Your browser is out of date

Update your browser to view this website correctly. Update my browser now

×

Cloudera Cloudera

Register Now

Date: October 23, 2019 Time: 10:00am PT | 1:00pm ET

Financial services institutions lost over $1.5 trillion in combined revenue to financial crimes in 2018, and this is increasing ever rapidly. 

Organizations today need a next-generation financial crimes platform that breaks down traditional silos across AML, fraud, cybersecurity, and surveillance, and leverages the power of analytics and machine learning to effectively simulate, predict, and prevent crimes.

Join Cloudera’s financial services industry experts as they explain how an analytics and machine learning led approach can more effectively fight financial crime.

Topics include:
  • New industry-wide approaches using data and analytics to combat financial crime.

  • Examples of key solutions that support revenue generation while mitigating financial crime risks.

  • Four innovative customer use cases and case studies on how leading banks are tackling financial crime including AML, fraud, and cybersecurity.

Speakers

Managing Director, Financial Services

Dr. Richard Harmon

More

Dr. Harmon is the global co-head of the Financial Services Industry vertical 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.

Business Integration Architect

Paul Lashmet

More

Paul Lashmet is a former senior vice president at HSBC who has also led programs at Deutsche Bank, Israel Discount Bank, and Fannie Mae. He is currently a Business Integration Architect at Cloudera and writes extensively about the practical applications of emerging and innovative technologies to regulatory compliance.

Your form submission has failed.

This may have been caused by one of the following:

  • Your request timed out
  • A plugin/browser extension blocked the submission. If you have an ad blocking plugin please disable it and close this message to reload the page.