FinTech CTO: Eradicating Fraud with Next-Gen Detection Strategies

Financial fraud types and the interconnectedness of AML

$30
FinTech CTO: Eradicating Fraud with Next-Gen Detection Strategies
FinTech CTO: Eradicating Fraud with Next-Gen Detection Strategies
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About the course

This session delves deep into financial fraud, covering its various forms, detection methods, and latest technologies for building robust prevention systems. Part 1 introduces financial fraud types and the interconnectedness of AML, fraud, and cybercrime prevention efforts, along with legacy fraud detection platform limitations and workflows. Part 2 emphasizes data management's crucial role in fraud detection, featuring case studies, data analytics techniques, and network analytics. Part 3 explores advanced detection techniques, geolocation data usage, and architectural considerations for modern fraud detection platforms. Attendees will gain essential knowledge and tools for combating financial fraud, crucial for CTOs, security professionals, and financial institution stakeholders.

Who should attend

  • Reconciliation Associates working in Investment Banking & Fund Services
  • Accounting graduates who want to launch their career as a fund accountant
  • MBA Finance graduates who want to work in Hedge Fund and Private Equity firms.
     

What you will learn

  • Welcome and Course Introduction: Begin the session with introductions, a course overview, and a roadmap for the module on Financial Fraud.
  • Financial Fraud: Overview and Types: Introduce the concept of financial fraud and the different types of fraud schemes that target banks and their customers.
  • Efforts in AML, Fraud, and Cybercrime Platforms: Highlight the interconnectedness of AML (Anti-Money Laundering), fraud, and cybercrime prevention efforts.
  • Exploring Legacy Fraud Detection Platforms: Discuss the limitations of traditional fraud detection systems.
  • Exploring Legacy Fraud Detection Platforms: Discuss the limitations of traditional fraud detection systems.
  • Exploring Legacy Fraud Detection Platforms : Discuss the limitations of traditional fraud detection systems.
  • Fraud Detection Case Study : Explore a real-world case study to illustrate how data analysis helped identify and prevent fraud.
  • Data Analytics in Fraud Detection: Discuss the application of data analytics techniques for fraud detection.
  • Network Analytics in Fraud Detection: Introduce the concept of network analytics and its role in uncovering fraudulent activity.
  • Key Strategies for Fraud Preventio : Discuss key strategies that banks can adopt to prevent fraud proactively.
    Advanced Detection Techniques
  • Exploring Detailed Fraud Detection Use Cases : Analyze various use cases where advanced fraud detection techniques can be applied.
  • Geolocation Data for Risk Assessment: Explore how geolocation data can be leveraged for fraud risk assessment.
  • Fraud Detection Platform Reference Architecture : Discuss the architectural considerations for building modern fraud detection platforms.
  • Fraud Detection Platform Reference Architecture: Discuss the architectural considerations for building modern fraud detection platforms.
     

About the instructor

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