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Financial Crimes

Financial Crimes/Fraud/Anti Money Laundering (AML)

fin_crimes_flow

The pipe_financial_crimes Combine wire transfers and various watchlists and enrich with rules to calculate a risk score to identify potentially nefarious transactions.

Datasets

  1. ds_person_watchlist This dataset contains a list of individuals who are on a watchlist, with their full names and the reasons for their inclusion. The format of this dataset is not specified, but it is likely to be in a structured format such as a database or spreadsheet. This data is useful for security and law enforcement purposes, allowing for the identification and tracking of individuals who may pose a threat or be involved in criminal activity.

  2. ds_country_watchlist This dataset contains a list of countries and their associated issues that require monitoring. The data is not stored in any particular format and can be accessed through various means. This dataset is useful for tracking global events and identifying potential risks or opportunities in different regions. It can be used by analysts, researchers, and policymakers to make informed decisions and take appropriate actions.

  3. ds_wire_transfers This dataset contains information on wire transfers, including transaction IDs, first and last names of the sender and recipient, bank details of both parties, originating and destination countries, and transaction amounts. The dataset is currently in an unspecified format. This data is useful for analyzing international money transfers, detecting fraudulent activities, and monitoring financial transactions. It can also be used to gain insights into customer behavior and preferences.

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