Trullion explores how explainable AI delivers traceable outputs and auditable decisions for accounting teams, addressing the black-box problem in financial AI systems.
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Researcher proposes evaluation protocols grounded in acceptance-test-driven development to ensure LLMs meet deterministic institutional requirements for safety, auditability, and economic utility—a...
Brazilian forensic accountant demonstrates how to use Claude AI for expert witness reports while maintaining technical rigor and professional standards.
FinVerBench evaluates 15 LLMs on numerical consistency checks in SEC 10-K filings, introducing error taxonomy across arithmetic, linkage, and magnitude categories to measure AI readiness for financ...
BlackLine explores explainable AI's role in audit compliance, highlighting how transparent decision-making and audit trails are critical for regulatory requirements in accounting.
Researchers propose LOM-action, an ontology-governed graph simulation framework that grounds LLM-based agents in business event logic and generates audit trails—addressing a critical gap in enterpr...