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Financial Intelligence Analysis⚓︎

  • Regulated Entity(RE) population, and
  • Parties within transaction reports (customers of the Regulated Entities).

The initiating event for analysis maybe: proactive (identified by the agency), or reactive (from an outside request). The below list provides some examples of the analysis performed by Financial Intelligence agencies broken down by the initiating type of event and focus of analysis:

1. Proactive analysis into Regulated Entities

  • Comparative analysis of transaction reporting across similar REs (or all the regulated entities in a sector). Significant differences in reporting volumne, value, submission delay, etc... might indicate under/over reporting.
  • Comparative analysis of transaction reporting across time for a single RE. Anomalies might indicate IT system issues that resulted in gaps in submitted reports.
  • Data matching of RES against other data sources (e.g. business registers) that may identify missing entities from the Regulated Entity Dataset.
  • Analysis of reporting to identify potentially duplicated reports.

2. Reactive analysis into Regulated Entities

  • Engagement/education and outreach to REs exposed to an emerging risk. For example; in response to a media release, associated to an enforcement action being undertaken by a foreign FIU, the domestic FIU may look to see if the same activity maybe occurring locally. The REs to be contacted would be identified based on their sector, location, reported characteristics or the characteristics of their customers.
  • Outreach to businesses to determine if they are providing designated services and need to be registered, as a result of a Dob-in from a fellow regulator or a member of the public.
  • Public disclosure of non-compliance or other regulatory issues, including disclosures to international regulators.

3. Proactive analysis into Transaction Report Parties

  • Identification of parties with transaction patterns that meet known Money Laundering or Terrorism Financial (ML/TF) micro profiles. E.g. Cash deposits and outgoing international fund transfers.
  • Identifcation of parties with anomolous behaviour (compared to the general population).
  • Analysis into specific parties, related to current active investigations.

4. Reactive analysis into Transaction Report Parties

  • Data matching lists of parties against the transaction reports dataset based on requests from partners.
  • Analysis into parties identified by the media or government partners.
  • Data matching of the transaction reports dataset against other data sources to identify high risk parties (e.g. the Panama Papers).