Fraud Doesn’t Fly Evenly: A Route-Level Look at Global Air Travel Fraud Risk
Q1 2026 Report
Accertify Global Air Travel Fraud Report: Q1 2026
A Global Analysis of Airline Booking Risk Concentration by Origin City
Executive Summary
Fraud risk in airline bookings is not evenly distributed across markets. Analysis of airline booking transactions processed on the Accertify platform shows meaningful variation in fraud exposure by region and by departure city, with some markets consistently experiencing greater fraud pressure at the point of booking than others.
Routes originating in North America and Australia continue to exhibit lower fraud rates, generally remaining below one percent even among high-volume departure cities. By contrast, several regions – including parts of Latin America, Africa, the Middle East, and South and Southeast Asia – show materially higher concentrations of prevented fraud, with certain departure cities recording fraud rates multiple times higher.
Note on methodology: The fraud rates presented in this report represent prevented fraud – transactions that were denied for a fraud reason before travel occurred. As a result, these figures reflect where fraud prevention systems are most actively intervening, rather than where fraud losses ultimately materialized.
By examining fraud risk at the route-origin level, this report provides airlines with a practical, market-level view of where fraud pressure is most concentrated today – and where sustained investment in fraud prevention has helped maintain lower risk environments.
Regional Comparison: Fraud Risk Varies Significantly By Market
Across the regions included in this analysis, fraud exposure at the point of booking is not evenly distributed. Clear differences emerge when comparing routes originating in North America and Australia with those in other parts of the world.
Departure cities in the United States, Canada, and Australia consistently exhibit lower fraud rates than those observed across Latin America, Africa, the Middle East, and parts of South and Southeast Asia. In these lower-risk markets, fraud rates generally remain well below one percent, even among high-volume routes, reflecting a comparatively stable and mature booking environment.
By contrast, several other regions show materially higher concentrations of prevented fraud, with top departure cities recording fraud rates multiple times higher. While year-over-year improvement is evident in select markets, elevated fraud pressure remains persistent in others, underscoring the uneven nature of fraud risk across global airline routes.
These regional differences point to varying levels of fraud maturity, influenced by factors such as booking behavior, payment risk profiles, and the consistency with which fraud controls are applied. Markets exhibiting lower fraud rates tend to reflect environments where airlines have established longstanding, layered fraud prevention strategies, while higher-risk regions highlight where fraud pressure continues to concentrate at the point of booking.
North America and Australia as Maturity Benchmarks
Routes originating in North America and Australia consistently demonstrate lower fraud rates relative to other regions included in this analysis. These markets exhibit both lower overall fraud exposure and less volatility year over year, even across high-volume departure cities.
This pattern is indicative of more mature fraud prevention environments, where airlines have invested over time in layered controls, real-time decisioning, and continuous optimization of booking-stage defenses. In these regions, fraud prevention systems intervene less frequently not because fraud is absent, but because risk is being effectively suppressed upstream.
By contrast, regions with higher observed fraud rates reflect environments where fraud pressure remains more concentrated at the point of booking, and where controls are required to intervene more often to prevent misuse.
Taken together, the data suggests that lower fraud rates are not accidental. They tend to emerge in markets where fraud prevention is treated as an operational discipline rather than a reactive measure – offering a useful benchmark for airlines operating in higher-risk regions.
Global View: Top 25 Departure Cities By Fraud Rate
The Global Top 25 highlights the departure cities with the highest fraud rates in Q1 2026 across all regions included in the analysis. While these cities vary widely in geography and travel volume, they share a common characteristic: a higher proportion of booking transactions requiring intervention due to suspected fraud. Year-over-year comparisons between Q1 2025 and Q1 2026 further demonstrate that fraud pressure is dynamic, declining in some markets while intensifying in others – reinforcing the importance of continuously reassessing route-level risk exposure.
