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Connected money: detecting high-risk transactions with network analytics

Webinar recording

In this webinar with Senzing and OpenSanctions, you will learn how combining entity resolution with connected data analytics can tackle the challenges of disparate data sources when tracing financial transactions.

Prepare for a unique experience featuring a live demo that answers transaction-based questions, reveals relationships, uncovers hidden patterns, and identifies illicit transactions using real data from the Azerbaijani Laundromat case, OpenSanctions, and Companies House.

Agenda

  • Following the money
    Understanding the “Following the Money” mission and how standardization and technology can address the challenges of disparate data sources when tracing financial transactions. Friedrich Lindenberg, Founder of OpenSanctions
  • Turning data into a usable resource for financial crime analysis
    Current approaches to financial crime analysis are often ineffective and resource-intensive. Discover how combining entity resolution with visual analytics can improve financial crime investigations. Boris Kusovski, Director – Financial Markets Strategy at Senzing, Inc.
  • Live demo: answering transaction-based questions
    Live investigation using GraphAware Hume to analyze real data from the $2.9 billion Azerbaijani Laundromat case. We’ll show how to answer transaction-based questions by integrating OpenSanctions and Companies House data and using Senzing entity resolution to reveal hidden connections and expose money laundering activities. Christophe Willemsen, GraphAware CTO

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Connected Money: Detecting High-Risk Transactions With Network Analytics