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Data de începere a cursuluijoi, 23 iulie 2020

Corruption and money laundering investigations often involve complex networks of individuals, companies, and other entities. Presenting these structures clearly to supervisors, colleagues, or in court can be challenging. A well-structured graph or diagram illustrating relationships between entities and financial flows makes it easier for others to understand the case.

In this course, you will learn to use the **free yEd software** to create clear, professional, and interpretable graphs to enhance your investigations.

What You Will Learn

Take your skills to the next level by mastering how to:

  • Create clear and structured graphs to represent entities in an investigation.
  • Visualize meaningful connections between entities to reveal hidden relationships.
  • Customize entity representations with personalized images.
  • Use layout functions to optimize graph structure in just a few clicks.
  • Import Excel data to automatically generate financial flow diagrams.
  • Add visual enhancements, such as thicker connection lines to indicate larger monetary transactions.
  • Export graphs to PowerPoint and other formats for seamless reporting.

Course Format

  • Self-paced: Learn at your own convenience.
  • Structured sessions: Designed to build on each other—start with Session 1 for the best experience.
  • Recommended device: Laptop or desktop for optimal learning.

Who Should Take This Course?

  • Financial investigators
  • Law enforcement officers
  • Anti-money laundering (AML) professionals
  • Compliance officers
  • Prosecutors and legal professionals

Prerequisites

No prior experience in data visualization is required. Basic knowledge of financial investigations is beneficial.

Duration

10 sessions, approximately 2 hours of learning time

Languages

English, български, Український

Opțiuni înscriere

Self-paced eLearning

Denumirea cursului Visualise Cases and Flows of Money

Text rezumativ curs:

Corruption and money laundering investigations often involve complex networks of ...