Developing a Comprehensive Financial Reporting Governance Framework Using AI Techniques

Khaleed Omair Alotabi

doi:10.48084/etasr.14202

Authors

Khaleed Omair Alotabi Business of College, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia

Volume: 15 | Issue: 6 | Pages: 29202-29207 | December 2025 | https://doi.org/10.48084/etasr.14202

Received: 20 August 2025 | Revised: 5 September 2025, 13 September 2025, and 17 September 2025 | Accepted: 18 September 2025 | Online: 6 November 2025

Corresponding author: Khaleed Omair Alotabi

Abstract

Financial Reporting Governance (FRG) comprises the structures, controls, and assurance processes that safeguard the accuracy, integrity, and compliance of financial reports. This paper proposes a Comprehensive Financial Report Governance Framework (CFRGF) that integrates Artificial Intelligence (AI) to strengthen oversight across the reporting lifecycle. Using a design science methodology, a structured literature review and concept mining are conducted to derive governance requirements, map them to AI capabilities, and iteratively design CFRGF components, decision flows, and control points. CFRGF organizes governance into four pillars: Data Governance and Quality, Algorithmic Transparency and Integrity, Anomaly and Fraud Detection, and Regulatory Compliance and Auditability. It specifies the roles, responsibilities, controls, escalation paths, and monitoring metrics. The current study details how AI supports risk scoring, outlier detection, exception prioritization, and continuous controls monitoring while preserving explainability, traceability, and human oversight. Implementation guidance encompasses data readiness, model validation, and drift monitoring, segregation of duties, and evidence collection for internal audit and external assurance purposes. The contribution presents a cohesive and implementable blueprint that aligns FRG principles with modern AI tooling, enhancing efficiency, accuracy, and transparency in practice. Organizations can use CFRGF to benchmark current controls, plan AI-enabled enhancements, and structure verifiable evidence for compliance, thereby reducing reporting risk and improving the timeliness and decision usefulness of disclosures.

Keywords:

artificial intelligence, finance report governance, design science methodology

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