| Rank | Country | Departure City | Q1 2026 Fraud Rate | Fraud Rate Change YoY | Fraud Rank Change YoY |
|---|---|---|---|---|---|
| 1 | Brazil | Brasilia | 4.37% | +375.86% | ▲ 47 |
| 2 | Tunisia | Tunis | 4.36% | +29.79% | ▲ 9 |
| 3 | Brazil | Sao Paulo | 3.61% | +245.29% | ▲ 40 |
| 4 | Nepal | Kathmandu | 3.43% | -24.91% | ▼ 1 |
| 5 | Brazil | Salvador | 3.16% | +110.51% | ▲ 28 |
| 6 | Ghana | Accra | 3.16% | -48.93% | ▼ 5 |
| 7 | Colombia | Cartagena | 2.80% | -31.14% | – |
| 8 | Lebanon | Beirut | 2.09% | +179.17% | ▲ 47 |
| 9 | Indonesia | Jakarta | 1.90% | -48.39% | – |
| 10 | Morocco | Casablanca | 1.89% | -37.88% | ▼ 2 |
| 11 | Brazil | Belo Horizonte | 1.78% | +169.80% | ▲ 52 |
| 12 | South Africa | Johannesburg | 1.52% | -16.47% | ▼ 10 |
| 13 | Dominican Rep. | Santo Domingo | 1.49% | -19.74% | ▼ 8 |
| 14 | Nigeria | Lagos | 1.45% | -61.82% | ▼ 6 |
| 15 | Egypt | Cairo | 1.43% | -73.02% | ▼ 13 |
| 16 | Colombia | Barranquilla | 1.39% | -60.96% | ▼ 6 |
| 17 | Dominican Rep. | Santiago | 1.38% | +19.81% | ▲ 24 |
| 18 | Kenya | Nairobi | 1.35% | -73.90% | ▼ 14 |
| 19 | Colombia | Cali | 1.34% | -70.32% | ▼ 13 |
| 20 | Ecuador | Quito | 1.33% | -38.58% | ▼ 1 |
| 21 | Colombia | Medellin | 1.31% | -40.30% | ▼ 5 |
| 22 | India | Delhi | 1.29% | -20.01% | ▼ 8 |
| 23 | Brazil | Rio De Janeiro | 1.23% | +30.06% | ▲ 24 |
| 24 | Colombia | Bogota | 1.21% | -49.56% | ▼ 9 |
| 25 | Brazil | Porto Alegre | 1.19% | +158% | ▲ 65 |
Regional Deep Dives
United States
Fraud rates across U.S. departure cities remain comparatively low relative to most international markets. While variation exists among individual cities, overall fraud exposure remains subdued, reflecting a mature booking environment where fraud prevention systems are consistently engaged across high-volume routes.
| Rank | Departure City | Q1 2026 | Fraud Rate Change YoY | Fraud Rank Change YoY |
|---|---|---|---|---|
| 1 | Fresno | 0.25% | +42.72% | ▲ 22 |
| 2 | Memphis | 0.23% | -26.34% | ▼ 4 |
| 3 | Miami | 0.21% | -45.64% | ▼ 2 |
| 4 | Las Vegas | 0.18% | -31.28% | ▼ 3 |
| 5 | New York | 0.18% | -8.78% | ▼ 10 |
| 6 | Fort Lauderdale | 0.18% | -16.28% | ▼ 6 |
| 7 | Bakersfield | 0.17% | +110.37% | ▲ 77 |
| 8 | Los Angeles | 0.16% | -38.35% | – |
| 9 | Honolulu | 0.15% | -23.57% | ▼ 5 |
| 10 | High Point | 0.15% | +221.18% | ▲ 136 |
Canada
Canada’s Top 10 departure cities exhibit a narrow range of fraud rates, with modest year-over-year movement across major markets. This consistency suggests stable booking behavior, while underscoring the importance of monitoring even small changes in fraud rates due to the scale of transaction volumes.
