How machine intelligence can help banks beat financial crime

The panel

  • Ted Sausen, Director and anti-money laundering subject matter expert, NICE Actimize
  • Jim Arndts, Director, Enterprise financial crimes compliance strategy, Transformation and governance, US Bank
  • Michael Schidlow, Head of financial crime compliance and emerging risk audit development, HSBC
  • McHenry Kane, Senior vice-president, Director of anti-money laundering, New York Community Bank
  • Alexander Campbell, Editor, Risk.net

Faced with massive financial crime challenges, many banks have responded by scaling up their functions. However, these investigations take way too much time and require unending growth in person power.

Sophisticated financial institutions are turning to machine intelligence to develop innovative approaches that eliminate risk, improve operations and retain the flexibility to evolve with threats in real time.

Recent developments in robotics process automation (RPA) and machine learning have ushered financial institutions into a new era. This emergent technology has revolutionised financial crime investigations by enabling banks to apply analytics-driven case management, automated evidence gathering and entity risk visualisation.

Key topics discussed in this webinar include:

  • The current challenges in financial crime investigations
  • New trends in applications of machine learning and RPA
  • How to address financial institutions’ risk appetite for anti-money laundering (AML) compliance risk
  • How to manage payment processes and reduce the risk of money laundering
  • What technology and data analytics systems firms are using for AML protection
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