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With more than $1.5 trillion lost to Financial Crime in 2018 alone, traditional ways of dealing with fraud and AML don't work anymore.  Advancements in data management and machine learning are now proving invaluable in the fight against Financial Crime

Join Quantexa and Cloudera as they demonstrate how they’ve partnered with HSBC, Standard Chartered and other leading financial organizations to leverage the power of data, dynamic entity resolution, and advanced network analytics to solve major financial crime challenges while enhancing customer intelligence and improving business outcomes.

As part of the webinar, we will cover:
  • A next-gen data and analytics-driven architecture to fight financial crime

  • Demo a solution of how data and context around your customer enables better assessment of potential criminal behavior

  • Three case studies from some of the leading financial organizations

  • Discuss the complementary data benefits to the rest of the business of improving financial crime prevention.

Speakers


Managing Director, Financial Services at Cloudera

Dr. Richard Harmon

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Dr. Harmon is the global co-head of the Financial Services Industry for Cloudera. He started his post-academic career at the Federal Reserve Bank of New York followed by leading risk and research teams at Citibank, Bankers Trust, JP Morgan and Bank of America. He is the co-founder of a GMAC funded Risk Management & Analytics start-up called Risk Monitors which was acquired by BlackRock, where he was an MD & Partner in the Risk Management Group. Dr. Harmon holds a PhD in Economics with specialization in Econometrics from Georgetown University.

Chief Technology Officer, Quantexa

Jamie Hutton

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Over the last 13 years, Jamie has been using big data technology to uncover complex criminal activity across the financial sector. Having pioneered the concept of dynamic entity resolution, Jamie manages the R&D and cloud teams to make this a reality and ensure the Quantexa solves global real-world challenges faced by some of the world’s largest organisations. Jamie has enabled the detection of multi-million-pound crash-for-cash scams, complex money laundering activity and insider fraud. HEADSHOT:

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