Sanction Scanner Blog

As the 2026 FIFA World Cup kicks off, a massive surge in AI-driven fraud, ticket scams, match-fixing, and financial crime threatens fans and operators alike. Discover the hidden risks of this tournament and how businesses can defend against them.

Sanction Scanner has been named a G2 Leader in Anti-Money Laundering for the third year in a row, earning 22 placements across four categories in G2's Summer 2026 reports — including four Leader badges and #1 rankings in the AML Mid-Market Results and Usability indexes.

Discover the reason of cross-border monitoring being the highest-risk surface, details about the transit country problem, and country risk framework. Learn about currency mismatch patterns, and beneficiary mapping in cross-border wires in “Cross-Border Transaction Monitoring: Detecting High-Risk Jurisdiction Flows” article. Learn more about the FATF travel rule crossover, and detection patterns. Read more! 

Layering is where money laundering succeeds or fails and where most AML programs fall short. Discover the key detection patterns, network analysis techniques, and regulatory expectations compliance teams need to catch layering before integration happens.

Correspondent banking is the highest-risk AML surface in global finance. Learn wire transfer monitoring, nested relationships, payable-through accounts, KYCC, and ISO 20022.

A definitive guide to threshold tuning and risk based calibration in transaction monitoring   segmentation, statistical baselines, the FP/detection trade off curve, recalibration triggers, and examiner ready documentation.

A practitioner’s guide to writing transaction monitoring rules and scenarios, including rule anatomy, the core rule library, risk based calibration, the false positive trade off, sandbox testing and regulator ready documentation.

Friendly fraud is rising fast and your real customers may be behind it. Learn how first-party fraud works, why chargebacks are exploding, and how to detect and prevent dispute abuse before it hits your bottom line.

A practitioner's guide to money mule detection: onboarding, behavioral, and network signals, why per-account screening misses 80%+ of mules, and how to stop mule accounts within the 24–72h cycle.