Fraud is not a problem that is being solved. It is a problem that is scaling. A comprehensive industry report released April 24, 2026 delivers a stark projection: global losses from digital payments and e-commerce fraud will more than double from $40 billion in 2024 to over $100 billion by 2029. That is not a worst-case scenario. That is the baseline.
The “Fraud, Scams, and Risk in Digital Payments and E-Commerce 2026: Global Market Overview, Key Metrics, and Outlook” report draws on regulatory filings, law enforcement data, financial institution disclosures, and payment processor incident reports across dozens of jurisdictions. Its headline number — $100 billion — reflects a convergence of forces that are accelerating simultaneously: the expansion of digital payments into new markets and populations, the industrialization of fraud through AI, and the persistent gap between fraud infrastructure and the defenses being deployed against it.
The Numbers, Broken Down
E-commerce and digital payments fraud: $40 billion in 2024, projected to exceed $100 billion by 2029. This category covers payment card fraud, account takeover, unauthorized transactions, fake merchant fraud, and return/refund abuse across digital commerce channels.
Financial institution fraud losses: Less than $25 billion in 2025, projected to rise over 150% to more than $55.3 billion by 2030. This reflects fraud directly affecting banks, credit unions, and payment processors — including authorized push payment (APP) fraud, where victims are manipulated into sending money directly, and synthetic identity fraud.
Cryptocurrency scam losses per victim: Average individual crypto scam payment values increased by more than 250% in one year — from under $800 per payment in 2024 to over $2,750 in 2025. This reflects both the increasing sophistication of crypto fraud and the shift toward targeting higher-net-worth victims with more elaborate, longer-duration scams like pig butchering.
Card payment fraud: Cumulative global losses over the next decade are estimated at over $400 billion.
What Is Driving the Growth
AI as a Force Multiplier
The report identifies artificial intelligence as the single most significant factor reshaping both the scale and the nature of fraud. AI is not merely making existing scams more convincing — it is fundamentally changing the economics of fraud by enabling one operator to run what previously required dozens of human workers.
Key AI-enabled capabilities driving the projections:
- Voice synthesis and cloning — enabling real-time impersonation of family members, bank representatives, and government officials at scale
- Deepfake video — enabling fake KYC (know-your-customer) verification, fake interview candidates, and fabricated video evidence used in scam scenarios
- AI-driven social engineering — chatbots capable of conducting multi-week relationship-building operations for romance and investment fraud without human oversight
- Automated document generation — fake bank statements, tax documents, legal notices, and government correspondence indistinguishable from genuine documents
- Large-scale phishing optimization — AI systems that test and iterate phishing message variants in real time to maximize click-through rates
The report notes a structural tension: the same AI capabilities that enable fraud also enable detection and response. But fraud operators have historically adapted faster than defenders, because they operate with no compliance overhead and no legal constraints.
Digital Payment Expansion
As digital payments penetrate new markets — particularly in South and Southeast Asia, Sub-Saharan Africa, and Latin America — they bring new populations of users who have limited fraud awareness, limited recourse when victimized, and who are being aggressively targeted by fraud networks that have already exhausted easier targets in more mature markets.
First-time digital payment users are statistically the most vulnerable to fraud — they haven’t developed the pattern recognition to identify suspicious activity, and they are less familiar with what legitimate institutional communication looks like.
The Authorized Payment Problem
A significant portion of the projected growth comes not from unauthorized transactions — where fraud liability typically falls on financial institutions — but from authorized push payment (APP) fraud, where victims are psychologically manipulated into sending money willingly. APP fraud is the mechanism behind romance scams, pig butchering, emergency scams, and business email compromise.
From a technical standpoint, APP fraud looks identical to a legitimate transaction. The victim’s bank sees an authorized payment from an authenticated account to a destination the victim has chosen. This makes it extremely difficult to detect and nearly impossible to reverse once executed.
The Cryptocurrency Dimension
The 250% jump in average crypto scam payment size in a single year is among the most alarming data points in the report. It reflects a deliberate targeting shift: scam operations are increasingly filtering toward victims with higher income, greater investment experience, and larger savings — because the return on investment for a more elaborate, longer-duration scam is substantially higher.
Pig-butchering operations in Southeast Asia have evolved their targeting criteria over the past two years. Early operations cast wide nets. Current operations use data enrichment — purchased from data brokers, leaked from breaches, or scraped from LinkedIn and financial forums — to identify and prioritize targets with verifiable wealth indicators.
A victim who can be cultivated for three months and defrauded of $200,000 generates more revenue than 100 victims defrauded of $1,500 each, while requiring roughly the same operational overhead.
The FBI’s 2025 IC3 report confirmed this pattern: cryptocurrency investment fraud was the highest-value cybercrime category with $6.57 billion in reported losses, driven disproportionately by a smaller number of very large individual losses.
The Accountability Gap
One of the report’s most significant findings is the persistent gap between fraud losses and fraud accountability. Despite record enforcement actions, record asset seizures, and unprecedented international cooperation, criminal prosecution rates for fraud remain extraordinarily low relative to the volume of activity.
The reasons are structural:
- Fraud is transnational by design — the victim, the criminal, the infrastructure, and the money are typically in different jurisdictions
- Cryptocurrency enables rapid, difficult-to-reverse fund movement across jurisdictions
- The most successful fraud operations are insulated behind layers of money mules, shell companies, and front businesses
- Law enforcement resources dedicated to fraud investigation are dwarfed by the scale of the activity
The $700 million in crypto restrained by the DOJ’s Myanmar operation this week — significant as it is — represents less than 0.1% of annual pig-butchering losses.
What the Trajectory Means
If the report’s projections hold, global fraud losses will exceed the GDP of dozens of countries by 2029. More practically: the average digital payment user will face a fraud ecosystem that is twice as well-resourced, twice as sophisticated, and twice as aggressive as the one that exists today.
For individuals, that means the baseline protective behaviors that may have been sufficient in 2024 — checking for HTTPS, not clicking suspicious links, using strong passwords — will be insufficient against AI-enhanced targeting that knows your name, your employer, your transaction history, and your emotional vulnerabilities.
The single most effective protection remains behavioral: treat any unsolicited contact requesting money, credentials, or urgent action with categorical suspicion — regardless of how legitimate it appears, regardless of what personal information the contact demonstrates, and regardless of the emotional pressure it creates.
For businesses operating in the digital payments space, the report’s message is equally clear: fraud losses are no longer an acceptable line item. They are an existential scaling problem that requires investment in AI-native detection infrastructure commensurate with the threat.
Sources: GlobeNewswire · FBI IC3 2025 Annual Report · ASIS Online
