Focus on Financial Institutions: Utilizing AML Data Analytics to Identify Emerging Criminal Patterns

  • When: Previously recorded on: November 5, 2014
  • Time: 12:00 PM – 2:00 PM ET
  • Level: Basic to Intermediate

Cutting through high volumes of transactions, historical trending information, and a maze of pattern matching and compliance rules can be a daunting exercise for a newcomer to the world of data analytics. However, with a continuous improvement approach to maintaining and fine-tuning AML systems, institutions can achieve a higher level of AML compliance.

By understanding and paying close attention to monitoring processes and system outputs, you will be able to better identify suspicious transaction patterns – and stay one step ahead of criminals wishing to move funds through your organization. This dynamic webinar provides key information to effectively utilize the outputs of the AML software to ensure your institution is protected from illicit activity.

Learning Objectives

  • Leveraging data analytics to better identify suspicious transactions
  • Utilizing red flags to improve rules, thresholds and parameters
  • Training your staff to identify new criminal activity trends and follow procedures for maintaining up-to-date documentation

Who Should Attend

  • AML Compliance Officers
  • Analytics Specialists
  • Consultants
  • Financial Intelligence Unit Personnel
  • Internal and External Auditors
  • IT Professionals
  • Law Enforcement Agents
  • Quality Assurance Professionals
  • Regulators
  • Risk Management Specialists
  • Transaction Monitoring Specialists

Industries

  • Banks and Credit Unions
  • Credit, Debit and Pre-paid Card Companies
  • Government and Regulatory Agencies
  • Money Service Businesses
  • Securities and Investments

Pricing

ACAMS Members Non-Members
$195 $295
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Moderator

Gail Towne
  • Gail Towne, CAMS

  • Director AML Modeling and Data Governance
  • BMO Financial Group

Speakers

Jeffrey Weiss
  • Jim Candelmo, CAMS

  • Executive Compliance Director & BSA AML Officer
  • Ally Financial

Steve Gurdak
  • Steve Gurdak, CAMS

  • Supervisory Analyst
  • High Intensity Drug Trafficking Area