Machine-readable financial reporting changes how corporate disclosures become visible, verified, and answerable. Inline eXtensible Business Reporting Language (Inline XBRL) combines a human-readable report with embedded structured data, while artificial intelligence expands automated extraction and screening. The study develops Machine-Readable Accountability as a bounded socio-technical construct organised around dynamic visibility, distributed judgement, and responsibility displacement. A qualitative documentary analysis examines four primary archives: regulatory rules, official filing-evidence records, verification materials, and algorithmic-governance documents. Peer-reviewed studies serve as contextual framing and external corroboration. They do not form primary documentary observations. The corpus covers the mature United States Securities and Exchange Commission regime and the European Single Electronic Format from 2020 to July 2026, with earlier sources retained for historical grounding. A seven-family codebook guides analysis of classification, visibility, validation, judgement, audit, artificial intelligence, and accountability. Results arise from coded rules, official filing observations, assurance requirements, and cross-archive role mapping. Structured reporting reduces extraction costs, supports comparison, and permits automated quality checks. It also places institutional weight on taxonomy fit, extension design, validation logic, and software-mediated review. Documentary evidence supports the relocation of judgement across preparers, taxonomy designers, software vendors, auditors, and regulators. Evidence for deliberate narrative optimisation aimed at artificial intelligence remains indirect, so algorithmic answerability remains a bounded theoretical proposition. The framework links market-efficiency research with studies of quantification, professional judgement, and digital governance, and specifies controls for data lineage, extension approval, model documentation, human review, and responsibility assignment.
Alessio Faccia· Journal of Risk and Financia...· 0 citations
Digital financial reporting depends on identity services, enterprise systems, cloud platforms, automated controls and system-generated evidence. Cybersecurity weaknesses therefore enter external audit when a governance condition or control deficiency affects a material reporting process, an assertion, a disclosure, an estimate or the reliability of audit evidence. This article develops a non-deterministic control-to-assertion framework through a structured integrative review. The search, completed on 16 July 2026, covered English-language journal work published from 2000 to 15 July 2026 through Google Scholar and publisher search services. The final analytic set contains 32 peer-reviewed journal articles, four institutional sources and two public company filings used for worked application. The revision separates organisation-level cybersecurity governance deficiencies from process-level cyber control deficiencies. It also locates the model against COSO, COBIT 2019, NIST CSF 2.0, IT general control methods and relevant International Standards on Auditing. Existing sources provide taxonomies for governance, internal control, security outcomes and audit procedures. The new framework supplies the missing translation route between those taxonomies: governance condition, control state, financial reporting dependency, assertion-level misstatement risk, audit-evidence reliability, audit response and reassessment. Compensating, detective and corrective controls might interrupt or reduce the route, so no governance deficiency automatically produces a control failure or a material misstatement. Two worked documentary applications, The Clorox Company and MGM Resorts International, show how public incident facts enter account, assertion, evidence and procedure analysis. The framework does not estimate incident probability, expected loss or a cyber risk score. It provides a file-ready reasoning structure for entity-specific risk assessment under the auditing standards. Its main contribution lies in the separate treatment of misstatement risk and evidence reliability, followed by a traceable link to accounts, assertions, evidence sources, specialist input and audit procedures.
Alessio Faccia, S. Tangjitsitcharoen· Journal of Cybersecurity and...· 0 citations
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