| Rank | Departure City | Q1 2026 | Fraud Rate Change YoY | Fraud Rank Change YoY |
|---|---|---|---|---|
| 1 | Montreal | 0.45% | -28.18% | – |
| 2 | Toronto – Billy Bishop | 0.33% | +21.75% | ▲ 1 |
| 3 | Toronto – Pearson | 0.29% | -6.67% | ▼ 1 |
| 4 | Abbotsford | 0.22% | +53.71% | ▲ 4 |
| 5 | Thunder Bay | 0.20% | +7.56% | ▲ 1 |
| 6 | Ottawa | 0.18% | +5.07% | ▲ 1 |
| 7 | St Johns | 0.16% | +196.00% | ▲ 9 |
| 8 | Vancouver | 0.15% | -36.91% | ▼ 4 |
| 9 | Halifax | 0.13% | -2.75% | – |
| 10 | Winnipeg | 0.10% | +3.79% | – |
Australia + Pacific
Fraud rates across Australia and the Pacific remain low overall, with limited dispersion among departure cities. The consistency across markets points to stable risk conditions, even as cross-border travel demand continues to evolve.
| Rank | Country | Departure City | Q1 2026 | Fraud Rate Change YoY | Fraud Rank Change YoY |
|---|---|---|---|---|---|
| 1 | Guam | Guam | 0.26% | -5.78% | ▼ 1 |
| 2 | Australia | Sydney | 0.12% | +6.97% | ▲ 6 |
| 3 | Australia | Proserpine | 0.11% | -61.49% | ▼ 2 |
| 4 | Australia | Melbourne | 0.10% | -24.31% | ▼ 1 |
| 5 | Australia | Hobart | 0.09% | -21.66% | ▼ 1 |
| 6 | Australia | Perth | 0.09% | -50.35% | ▼ 2 |
| 7 | Australia | Adelaide | 0.09% | -3.05% | ▼ 4 |
| 8 | Australia | Cairns | 0.09% | -22.32% | ▼ 1 |
| 9 | Fiji | Nadi | 0.08% | -64.34% | ▼ 6 |
| 10 | Australia | Brisbane | 0.07% | -21.55% | ▼ 3 |
Europe + United Kingdom
Across Europe and the UK, fraud rates vary more noticeably by departure city. Several leisure-oriented and cross-border travel markets stand out, illustrating how fraud exposure can differ significantly even within geographically proximate areas.
| Rank | Country | Departure City | Q1 2026 | Fraud Rate Change YoY | Fraud Rank Change YoY |
|---|---|---|---|---|---|
| 1 | Turkey | Istanbul | 0.89% | -53.98% | 0 |
| 2 | Greece | Athens | 0.70% | +56.70% | ▲ 5 |
| 3 | Turkey | Cukurova | 0.56% | -1.83% | ▼ 1 |
| 4 | Cyprus | Larnaca | 0.51% | +80.71% | ▲ 9 |
| 5 | Greece | Heraklion | 0.50% | -2.61% | 0 |
| 6 | Iceland | Reykjavik | 0.49% | +305.44% | ▲ 38 |
| 7 | Romania | Cluj | 0.45% | +204.25% | ▲ 24 |
| 8 | Moldova | Chisinau | 0.45% | -33.86% | ▼ 6 |
| 9 | Romania | Bucharest | 0.40% | -6.43% | ▼ 1 |
| 10 | Serbia | Belgrade | 0.33% | +157.04% | ▲ 31 |
East Asia
East Asia continues to demonstrate relatively low fraud rates across major departure cities, with year-over-year improvements evident in several high-volume markets. These trends suggest stable booking behavior across the region’s largest travel hubs.
