Data Governance and Auditability in High-Volume Financial Operations: A Review

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@article{1722630,
      author = {Ifeanyichukwu Jeffrey Okwesa, Funmilayo Ashore-Onisemo},
      title = {Data Governance and Auditability in High-Volume Financial Operations: A Review},
      journal = {Iconic Research And Engineering Journals},
      year = {2023},
      volume = {6},
      number = {8},
      pages = {450-488},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1722630.pdf},
      abstract = {High-volume financial operations (payments processing, trading, lending, and reconciliation) generate torrents of transactional data whose integrity, traceability, and compliance carry material legal and economic consequences. Data governance and auditability are the twin disciplines that make such data trustworthy: the former establishes accountability for how data is defined, produced, and controlled, while the latter ensures that any recorded state or decision can be reconstructed and independently verified. This review synthesises the multidisciplinary literature that connects these disciplines, drawing on information systems research on data governance, database and provenance research on data lineage, the accounting and assurance literature on internal control and continuous auditing, and the regulatory canon codified in frameworks such as COSO and legislation such as the Sarbanes–Oxley Act. Following a structured narrative method, we organise the evidence into five themes: data governance frameworks and mechanisms; auditability, audit trails, and lineage/provenance; internal controls and compliance in finance; data quality; and enabling technologies. A comparative synthesis maps prominent governance frameworks across decision domains, locus of accountability, and treatment of audit and quality. We find that governance and auditability are frequently theorised in separate literatures despite being operationally inseparable in finance, that most governance frameworks under-specify the machinery of end-to-end lineage, and that a persistent tension exists between operational scale and the granularity of control. We argue that provenance-aware, continuously audited architectures reconcile this tension, and we outline a research agenda spanning automated lineage capture, control-aware data quality, immutable audit substrates, and governance metrics. The review is intended for researchers and practitioners designing accountable data platforms in regulated, high-throughput financial environments.},
      keywords = {data governance; auditability; audit trail; data lineage; data provenance; internal control; data quality; financial operations; continuous auditing; compliance},
      month = {February},
      doi = {https://doi.org/10.64388/IREV6I8-1722630}
  }