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This study examines how artificial intelligence (AI) reshapes auditing practices in robo-advisory systems through the integration of internal and external control frameworks. It explains how internal audits ensure algorithmic reliability, data integrity, cybersecurity, and regulatory compliance, while external audits provide independent verification of financial reporting under IFRS, GAAP, Basel III, and MiFID II. The chapter highlights how AI technologies—machine learning, natural language processing, robotic process automation, and explainable AI—transform auditing into a continuous, data-driven, and predictive function. Ethical dimensions such as bias, transparency, accountability, and data privacy are also analyzed, emphasizing the importance of governance frameworks and regulatory oversight. Drawing on real-world examples from leading financial institutions and audit firms, the chapter proposes a dual-layer audit model combining technological and ethical assurance to enhance trust, transparency, and resilience in AI-driven financial ecosystems.

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Robo-Advisory and Auditing: Internal and External Controls

  • 章节

  • 出版模式：

    开放获取

  • 发表日期：

    2026年

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  • Ahmad Hatamabadi Farahani,
  • Narmin Nahidi

摘要

This study examines how artificial intelligence (AI) reshapes auditing practices in robo-advisory systems through the integration of internal and external control frameworks. It explains how internal audits ensure algorithmic reliability, data integrity, cybersecurity, and regulatory compliance, while external audits provide independent verification of financial reporting under IFRS, GAAP, Basel III, and MiFID II. The chapter highlights how AI technologies—machine learning, natural language processing, robotic process automation, and explainable AI—transform auditing into a continuous, data-driven, and predictive function. Ethical dimensions such as bias, transparency, accountability, and data privacy are also analyzed, emphasizing the importance of governance frameworks and regulatory oversight. Drawing on real-world examples from leading financial institutions and audit firms, the chapter proposes a dual-layer audit model combining technological and ethical assurance to enhance trust, transparency, and resilience in AI-driven financial ecosystems.