| Rank | Country | Departure City | Q1 2026 | Fraud Rate Change YoY | Fraud Rank Change YoY |
|---|---|---|---|---|---|
| 1 | Mainland China | Guangzhou | 0.75% | -13.09% | ▼ 1 |
| 2 | Mainland China | Shanghai | 0.56% | -32.05% | ▼ 1 |
| 3 | Mainland China | Beijing | 0.39% | -77.51% | ▼ 2 |
| 4 | Korea, Republic of | Gimpo | 0.21% | +168.89% | ▲ 9 |
| 5 | Korea, Republic of | Seoul | 0.14% | -34.66% | ▼ 2 |
| 6 | Japan | Tokyo | 0.09% | -44.81% | ▼ 3 |
| 7 | Japan | Osaka | 0.09% | -61.44% | ▼ 1 |
| 8 | Chinese Taipei | Kaohsiung | 0.08% | +21.16% | ▲ 8 |
| 9 | Japan | Sapporo | 0.08% | -66.16% | ▼ 4 |
| 10 | Hong Kong SAR, China | Hong Kong | 0.07% | -33.01% | ▼ 1 |
Southeast Asia
Fraud exposure across Southeast Asia varies considerably, with certain destinations showing higher concentrations of prevented fraud. The dispersion across departure cities highlights why regional averages can mask localized spikes in fraud activity.
| Rank | Country | Departure City | Q1 2026 | Fraud Rate Change YoY | Fraud Rank Change YoY |
|---|---|---|---|---|---|
| 1 | Indonesia | Jakarta | 1.90% | -48.39% | – |
| 2 | Philippines | Tacloban | 0.68% | +2.25% | ▲ 5 |
| 3 | Thailand | Phuket | 0.38% | -23.94% | ▼ 9 |
| 4 | Vietnam | Phu Quoc | 0.38% | +93.77% | ▲ 13 |
| 5 | Malaysia | Kuala Lumpur | 0.38% | -78.13% | ▼ 3 |
| 6 | Philippines | Manila | 0.35% | -69.79% | ▼ 2 |
| 7 | Philippines | Cebu | 0.35% | -44.01% | ▼ 1 |
| 8 | Thailand | Bangkok – Don Mueang | 0.34% | -44.33% | ▼ 1 |
| 9 | Thailand | Bangkok | 0.28% | -82.55% | ▼ 6 |
| 10 | Vietnam | Ho Chi Minh City | 0.25% | -61.95% | ▼ 4 |
South Asia
South Asia exhibits some of the widest variation in fraud rates among departure cities, with a small number of markets accounting for a disproportionate share of prevented fraud activity. These patterns highlight the importance of route-level visibility in high-growth travel markets.
| Rank | Country | Departure City | Q1 2026 | Fraud Rate Change YoY | Fraud Rank Change YoY |
|---|---|---|---|---|---|
| 1 | Nepal | Kathmandu | 3.43% | -24.91% | – |
| 2 | India | Delhi | 1.29% | -20.01% | ▼ 1 |
| 3 | India | Hyderabad | 0.85% | -1.42% | ▼ 2 |
| 4 | India | Calcutta | 0.84% | -37.01% | – |
| 5 | India | Bangalore | 0.77% | +24.21% | ▲ 2 |
| 6 | India | Ahmedabad | 0.69% | -0.96% | – |
| 7 | India | Amritsar | 0.65% | +17.37% | ▲ 2 |
| 8 | Sri Lanka | Colombo | 0.31% | -33.93% | ▼ 2 |
| 9 | India | Mumbai | 0.29% | -48.25% | ▼ 1 |
| 10 | India | Chennai | 0.29% | -83.91% | ▼ 8 |
Latin America & Caribbean
Latin America and the Caribbean remain among the regions with the most concentrated fraud activity, particularly across several Brazilian and Colombian departure cities. Although fraud rates declined in select markets compared to Q1 2025, they remain elevated relative to global averages.
