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The rise of AI fraud and how you can reduce your risk
Talking points
- Generative AI technology provides bad actors access to sophisticated tools to commit fraud.
- To help mitigate the risk of AI fraud, organizations should revisit their fraud risk management frameworks.
- By following a few strategic tips, such as those outlined below, Risk Management and Internal Audit, among other functions, can play an important role in reducing AI-enabled fraud risks.
Over the past year, we’ve seen a flood of stories about the impressive benefits artificial intelligence (AI) can bring to businesses. But with this rush of AI exuberance, are we overlooking the potential for new types of AI-enabled fraud and criminal activity?
Thanks to Generative AI (GenAI), bad actors now have access to sophisticated tools that can execute more complex fraud schemes on a large scale, potentially evading traditional detection methods. In a new report, Deloitte’s Center for Financial Services predicts that GenAI could drive a substantial increase in fraud losses in the United States: from some $12 billion in 2023 to $40 billion by 2027.
GenAI and the potential for fraud
As GenAI-enabled fraud schemes evolve, here are a few examples of the fraud we’re already seeing:
- Synthetic identity and deepfake fraud: Many of us have seen examples of deepfakes in the media. These videos, audio recordings, and other synthetic media can impersonate individuals and mimic their speech patterns in a highly realistic way. A closely related and equally malicious type of fraud is synthetic identity creation. By that process, criminals use AI and other tools to forge various identity documents such as driver’s licenses and employee ID cards drawing on real and fraudulent personally identifiable information (PII). In both instances, bad actors exploit free, low-cost AI and readily available tools to evade human detection and elude less advanced authentication systems.
- Forged documents and financial statement manipulation: Bad actors can create highly convincing forged documents or reports (e.g., invoices, bank statements, shipping documents) that may bear replicated watermarks, letterheads, and even signatures. Such increased sophistication makes it more challenging for traditional verification processes to detect fraudulent documentation. Moreover, bad actors can use GenAI to create synthetic transactions. Innocuous and legitimate looking, they can find their way into operational systems such as point-of-sale terminals, inventory management systems, or enterprise resource planning (ERP) platforms.
Impact and steps you can take to protect your organization
Beyond financial losses, AI-enabled fraud can put an organization’s trust, credibility, and brand at risk. If a company fails to protect its stakeholders or itself, it can lose the confidence of customers, investors, employees, and other stakeholders.
So how can companies protect themselves? Deloitte has identified some specific steps your organization can take to bolster your fraud risk management framework and defend against AI-enabled fraud.
- Risk assessment: Identify potential AI fraud vectors relevant to your organization, assess their likelihood and impact, and evaluate the effectiveness of existing controls. Consider GenAI’s emergent capabilities, including advanced reasoning and pattern recognition, as you develop and test your response plans for various AI fraud scenarios.
- Access and approval systems: Establish multiple levels of approval and implement multifactor authentication to verify identities for authorized and pertinent personnel dealing with cash disbursements and other transactions that require approval to help reduce the risk of AI-driven fraud. Schemes targeting cash disbursements are often cloaked in a sense of urgency and a false face of authority. Multiple levels of approval can also slow the process and provide greater opportunity to identify suspicious attributes or markers for certain transactions. All told, multifactor authentication can foil fraud attempts by making it more difficult for those using GenAI to impersonate employees authorized to approve transactions.
- Verification of documents: Implement rigorous verification processes for documents originating from third parties to combat the risk of AI-generated fraudulent documentation. For example, organizations can establish direct communication channels with issuers of critical documents rather than merely accepting provided documents at face value. Moreover, organizations can draw on independent sources and databases to cross-verify information. A multifaceted approach to verification can reduce the risk of your company falling victim to sophisticated, fraudulent AI-generated documentation.
- Collaboration and information sharing: Establish a multidisciplinary team (e.g., internal audit, risk management, IT, cybersecurity, and professionals from other functions) to monitor relevant advances in AI technology and regularly update risk assessments, security protocols, and fraud detection systems geared to emerging AI capabilities.
- Training and communication: Improve training so you can increase employee awareness of new and evolving types of fraud while also reinforcing appropriate courses of action to remedy any breaches.
What role can Deloitte play?
Deloitte can advise you on identifying and responding to AI-enabled fraud. We have extensive experience with fraud risk management, the three lines of defense model, and other fraud prevention measures. To learn more, reach out to Ryan Hittner or Kirk Petrie
This publication contains general information only and Deloitte is not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services. This publication is not a substitute for such professional advice or services, nor should it be used as a basis for any decision or action that may affect your business. Before making any decision or taking any action that may affect your business, you should consult a qualified professional advisor. Deloitte shall not be responsible for any loss sustained by any person who relies on this publication.
The services described herein are illustrative in nature and are intended to demonstrate our experience and capabilities in these areas; however, due to independence restrictions that may apply to audit clients (including affiliates) of Deloitte & Touche LLP, we may be unable to provide certain services based on individual facts and circumstance.
