Responsible AI in finance: PwC

2025-03-17 · Source: Curated for you: AI: PwC · Field: Finance & Economics — Corporate Finance & Treasury, FinTech & Digital Financial Services · Depth: Intermediate, long

Summary

PwC's analysis highlights that AI is transforming finance by enhancing analysis, forecasting, and insight extraction, but its adoption necessitates robust governance for accuracy and compliance, especially for public companies. The report emphasizes three core considerations for finance leaders: establishing data integrity through oversight of sources and control enhancements, validating AI outputs via structured human review, and evaluating AI dependencies in third-party systems like SaaS solutions. It details how CFOs, CAOs, controllers, SOX program owners, and audit committees must define responsibilities, design controls, and engage with external auditors to mitigate risks and ensure financial reporting accuracy. One-third of CEOs report increased revenue and profitability from GenAI in the past year.

Key takeaway

For finance leaders overseeing AI integration into financial reporting, you must prioritize a structured Responsible AI framework. Design and implement robust controls for data integrity and human-led validation of AI outputs. Engage external auditors and evaluate third-party AI systems to mitigate risks, ensuring compliance with ICFR and maintaining stakeholder trust in your AI-driven financial processes.

Key insights

Responsible AI in finance requires robust governance, data integrity, human oversight, and third-party risk management.

Principles

• Data integrity is foundational for AI in finance.
• Human oversight is crucial for validating AI outputs.
• Third-party AI dependencies require rigorous evaluation.

Method

A framework for Responsible AI in finance involves establishing data integrity, validating AI outputs with human review, and evaluating third-party AI dependencies, with defined stakeholder actions.

In practice

• Implement data lineage systems for transparency.
• Manually validate AI-extracted lease terms.
• Request detailed AI model documentation from vendors.

Topics

• Responsible AI
• Financial Reporting
• AI Governance
• Data Integrity
• Internal Controls
• Third-Party Risk Management

Best for: Director of AI/ML, Executive, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by Curated for you: AI: PwC.