Agenda

Agenda

Agenda

08:3009:00

Registration & refreshments

08:30 - 09:00

09:0010:30

Implementing a data governance framework

09:00 - 10:30

  • What is data management and data governance?
  • How does data management add value to the business?
  • The pillars for succeeding in data governance
  • Policy, roles and responsibilities, processes
  • How to identify critical data governance elements
  • Creating and using data lineage effectively
  • Assessing the current maturity of your data governance program using data management maturity model and other capabilities
Ayana Cavelle Richards

VP, Data Governance Delivery Manager, US Chief Data Office

HSBC

<p>Ayana is a member of the 2018 North American Financial Information Summit Advisory Board. To view all board members please click <a href="http://www.financialinformationsummit.com/na/static/advisory-board">her…;
<p>Over 10 years as a Data practitioner between Health Insurance and Finance industries covering regulatory reporting, business intelligence, data quality and analysis, data stewardship, data architecture, drafting/vetting EDM Policies and strategies. Creator of the MUFG Mitsubishi UFJ Trust and Banking Data Management Office and currently BCBS and CCAR Data Governor in the HSBC US Chief Data Office.</p>

10:3010:45

Morning break

10:30 - 10:45

10:4512:00

Data quality and data culture

10:45 - 12:00

  • Poor data quality and core infrastructure and its challenges 
  • Creating sustainable data quality
  • Culture of hiding mistakes
  • Fixing anomalies
  • Value of high quality ESG data
Ellen Gentile

Vice-president, data quality manager & data steward

SUMITOMO MITSUI

Ellen Gentile is the data quality manager for the SMBC Americas Division of Sumitomo Mitsui Banking Corporation. Ellen has over 20 years of experience in the financial services sector and has worked in various capacities for companies such as Cowan & Company, Morgan Stanley, Bank of America, Banc of America Securities and Pershing, LLC. As SMBC's data quality manager, Ellen works assiduously to establish and implement all facets of a comprehensive data quality program at the SMBC Americas division.

Prior to managing SMBC's data quality, Ellen championed the use of qualified data as a core enterprise resource supporting decision makers. To best deliver and monitor quality of service and information, Ellen established and set enterprise standards through operational quality scorecard products at Pershing, LLC. The quality based products she managed provided the much needed insight and transparency clients require to manage and grow their businesses.

 

 

12:0013:00

Lunch

12:00 - 13:00

13:0014:30

Preparing your data for AI and ML

13:00 - 14:30

  • Mitigating bias and error
  • Optimizing AI tools with high quality data
  • Defining high quality data
  • Developing an appropriate data foundation for AI
  • Continual maintenance of data quality
  • Ethical considerations
Michael Beal

CEO

DATA CAPITAL MANAGEMENT

Michael Beal is the CEO of Data Capital Management. A systematic Hedge Fund that specializes in machine learning, advanced technologies and novel data sources to generate differentiated and uncorrelated returns for the clients of its DCM A.I. Absolute Return Fund.

Prior to DCM, Mr. Beal co-founded the Big Data and Advanced Analytics group for JP Morgan Chase and was an investor with TPG Capital and Morgan Stanley. Michael is a frequent Keynote and CNBC contributor and is passionate about investing, the onset of the “Data Economy” and the application of disruptive technologies to valuable “problems to solve”.

Michael earned a BA from Harvard College with honors in Economics and an MBA from Harvard Business School with distinction. Michael is an active Board Member of the City University of New York’s Medgar Evers College.

14:3015:00

Afternoon Break

14:30 - 15:00

15:0016:30

Data privacy and security

15:00 - 16:30

  • Accountability and best practices
  • Cyber incident response
  • GDPR: legal and ethical concerns with persisting data, ownership and consumer rights
  • Data issues across different jurisdictions globally 
  • Need for algorithmic transparency and accountability

16:3016:35

End of day one

16:30 - 16:35

08:3009:00

Refreshments

08:30 - 09:00

09:0010:30

AI and data analytics

09:00 - 10:30

  • Creating a single security master
  • Algorithms to utilize unstructured data
  • Which areas of data management will benefit most from advances in AI
  • Developing the business case for AI driven analytics tool
  • Assessing third party tools
Imrankhan Mulla

Head - GIA data analytics Americas

UBS

Imrankhan is an experienced leader, with a decade and half of experience building analytics practices and leading large-scale global strategic initiatives with organizations such as UBS, JPMC, Exxon, FDIC, and SIPC. As a founding member of UBS GIA's data analytics group, he has helped the department set up an industry leading analytics practice (rated by external consulting firm Deloitte as a top tier analytics practice among all banking peers). In his six years at UBS, he has developed high impact analytics, including presenting analytics driven insights to the chairman of the board, Americas CEO/COO. He brings in the ability to not only drive the vision for a data analytics driven organization but also the ability to execute and transform the organization strategically while delivering high impact results along the way to create buy-in from most senior to lowest levels of the organization.

10:3010:45

Morning break

10:30 - 10:45

10:4512:00

Bringing your data in to cloud environments

10:45 - 12:00

  • Benefits of the cloud
    • Agile innovation – reallocating resources to deliver products and services faster to the market
    • Improving security, reducing financial crime and cost savings
  • Machine learning and deep learning
  • Multiple data centres, data residency, security and control 
  • Vendor lock-in
  • Shared liability
William M. Cohee

Executive director

Greenwich Analytica

12:0013:00

Lunch

12:00 - 13:00

13:0014:30

Alternative data for investors

13:00 - 14:30

  • Natural language processing and structure text based data
  • Python tools
  • Investor use cases for alternative data for a number of different types of datasets
  • Leveraging the right FX flow data to measure supply and demand of a particular currency

14:3015:00

Afternoon Break

14:30 - 15:00

15:0016:30

Governance and (AI & ML) data analytics

15:00 - 16:30

  • Developing harmonised reporting methods that streamline and improve outcomes for the stakeholders
  • Opacity of the black box
  • Eliminate silos and combining isolated data sets
  • Current focus on AI/ML in reducing cost of regulation
  • Utilising AI/ML for complex analytics use cases in future

16:3016:35

End of course

16:30 - 16:35