Yves Chauvin

Director, Investment Data Platform
AXA Investment Managers, Rosenberg Equities

Yves Chauvin is the Director of the Investment Data Platform at AXA-IM, Rosenberg Equity. He is responsible for data processing from supplier data to data integration and for the construction of data quality tools used in computer models for asset management. He started work in Machine Learning more than 20 years ago, when Machine Learning was seen as an alternative statistical tool to extract relevant knowledge from noisy data. One current topic of interest is how recent advances in Machine Learning may change or add constraints to data processing and knowledge management in the financial industry.

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Innovation, Data Quality and Compliance

Sunday, June 12th, 2016

14:25 Accessing the Potential of Machine Learning – A Guide for Data Management Executives

One of the great benefits to prioritizing data governance and data quality is having clean data to take advantage of new computational opportunities, including machine learning. Machines have an ability to discover patterns that humans may not find without expert training. But such patterns may also include spurious noise due to fundamental data errors. The need for data quality becomes especially acute when non-linear machine learning techniques are used. With clean data and appropriate interpretation of the patterns, machine learning techniques have the potential to improve investment decision making across the business.
Find out:
• How data management teams can begin to make use of machine intelligence
• How machine intelligence can help with the recognition and interpretation of data patterns.
• How to take advantage of recent advances in deep learning