Mindbridge

Guest Contributor Michael Rasmussen CEO, GRC 20/20 Research Editor's Note: This guest article by Michael Rasmussen expands on themes discussed during MindBridge's webinar, Building Resilient Financial Risk Oversight in an Era of Constant Change. Watch On-

For more than a century, financial oversight has relied on a simple idea: review a representative sample and infer the condition of the population. Audit standards, internal controls, internal audit, and external audit practices all evolved around that pr

Over the past year, nearly every major enterprise software vendor has announced a new generation of AI capabilities for finance. SAP is expanding Joule across finance workflows. Oracle is embedding AI agents throughout Fusion Cloud Applications. Workday i

The future of audit will be shaped not only by new technologies but by the standards and oversight frameworks that govern how those technologies are applied. MindBridge recently submitted formal comments to the Public Company Accounting Oversight Board (P

AI is no longer sitting at the edge of the business. It is increasingly being embedded into financial reporting, approvals, monitoring activities, vendor management, reconciliations, and other critical workflows across the enterprise. In many cases, these

AI is no longer sitting at the edge of the business. It is being embedded into everyday processes, from journal entry review and expense approval to fraud monitoring, customer communications, vendor screening, and financial reporting workflows. For audit

Accounting firms are facing increasing pressure from larger datasets, tighter timelines, rising client expectations, and ongoing staffing constraints. As engagement complexity grows, many firms are rethinking how review and audit workflows scale without s

Audit has always relied on sampling as a practical way to evaluate large volumes of financial data. But as data has grown, systems have fragmented, and risk has become more complex, that approach is starting to show its limits in ways that are harder to i