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Ryan Hittner
Ryan is an Audit & Assurance principal with more than 20 years of experience helping global institutions strengthen trust, transparency, and performance across complex analytical, financial, and artificial intelligence (AI) systems. His work brings together deep experience in risk management, governance, controls, valuation, modeling, data, automation, and emerging technology to help clients navigate transformation with confidence. Ryan serves as Deloitte’s Global AI Specialist Leader, leading a team of AI professionals who support assessments of AI systems and advise non-attest clients on large-scale AI strategy and governance transformations. His work focuses on helping organizations understand, govern, and manage the business, risk, and control implications of AI, advanced algorithms, and emerging agentic systems. Ryan also serves as Deputy Leader of Deloitte’s Valuation & Analytics practice, a global network of professionals with deep experience across traded financial instruments, data analytics, modeling, and valuation. In this role, he leads Deloitte’s Omnia DNAV AI and Derivatives technologies, which incorporate automation, machine learning, and large-scale data to enhance the delivery of valuation and analytics services. Previously, Ryan served as a leader in Deloitte’s Model Risk Management practice, where he advised financial services institutions on model development, validation, governance, technology enablement, and quantitative risk management. He has led multidisciplinary teams serving several of the top 10 US financial institutions on complex risk, control, and process transformation programs. Ryan frequently serves as a trusted advisor to CEOs, CFOs, CROs, boards, and audit committees on issues at the intersection of risk, technology, governance, financial markets, and business transformation. His experience spans AI and algorithmic risk, model risk management, financial risks and valuation. Ryan received a BA in Computer Science and a BA in Mathematics & Economics from Lafayette College. His work sits at the intersection of financial risk, valuation, modeling, data, automation, machine learning, and AI, helping clients strengthen trust, transparency, and business value across critical decision-making processes. Media highlights and perspectives Ryan has authored many thought leadership articles and blogs and his commentary has been featured in publications including Accounting Today, CFO Dive, Strategic Finance Magazine, and the Wall Street Journal. 2026 [Strategic Finance Magazine] Optimizing AI with Good Governance [Accounting Today] Internal audit’s role in guiding AI responsibly [Internal Auditor Magazine] AI Unleashed [Deloitte blog] COSO AI framework: Internal controls for generative AI 2025 [Deloitte blog] Internal Audit’s role in strengthening AI governance [Deloitte blog] The impact of AI on your audit: Supporting AI transparency and reliability in finance and accounting [Deloitte blog] Generative AI in Financial Reporting and Accounting [WSJ Risk & Compliance Journal] A Day in the Life of an Accounting Generative AI User [FEI Weekly] AI in Finance: Balancing Innovation, Accuracy, and Audit Readiness [Accounting Today] Auditors, management prepare for AI impact on financial data 2024 [Deloitte blog] Mitigating AI fraud risks [Deloitte perspectives] Underscoring the role of AI in investment management [NACD report] NACD 2024 Governance Outlook Report [FM Magazine] What CFOs Need to Know About AI Risk [Internal Auditor] The Fraudsters Have AI, Too [CFO Dive] Bolstering your cyber defenses in the age of AI 2023 [Deloitte perspectives] Perspective on New York City local law 144-21 and preparation for bias audits [Deloitte blog] Reduce AI risk and promote AI trust [Deloitte perspectives] What is an Algorithm? Let’s Demystify Algorithms and Artificial Intelligence (AI) [Pitchbook] Road to Next 2022 [Deloitte perspectives] An Auditor’s Mindset in an AI Driven World | Deloitte US [WSJ article] First Bias Audit Law Starts to Set Stage for Trustworthy AI 2021 [Deloitte perspectives] Applying COSO ERM framework principles to AI
Kirk Petrie
With a rich background in technology and analytics, business and forensic consulting, and executive leadership, I currently lead the fraud analytics group within Deloitte’s Audit & Assurance business. In this role, I lead teams of seasoned analytic professionals who deliver client services and develop technological solutions focused on financial statement fraud risk sensing. Throughout my career, I have led numerous client engagements, offering services in enterprise risk, innovative analytic enablement, large-scale forensic investigations, and risk program initiatives. My experience spans both the commercial and public sectors, addressing challenges such as fraud and financial crimes, anti-bribery and corruption strategies, anti-counterfeiting, brand protection, claims management, ethics and compliance, and business reorganization. I have developed a deep understanding of cutting-edge technologies, notably in the realm of data science and artificial intelligence. As an accomplished Python programmer, I proficiently employ advanced analytics techniques, including machine learning, natural language processing, and data visualization, to address the needs of clients and stakeholders. This proficiency allows me to efficiently process large datasets, uncover hidden patterns, and extract meaningful insights for our business teams. My current focus is on generative AI, exploring and implementing various large language models and related frameworks to augment our traditional analytic capabilities. I'm particularly interested in leveraging this technology for advanced reasoning and logic applications. The technology’s emerging ability to emulate human-like reasoning opens up new solutioning possibilities and is pushing the boundaries of what we can achieve in risk analysis and fraud prevention. To effectively bridge the gap between complex technical solutions and practical business applications, I've pursued a unique combination of professional credentials that reflect both my business acumen and technological experience. On the business side, I'm a Certified Public Accountant (CPA), Certified Fraud Examiner (CFE), and Certified Insolvency and Reorganization Advisor (CIRA). These are complemented by my diverse technology certifications, including in cloud and Python programming. I've also completed several professional programs in data science, computer science, and AI through institutions such as the Massachusetts Institute of Technology (MIT), the University of California-Berkeley, and Cornell University.