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Artificial intelligence (AI) is transforming financial reporting by automating processes, improving efficiency, and uncovering insights. AI enables speed and accuracy that were once difficult to achieve, such as transaction processing to contract review. Yet with these innovations come with risks, particularly related to internal control over financial reporting (ICoFR). Without proper governance, AI adoption could compromise reporting integrity instead of strengthening it.
Setting the Right Foundation
Strong governance must guide every AI initiative in financial reporting. Policies and standards should be established before implementation. Key areas include:
- Access controls to manage system permissions and safeguard sensitive data.
- Data integrity checks to ensure training and input data remain reliable.
- Use case road maps that connect AI opportunities with risk management strategies.
- Governance frameworks aligned with organizational risk tolerance.
- ICoFR risk assessment to evaluate how AI affects financial controls and reporting accuracy.
Training and Accountability
Adopting AI changes how people, processes, and controls work together. To reduce risk, organizations must build awareness across functions and clarify accountability:
- Training and awareness programs should address risk tolerance and clarify how AI impacts ICoFR.
- Second and third lines of defense (compliance, audit, and IT teams) play a crucial role in validating AI outputs.
- External auditors should be engaged early to align expectations and avoid surprises
- Accountability structures, including governance committees, CFO oversight, and support from CIOs and CISOs, ensure responsibility ownership is clear.
Implementation and Oversight
AI in financial reporting should be introduced gradually, focusing first on objective, low-risk use cases. Organizations should:
- Begin with quick wins, such as extracting contract terms.
- Use phased implementation alongside existing systems to build confidence.
- Apply agile approaches to balance innovation with governance.
Testing and monitoring are critical for trust and compliance where a tiered approach works best:
- Human-in-the-loop validation remains the simplest safeguard.
- IT controls with confidence scores strengthen reliability.
- In the future, AI checking AI may add an extra layer of assurance.
Regular reviews, documentation, and board oversight further ensure alignment with evolving risks and technology.
Balancing Opportunity and Risk
AI can modernize financial reporting, but success depends on governance, accountability, and transparency. By embedding robust controls and monitoring practices, organizations can harness AI’s benefits while protecting the integrity of their reporting.
How Crowe Can Help
Crowe helps organizations adopt AI in financial reporting with the right balance of innovation and control. We assess how AI impacts internal control over financial reporting (ICoFR), design governance frameworks, and align compliance with business objectives.