Combating AI fraud: why finance leaders must act now

AI fraud is no longer a future threat

AI is no longer just transforming productivity. It is rapidly reshaping fraud. Across Australia and New Zealand, finance leaders are facing a new reality where AI-driven scams are faster, cheaper to deploy, and far more convincing than traditional fraud attempts. What makes this moment different is not just the sophistication of the technology, but the speed at which it is outpacing existing controls.

A recent survey of finance, audit, and risk professionals identified “new technology outpacing controls” as the leading driver of fraud. This creates a critical inflection point for CFOs, particularly as deepfakes, synthetic documents, and AI-powered impersonation move from fringe risks to everyday operational threats. 

Why AI fraud matters now for finance leaders

Companies globally report losing 7.7% of revenue to fraud, underscoring the material impact this has on growth, margins, and trust. 

AI-driven fraud is escalating at the same time organisations are becoming more digitally connected. Remote work, cloud systems, mobile approvals, and complex supplier networks have expanded attack surfaces. At the same time, AI tools have become widely accessible, lowering the barrier for criminals to launch highly personalised scams at scale.

The result is a fraud environment where:

• Attack entry points are multiplying
• Fraud tactics are evolving faster than policy updates
• Finance teams are under pressure to approve transactions quickly
• Traditional detection methods are proving insufficient

The real cost of inaction

Only 35% of finance teams globally rated their fraud prevention as effective in 2025, a sharp decline from the previous year. This gap between risk and readiness leaves organisations exposed to preventable losses.

AI fraud does not only lead to direct financial loss. It creates second-order risks that finance leaders cannot afford to ignore:

• Increased compliance exposure if fraudulent payments breach internal controls
• Productivity loss as teams spend more time manually checking transactions
• Reputational damage when fraud incidents become public
• Erosion of employee confidence in systems and leadership

Five AI fraud realities reshaping finance risk

1. AI impersonation is redefining trust

Deepfake audio and video are now realistic enough to deceive employees in live interactions, including video calls. These attacks exploit urgency, authority, and familiarity, putting intense pressure on staff to act quickly. 

2. Synthetic documents are flooding finance workflows

Generative AI can fabricate invoices, receipts, supplier records, and expense claims in seconds. These documents often include synthetic data designed to bypass traditional checks, making detection significantly harder.

3. Business Email Compromise has evolved

BEC scams now leverage scraped public data and AI-driven personalisation to time attacks precisely. Email, SMS, and voice channels are increasingly combined to create highly plausible, multi-stage fraud attempts.

4. Shadow AI is creating blind spots

Unsanctioned use of external AI tools by employees introduces low-visibility risks, increasing the likelihood of data exposure and manipulation without governance oversight.

5. Fraud is becoming multi-channel

The most concerning trend is the combination of multiple AI techniques into a single attack. A fake invoice may be followed by a deepfake voice note or a phishing message, dramatically increasing the chance of success.

Why CFOs are central to combating AI fraud

Combating AI fraud cannot sit solely with IT or internal audit. The CFO is uniquely positioned to lead because the threat spans payments, expenses, procurement, treasury, compliance, and people. Finance leaders also play a critical role in shaping culture, governance, and decision-making norms. 

Effective responses require more than tools. They demand alignment across finance, IT, legal, and HR, supported by training, clear policies, and leadership that normalises verification and challenge.

Primary

The fightback: people, controls, and governance

This guide outlines a comprehensive framework built around three pillars:

• People, focusing on training, awareness, and a fraud-aware culture
• Controls, strengthening approvals, audits, and verification processes
• Governance, ensuring AI tools are deployed responsibly with strong oversight

Used well, AI can also become a powerful ally. When combined with human judgement, AI-driven detection can flag anomalies, identify deepfakes, and surface patterns that manual reviews miss.

Get the full framework for finance leaders in Australia and New Zealand

AI fraud is a shapeshifting threat, but it is not unstoppable. Finance leaders who act now can reduce exposure, strengthen trust, and future-proof their controls.

👉 Download the full guide, Combating AI fraud: A guide for finance leaders, to explore the complete frameworks, controls, and governance models CFOs need to stay ahead of AI-driven fraud.