In many organizations, the audit does not begin when the auditors arrive. It begins months earlier, quietly and painfully, as finance teams start reconstructing trails that should already exist. Spreadsheets are pulled from shared drives. Emails are searched for approvals that were never logged centrally. Data is reconciled manually across systems that were never designed to speak to one another. By the time the formal audit starts, the organization is already exhausted. This pattern is not confined to one sector. Public agencies, financial institutions, healthcare providers, manufacturing firms, and NGOs all face the same underlying problem: compliance has grown more complex, while the systems that support it remain fragmented. Regulatory expectations now demand continuous assurance rather than periodic reporting, yet many organizations still operate as though audits are rare events rather than an ever-present obligation. Data pipeline automation is emerging as a structural response to this mismatch. Rather than treating audits as episodic exercises in reconstruction, automated data pipelines embed compliance into everyday operations. Financial data is captured, validated, transformed, and logged as it moves through the organization, creating an audit-ready environment by default rather than by emergency effort.
Adeola Yusuf (Mon,) studied this question.