Recorded Webinar: Artificial Intelligence in the EDM Era1 November 2017
The scope and scale of structured and unstructured data that financial firms must manage continues to grow exponentially, calling for innovative approaches that can deliver automated, accurate and timely decision making. Artificial intelligence (AI) and cognitive computing are prime contenders to ease the enterprise data management burden, but what types of solutions are available, how do they work, how can they be integrated into existing infrastructure, and to what extent can they benefit firms now and in the future?
Listen to the webinar to find out about:
- State-of-play in enterprise data management programmes and initiatives
- Outstanding problems and challenges of data management
- How AI and cognitive computing can help
- Specific and particularly beneficial use cases
- Best practice integration with existing systems
More about our speakers:
Senior Vice President, Head of Enterprise Knowledge Graph Solutions, Data Management and Insights
David provides leadership and expertise for the advancement of knowledge graph and machine intelligence based technologies at Wells Fargo. His team develops innovations that employ various AI capabilities, including semantic technology, graph analytics, machine learning and natural language processing. David’s core mission is to use AI to develop the foundational building blocks for the future of data at Wells Fargo.
David’s interests include how to operationally leverage knowledge graphs to support data catalogs, semantic data lakes, and as a source to train machine learning algorithms.
David chairs the Financial Industry Business Ontology (FIBO) initiative, a collaborative effort of global banks, financial regulators and vendors, under the auspices of the Enterprise Data Management Council. Their goal is to semantically define a common language standard for finance using ontologies.
David is also engaged in a collaborative effort with academic researchers to use knowledge graphs to help explain the influential features contributing to machine learning predictions.
Head of Technology
Jordan & Jordan
Greg manages the development of systems-based services at Jordan & Jordan, where he is responsible for delivering market data reporting, regulatory trade reporting and post trade compliance solutions. With a focus on regulatory compliance he has assisted clients with their SEC Market Access, 17a-4 data retention, and RegSCI system integrity/security requirements. He has also managed numerous technology infrastructure assessments in areas such as system performance, post-mortem analysis of service outages, service validation and testing policies, analysis of industry-standard order-routing protocols, and OATS/EBS regulatory reporting. He is currently driving efforts to apply machine learning capabilities to post trade surveillance, specifically in the detection of trading violations such as spoofing and layering.
Greg also co-chairs two FIX Trading Communities working groups: the FIX Algorithmic Trading Working Group where he led in the creation of FIXatdl, an extensible markup language used to define data models and interfaces of advanced order types, and the FIX High Performance Working Group Google Protocol Buffers Subgroup where they have developed a method to use Google Protocol Buffers technology to produce fast and compact encodings of FIX messages.
Tony Brownlee is a Kingland partner and board member, responsible for leading and setting the company’s Data Science and Research strategy worldwide. Mr. Brownlee has been instrumental in leading complex data and software initiatives at Kingland, as a founding member of the Kingland team that built the company’s first data platform, to his work with the Legal Entity Identifier (LEI) developing the first LEI platform in the world for DTCC. Mr. Brownlee’s leadership extends across the company as he has managed numerous operational, product development, business development, and client relationship management functions for the company. Tony worked closely with US regulators for more than four years on the Consolidated Audit Trail and is a leading expert on customer and account data and regulatory reporting issues. Mr. Brownlee is recognized as a thought leader in financial services and data topics and speaks regularly on data quality, data governance, data standards, legal entity and hierarchy data, and cognitive technologies and has served on various committees including the Securities Industry Financial Markets Association (SIFMA); the International Standards Organization (ISO); the Financial Stability Board (FSB) for the LEI; and the Enterprise Data Management Council (EDMC).
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