Data and Model Governance in the Age of Data Science and AI
PRMIA Boston invites you to a seminar on AI and ML and Identity Risk in the Era of Global Data Protection and Privacy Mandates in collaboration with Suffolk University and Quant University.com.
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Event Information
Date: October 23, 2018
Time: 4:00 p.m. - 7:30 p.m.
Location: Suffolk University, Sawyer Business School, Department of Finance
Commons/Blue Sky Lounge; Sargent Hall, 5th Floor
120 Tremont St
Boston, MA 02108
Subject matter experts and thought leaders will discuss the following topics:
- Data and Model Governance in the Age of Data Science and AI
- Identity Risk in the Era of Global Data Protection and Privacy Mandates
- Digesting Big Data
- Big Data Analytics, A Cautionary Comment
Agenda
4:00 p.m. Registration and Refreshments
4:30 p.m. Welcoming remarks:
Dan diBartolomeo and Sohayla Fitzpatrick, Regional Directors, PRMIA Boston
Abu Jalal, Chair, Finance Department and Director of the MSF Program
Ying Becker, Ph.D., Professor of Finance Practice
4:45 p.m. Sri Krishnamurthy: Model Governance in the age of Data Science and AI
5:15 p.m. David Blaszkowsky: Identity Risk in the Era of Global Data Protection and Privacy Mandates
5:45 p.m. Break: Warm Finger Foods, soft drinks and desserts
6:00 p.m. Dan Joldzic: Digesting Big Data
6:30 p.m. Dan diBartolomeo: Big Data Analytics, A Cautionary Comment
7:00 p.m. Panel Discussion & Q&A
7:30 p.m. Closing Remarks
Dan diBartolomeo, Regional Director, PRMIA Boston
Speakers
SRI Krishnamurthy, Model Governance in the age of Data Science and AI
Abstract:
As more and more open-source technologies penetrate enterprises, data scientists have a plethora of choices for building, testing and scaling models. In addition, data scientists have been able to leverage the growing support for cloud-based infrastructure and open data sets to develop machine learning applications. Even though there are multiple solutions and platforms available to build machine learning solutions, challenges remain in adopting machine learning in the enterprise. Many of the challenges are associated with how machine learning process can be formalized. As the field matures, formal mechanism for a replicable, interpretable, auditable process for a complete machine learning pipeline from data ingestion to deployment is warranted. Projects like Docker, Binderhub, MLFlow are efforts in this quest and research and industry efforts on replicable machine learning processes are gaining steam. Heavily regulated industries like financial and healthcare industries are looking for best practices to enable their research teams to reproduce research and adopt best practices in model governance. In this talk, we will discuss the challenges and best practices of governing AI and ML model in the enterprise
Biography:
Sri Krishnamurthy, CFA, CAP is the founder of QuantUniversity.com, a data and Quantitative Analysis Company and the creator of the Analytics Certificate program and Fintech Certificate program. Sri has more than 15 years of experience in analytics, quantitative analysis, statistical modeling and designing large-scale applications. Prior to starting QuantUniversity, Sri has worked at Citigroup, Endeca, MathWorks and with more than 25 customers in the financial services and energy industries. He has trained more than 1000 students in quantitative methods, analytics and big data in the industry and at Babson College, Northeastern University and Hult International Business School. Sri is leading development efforts in creating a platform called QuSandbox for adopting open source and analytics solutions within regulated industries.
David Blaszkowsky, Identity Risk in the Era of Global Data Protection and Privacy Mandates
Abstract:
As BCBS 239 compelled the largest banks to take on governance of risk data, GDPR and its brethren -- now including California's new data protection and Privacy act -- are forcing everyone else to impose even more stringent and complex controls on the data they collect on people. But, requirements assume that firms can connect all of the digital identities, of which a person might have many, to the singular actual natural person "real world" entity. And, to manage these identities across all activities, forever. This is an enormous and new risk due to the challenges of the task and the unprecedented sanctions in money and lost opportunity. This session will examine new findings and suggest a fresh approach to remove complexities and eliminate much of the labor involved.
Biography:
David Blaszkowsky is an expert and thought-leader in regulatory compliance, data governance, semantic technology, and strategic planning. He has held senior roles at Accenture, State Street, US Department of Treasury, SEC and Standard & Poor’s.
He has a BA in Economics from University of Chicago and has an MBA from Northwestern University.
Dan Joldzic, Digesting Big Data
Abstract:
90% of communication is unstructured and information volumes are growing. In order to separate information from noise, systems need to be developed to capture Big Data and analyze it as consistently and accurately as possible.
Biography:
Dan Joldzic, CFA, FRM is CEO of Alexandria Technology, Inc, which develops artificial intelligence to analyze financial news. Prior to joining Alexandria, Dan served dual roles as an equity portfolio manager and quantitative research analyst at Alliance Bernstein where he performed factor research to enhance the performance of equity portfolios.
Dan diBartolomeo, Big Data Analytics, A Cautionary Comment
Abstract:
This presentation will describe the many practical and statistical difficulties in validating analytical models of unstable systems such as financial markets. As financial analysis is increasingly based on data analysis rather than expository theories, the challenge of testing such models becomes exponentially more problematic.
Biography:
Mr. diBartolomeo is President and founder of Northfield Information Services, Inc. Based in Boston since 1986, Northfield develops quantitative models of financial markets. He sits on boards of numerous industry organizations include IAQF and CQA, and is past president of the Boston Economic Club. His publication record includes thirty books, book chapters and research journal articles. In January 2018, he became editor of the Journal of Asset Management. Dan spent multiple years as a Visiting Professor at Brunel University, and has been admitted as an expert witness in litigation matters regarding investment management practices and derivatives in both US federal and state courts.
Registration
This event is FREE for members and non-members, although registration is required. Click "Register Myself" below to reserve your spot. Make sure to click "Continue" to proceed with your registration. (If this is your first time accessing the PRMIA website you will need to create a short user profile to register.)