TAG ARCHIVE
finance
2 MARIA OS blog articles tagged finance, organized as a Bonginkan topic archive for search engines and LLM retrieval.
Judgment OS / Decision Intelligence OS
Core MARIA OS research on turning organizational judgment into executable decision systems.
Agentic Company Architecture
Research on human-agent organizations, delegation boundaries, role topology, and governed autonomy.
Responsibility Gates and AI Governance
Safety, accountability, fail-closed gates, auditability, and human-in-the-loop control for AI agents.
Multi-Agent Mathematics
Formal models for convergence, stability, game theory, graph dynamics, and multi-agent evaluation.
Evidence, RAG, and Knowledge Governance
Evidence bundles, retrieval architecture, Graph RAG, knowledge trust, and auditable reasoning pipelines.
AML Detection Gate Optimization: Constrained Loss Minimization for Anti-Money Laundering
Formalizing gate strength as a continuous control variable to minimize the combined cost of false positives, missed detections, and investigation delay in AML compliance pipelines
AML programs face a costly tradeoff between false positives, missed detections, and investigation delay. This paper formalizes AML detection as constrained loss minimization over gate strength `g` and treats the benchmark numbers as synthetic scenario outputs, not as universal regulatory thresholds or turnkey compliance claims. The practical value of the article is in the control framework, escalation logic, and risk-based calibration structure.
Auditable Financial Decision Traceability: Evidence Graph Models for Regulatory Compliance
Formal evidence graph construction and matrix-algebraic traceability for reconstructing every financial decision under SOX, Basel III, and MiFID II
Regulatory reconstruction of AI-driven financial decisions is difficult when logs are fragmented, timestamps drift, or causal links are missing. This paper introduces a formal evidence-graph model where each decision is an immutable node in a directed acyclic graph, linked by typed causal edges with cryptographic evidence bundles. We define `TraceCompleteness` as `TC = |reproducible decisions| / |total decisions|` and report `TC >= 0.997` across evaluated SOX, Basel III, and MiFID II audit scenarios.