Peter Ku

Head of Industry Consulting & Financial Services Strategist & Evangelist, N
Informatica, LLC.

Peter Ku is responsible for Informatica's Global Financial Services industry solutions consulting practice. He is an expert in data integration, data quality, business intelligence, data warehousing, master data management and data mining technologies and has spent over 15 years helping banks and insurance companies understand how to leverage technology to accelerate business growth, comply with regulations, combat fraud and improve business efficiencies. Mr. Ku spent six years in the credit card industry with Providian Bancorp and Visa International and five years in the residential mortgage technology industry with Dorado and Ellie Mae. Peter is a regular presenter at industry events across the globe and author of many articles related to Big Data, regulatory compliance, credit risk management, operational risk and driving customer insight and growth across the enterprise.

Check out the incredible speaker line-up to see who will be joining Peter.

Download The Latest Agenda

Operational, Technology and Business Foundations for Success

Thursday, May 12th, 2016

12:05 Interactive Roundtable Discussions

#1 Injecting Compliance Into The Data Supply Chain
Sue Habas, Vice President, Strategic Technologies, ASG

#2 Managing Data Quality in Financial Services – What’s Working vs. Not?
Peter Ku, Head of Industry Consulting & Financial Services Strategist & Evangelist, North America Enterprise Sales, Informatica, LLC.

#3 Leadership Structures to Advance Data Management Without a CDO
Natalie Sendele, Director, Data Governance, Artisan Partners

#4 What is a Golden Source and How Do You Establish it?
Steve Krosch, Vice President, Data Architecture, Business Applications, Allianz Global Investors

#5 Managing the Complexities of Data Integration From Various Sources
CP Singh, Managing Principle, CPSI Consulting

Innovation, Data Quality and Compliance

Sunday, June 12th, 2016

08:10 Chairperson’s Opening Remarks

11:00 Panel Discussion | Developing and Maturing Data Quality Monitoring

Fixing data quality is the plumbing of a huge skyscraper, it cannot be fixed overnight. After building in metadata, terms and definitions, the next phase is a strong framework around data quality that can be continuously monitored.
Find out how to:
• Develop metrics to measure and prove data quality while reducing redundancy
• Quickly get up the data quality curve if you’re behind
• Balance data quality activities with new opportunities, including advanced analytics