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22/07/2026 4:38 pm
TL;DR: Payment fraud bypass rose to 2.8%, account takeover attempts fell to 0.88%, and chargebacks increased 19% to 0.31%, indicating attackers are targeting fewer, higher-value accounts while losses increase, according to Sift’s Q2 2026 benchmarking. The practical lesson is that block rate alone is no longer a reliable success metric; teams need cost-per-attack and dispute-lag visibility.
NHIMG editorial — based on content published by Sift: When Fraud Gets Targeted, Q2 2026 benchmarks reveal the shift
By the numbers:
- Payment fraud bypass rate held steady at 2.8% in Q2 2026, essentially flat quarter over quarter and down 14% year over year from Q2 2025.
- Manual review rate declined 13.5% to 2.1% from 2.4% in Q1.
- Account takeover attempts declined to 0.88% in Q2 from 0.95% in Q1, a 7% quarterly improvement.
Questions worth separating out
Q: How should fraud teams respond when attack volume falls but chargebacks rise?
A: They should stop treating block rate as the primary success metric and start measuring cost per successful attack, dispute lag, and account-value concentration.
Q: Why do trusted accounts create more fraud loss than obvious new attacks?
A: Trusted accounts already carry behavioural history, payment permissions, and user confidence, so malicious actions blend in more easily.
Q: What do security teams get wrong about manual review efficiency?
A: They often assume a lower manual review rate means better fraud prevention.
Practitioner guidance
- Reweight fraud scoring toward trusted-account compromise Tune decisioning to penalise improbable activity on established accounts even when device, payment method, and customer history look normal.
- Link identity assurance to payment controls Feed authentication strength, step-up events, and recent credential changes into payment risk decisions so a clean transaction cannot override a compromised identity context.
- Track chargebacks as a delayed control signal Build a reporting view that compares real-time block rates with later dispute outcomes by cohort, vertical, and account age so you can see where fast approvals are hiding losses.
What's in the full report
Sift's full article covers the operational detail this post intentionally leaves for the source:
- Vertical-by-vertical benchmark data showing where fraud pressure is concentrating across Internet and Software, Online Gambling, Digital Commerce, and Finance.
- Breakdowns of payment fraud, account takeover, manual review, and chargeback trends that support internal benchmarking and board reporting.
- The article's interpretation of how better automation can still coincide with rising disputes when thresholds are tuned to the wrong signal mix.
- Context on how 2FA adoption and stored credential behaviour influence fraud outcomes in different business models.
👉 Read Sift's Q2 2026 fraud benchmarking analysis on chargebacks and ATO →
Chargebacks and account takeover are diverging, what should teams change?
Explore further
22/07/2026 4:42 pm
Selective fraud is now a governance problem, not just a detection problem. When attackers focus on high-value accounts, the issue becomes how trust is granted and maintained across the account lifecycle. Fraud teams that only measure block rates miss the downstream loss pattern, especially where disputes surface after settlement. That makes identity assurance, authentication strength, and behavioural context part of the same governance conversation.
A question worth separating out:
Q: Which accountability model should organisations use when identity compromise drives fraud losses?
A: Accountability should be shared across fraud, IAM, and customer risk teams because the loss originates in identity trust but surfaces in payment and finance. If each team owns only its own metric, the compromise path falls between functions. A shared control model, with one view of authentication, session risk, and dispute outcomes, is the only practical answer.
👉 Read our full editorial: Fraud is shifting to high-value accounts as chargeback losses rise
