The Strategic Gap: How AI-Driven Timing and Complexity Shape Investor Trust in the Age of Digital Agents
Krishna Neupane

TL;DR
This paper introduces an AI framework to analyze how strategic timing and complexity in disclosures affect investor trust and market efficiency, revealing a structural 'Strategic Gap' that allows insiders to obscure information and extract rents.
Contribution
The study develops a multi-node AI auditing system to detect and analyze disclosure strategies, highlighting the impact of timing and complexity on market transparency and proposing a shift to active regulatory infrastructure.
Findings
Identified a 60% slowdown in market learning due to strategic disclosure tactics.
Isolated 39 high-priority failures facilitating insider rent extraction.
Demonstrated a 360% potential welfare recovery through recursive AI auditing.
Abstract
Traditional models of market efficiency assume that equity prices incorporate information based on content alone, often neglecting the structural influence of reporting timing and cadence. This study introduces the Autonomous Disclosure Regulator, a multi-node AI framework designed to audit the intersection of disclosure complexity and filing unpredictability. Analyzing a population of 484,796 regulatory filings, the research identifies a structural Strategic Gap: a state where companies use confusing language and unpredictable timing to slow down how fast the market learns the truth by 60%. The results demonstrate a fundamental computational asymmetry in contemporary capital markets. While investors are now good at spotting "copy-paste" text, they remain vulnerable to strategic timing that obscures structural deterioration. The framework isolates 39 high-priority failures where the…
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Taxonomy
TopicsAuditing, Earnings Management, Governance · FinTech, Crowdfunding, Digital Finance · Blockchain Technology Applications and Security
