Read-only view: browsing is open, changes need a signed-in user.
Staging: test environment for new releases. Data may be reset; do not share from here.
WatchtowerSignicat competitor intelligence

Feed

Reset
Napier· 22 Oct 2026 L3 · Notable

Napier AI and GlobalData published the Napier AI / AML Index 2026–2027, covering 42 markets, with a global loss estimate modelled across 161 countries.

Napier AI / AML Index 2026–2027: three takeaways as money laundering losses fall for the first time ↗ · repeat of an earlier article

What happened

  • The Index estimates global money laundering losses at $5.09 trillion (USD), equal to 4.30 per cent of global GDP, down $203 billion (USD) year-on-year.
  • Global AML compliance cost an estimated $227.95 billion (USD) last year, down 4.9 per cent from $239.74 billion.
  • The Index estimates $143.08 billion (USD) in potential AI-driven AML savings remains unrealised across the 42 markets assessed.
  • The Index ranks the Czech Republic first of 42 markets with a score of 1.81, where lower is better.

Why it matters to Signicat

  • Napier frames AML and AI-driven detection as the value case for compliance teams, a sales narrative adjacent to Signicat's risk and AML screening line.
  • Report data on AI-driven savings and explainability requirements is relevant to Signicat's risk and AML screening positioning in Nordic and Benelux banking.
Evidence from the source (6 quotes)
  • “Our research found that an estimated $5.09 trillion (USD) was laundered globally last year, equivalent to 4.30 per cent of global GDP. Losses fell by $203 billion (USD), or 3.84 per cent, year-on-year” source ↗
  • “Global AML compliance cost an estimated $227.95 billion (USD) last year, down from $239.74 billion” source ↗
  • “The Index estimates $143.08 billion (USD) in potential AI-driven savings remains unrealised across the 42 markets assessed.” source ↗
  • “The Czech Republic The strongest overall performer, with an Index score of 1.81. Canada ranks second.” source ↗
  • “Better detection and more robust underlying data, underpinned by AI, give compliance teams a more accurate picture of their financial risk” source ↗
  • “That depends on AI that is explainable, auditable, and with accountability owned by people.” source ↗
AML KYB screeningAgentic AI identityResearch reportGlobal

5 of 5 facts verified against the source · confidence high · claude-haiku-5-5