AML Judgment Gap Report · Full findings
Insurance
This is a specimen. The cases, the weights, the methods and the sources are real, and are what your team would sit and what your own report would cite. The scores are invented, for a hypothetical cohort of 14 people. A real report carries your own results and nothing else.
Your team detects 5 of the 10 money laundering methods that apply to this sector. 2 need action.
2 of these are urgent. Your team was tested on them and missed them.
Your assessment is 10 cases, not one. Each covers a different part of your exposure, and the appendix shows how many of your 10 methods each one carries. Measured against the methods that apply to this sector, not against other firms.
Since the last sitting
September cohort against March cohort. Your team detected 0 methods then and 5 now. 1 went backwards.
What to do
For each one, ask a single question. Does the team not know the method, or do they know it and have no rule that would surface it? The first needs a briefing. The second is a control gap, and it is the more serious answer.
- High
- Tested and missed, on a case covering a large part of your exposure.
- Medium
- Tested and missed on a smaller case, or never tested on one that matters.
- Low
- Never tested, and a small part of your exposure.
Ordered by priority. The reason for each is printed with it, so you can disagree with the ranking.
- 01
Bribery Conduits and Consultancy Payments
HighYour team was tested on this and missed it. It sits in The Policy Book, which covers 7 of the 10 methods that apply to you.
- Result
- Caught 45% of the laundering customer's alerts.
- Tested by
- The Policy Book — covers 7 of your 10 methods
Now · BriefSend the team the register entry. It has the mechanism, the signal and the sources.
30 days · ControlWhich rule, report or alert would surface this?
Consultancy receipts from jurisdictions where the recipient holds influence, payments unconnected to any deliverable, and timing correlated with contract awards.
90 days · Re-testSit The Policy Book again, on the version the team has not seen.
OwnerTarget date - 02
Sanctions-Evasion Ownership Restructuring
HighYour team was tested on this and missed it. It sits in The Policy Book, which covers 7 of the 10 methods that apply to you.
- Result
- Caught 45% of the laundering customer's alerts.
- Tested by
- The Policy Book — covers 7 of your 10 methods
Now · BriefSend the team the register entry. It has the mechanism, the signal and the sources.
30 days · ControlWhich rule, report or alert would surface this?
Ownership changes closely following a designation date, incoming owners with no commercial history, and unchanged management across the restructuring.
90 days · Re-testSit The Policy Book again, on the version the team has not seen.
OwnerTarget date
On your own report
Each line carries your team’s result, an owner and a date. The re-test at 90 days shows what has moved.
Appendix
Evidence
Everything the finding above rests on, for anyone who wants to check it.
By case
The 10 cases that make up your assessment. Detection rate is the share of the laundering customer’s alerts the team caught. The last column counts people who escalated everything, which catches the laundering customer without deciding anything and scores badly for that reason.
| Case | Your methods | Share of assessment | Runs | Median mark | Detection rate | Escalated everything |
|---|---|---|---|---|---|---|
| The Policy Book | 7 | 28% | 14 | 49 | 45% | 3 of 14 |
| The Verification Desk | 5 | 23% | 14 | 87 | 84% | 3 of 14 |
| The Relationship Review | 3 | 14% | 14 | 50 | 46% | 2 of 14 |
| The Betting Account | 1 | 5% | 14 | 67 | 63% | 2 of 14 |
| The Client Account | 1 | 5% | 14 | 80 | 77% | 3 of 14 |
| The Exchange Desk | 1 | 5% | 14 | 69 | 66% | 3 of 14 |
| The Incoming Payment | 1 | 5% | 14 | 69 | 65% | 3 of 14 |
| The Onboarding Interview | 1 | 5% | 14 | 87 | — | — |
| The Securities Book | 1 | 5% | 14 | 53 | 50% | 3 of 14 |
| The Sponsorship File | 1 | 5% | 14 | 42 | 39% | 3 of 14 |
Every method
All 10 methods that apply to this sector, and where each one is documented. Full citations are at amlbenchmark.com/coverage.
| Method | Case | Rate | Result |
|---|---|---|---|
| Bribery Conduits and Consultancy PaymentsOperation Lava Jato: in December 2016 Odebrecht and Braskem admitted paying approximately US$788m in bribes to officials across a… | The Policy Book | 45% | Missed |
| Sanctions-Evasion Ownership RestructuringOFSI and FCDO joint guidance on the meaning of ownership and control under UK sanctions, issued following Mints v National Bank… | The Policy Book | 45% | Missed |
| Insurance Product Misuserarely trainedFATF, Guidance for a Risk-Based Approach for the Life Insurance Sector (October 2018), developed with the private sector; and… | The Incoming Payment | 65% | Partial |
| Necrofinance: dead directors and zombie accountsrarely trainedICIJ Panama Papers investigation (2016) into Mossack Fonseca | The Client Account | 77% | Partial |
| Beneficial Ownership ObfuscationThe two largest beneficial ownership regimes moved in opposite directions within a year, and a structure is now easier to hide in… | The Onboarding Interview | — | Partial |
| Deepfake-Enabled Payment Instruction Fraudrarely trainedArup, Hong Kong (January 2024): 15 transfers totalling approximately HK$200m (about US$25.6m) executed in a single day after a… | The Verification Desk | 84% | Detected |
| Laundering and Fraud as a Servicerarely trainedFATF, Professional Money Laundering (26 July 2018), describing professional launderers, organisations and networks that launder… | The Verification Desk | 84% | Detected |
| Synthetic and AI-Generated Onboarding Documentsrarely trainedFinCEN Alert FIN-2024-Alert004 (13 November 2024) on fraud schemes using generative AI to circumvent identity verification… | The Verification Desk | 84% | Detected |
| Synthetic Identities at Scalerarely trainedUS Federal Reserve payments-improvement material on the transformation of synthetic identity fraud by generative AI; industry… | The Verification Desk | 84% | Detected |
| Synthetic Voice Against Telephone and Callback Controlsrarely trainedFinCEN Alert FIN-2024-Alert004 (13 November 2024), whose red flags cover GenAI-assisted impersonation used to circumvent identity… | The Verification Desk | 84% | Detected |
How this was measured
Each case is built around one customer who is laundering money. The rate is the share of that customer’s alerts the team caught.
- Detected
- Four fifths of them or more.
- Partial
- Between a half and four fifths.
- Missed
- Half or fewer.
- Untested
- No one has sat a case covering it.
Nothing is reported as detected on the strength of a good overall mark. Findings are suppressed below 3 runs on a case, because a smaller number describes one analyst rather than a team. Methods are declared on the case, not the individual alert, so this reports whether the team detected the method a case is built around rather than scoring each method separately.