| Rank | Country | Departure City | Q1 2026 | Fraud Rate Change YoY | Fraud Rank Change YoY |
|---|---|---|---|---|---|
| 1 | Brazil | Brasilia | 4.37% | +376% | ▲ 20 |
| 2 | Brazil | Sao Paulo | 3.61% | +245% | ▲ 13 |
| 3 | Brazil | Salvador | 3.16% | +111% | ▲ 9 |
| 4 | Colombia | Cartagena | 2.80% | -31% | ▼ 1 |
| 5 | Brazil | Belo Horizonte | 1.78% | +170% | ▲ 19 |
| 6 | Dominican Rep. | Santo Domingo | 1.49% | -20% | ▼ 4 |
| 7 | Colombia | Barranquilla | 1.39% | -61% | ▼ 3 |
| 8 | Dominican Rep. | Santiago | 1.38% | +20% | ▲ 8 |
| 9 | Colombia | Cali | 1.34% | -70% | ▼ 7 |
| 10 | Ecuador | Quito | 1.33% | -39% | ▼ 1 |
Middle East & Africa
The Middle East and Africa region includes several of the highest-risk departure cities observed in the analysis. While improvements are visible in some markets, elevated fraud pressure persists across others, emphasizing the continued importance of localized fraud management strategies.
| Rank | Country | Departure City | Q1 2026 | Fraud Rate Change YoY | Fraud Rank Change YoY |
|---|---|---|---|---|---|
| 1 | Tunisia | Tunis | 4.36% | +29.79% | ▲ 3 |
| 2 | Ghana | Accra | 3.16% | -48.93% | ▼ 1 |
| 3 | Morocco | Casablanca | 1.89% | -37.88% | ▼ 2 |
| 4 | South Africa | Johannesburg | 1.52% | -16.47% | ▼ 3 |
| 5 | Egypt | Cairo | 1.43% | -73.02% | ▼ 3 |
| 6 | Kenya | Nairobi | 1.35% | -73.90% | ▼ 3 |
| 7 | Saudi Arabia | Jeddah | 0.91% | -62.72% | ▼ 1 |
| 8 | South Africa | Cape Town | 0.67% | -32.12% | ▼ 5 |
| 9 | United Arab Emirates | Dubai | 0.64% | -51.01% | ▼ 3 |
| 10 | Saudi Arabia | Riyadh | 0.54% | -69.31% | ▼ 1 |
How to Interpret These Rankings
Fraud rates in this report represent prevented fraud, defined as the percentage of booking transactions denied for a fraud reason during the period analyzed. These figures reflect where Accertify’s fraud prevention platform intervened, rather than confirmed fraud losses.
Departure cities are presented as a proxy for route origin, enabling consistent comparison of booking behavior across markets. The rankings are not intended to assess airline performance, airport operations, or physical security conditions at specific locations.
Methodology
This analysis is based on airline booking transactions processed on the Accertify platform during Q1 2026, with year-over-year comparisons to Q1 2025.
In total, the analysis examined more than 180 million airline booking transactions spanning 594 departure cities worldwide, providing a broad view of global booking-stage fraud risk distribution.
To ensure statistical relevance, only departure cities with at least 10,000 booking transactions during the quarter were included in the final rankings.
Within each region, departure cities were ranked in descending order by Q1 2026 fraud rate, defined as the percentage of transactions denied for a fraud reason relative to total transaction volume during the period. The change in fraud rate represents the relative percentage change in fraud rate compared to the previous period, calculated as the difference between Q1 2026 and Q1 2025 fraud rates divided by the Q1 2025 fraud rate.
Fraud rank change reflects how a city’s position has shifted compared to Q1 2025 within the same regional cohort shown in each table. Results are presented by departure city as a proxy for route origin, reflecting market-level booking behavior observed during the quarter.
Closing Insight
Understanding where fraud is being actively prevented provides global airlines with a more practical lens into today’s risk landscape than regional averages alone. Route-level insight enables more precise prioritization of controls, resources, and monitoring – particularly as booking patterns and fraud tactics continue to evolve across global markets.
Fraud detection is based on a combination of transactional, technical, and risk-based signals. Geographic information, where used, is only one of many non-determinative inputs and is not used in isolation to make recommendations. Final fraud determinations, including approval or decline decisions, are made by Accertify clients in accordance with their own policies, procedures, and risk tolerance.