regulatory supervision. This opacity creates existential risks for organizations that must justify every decision to regulators and stakeholders. Hebbia identified this fundamental gap early, recognizing that even with proper citation

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