Predictive Analytics World for Financial 2020
May 31-June 4, 2020
Chief Data Officer
Naveed Asem is the Chief Data and Analytics Officer and Senior Vice President at Donnelley Financial Solutions (DFIN), a $1.2 billion company that provides software and services to support clients with regulatory reporting, filing, and compliance functions globally.
Naveed joined DFIN in 2016 as the head of data and analytics. He now leads a growing team of data architects, engineers, and data scientists who are focused on creating business value from data through the use of modern data management technologies, analytics and machine learning. The team is not only responsible for the implementation of DFINâ€™s enterprise data warehouse and data lakes, but they manage everything from data ingestion and curation, to the delivery of reporting, and filing of artifacts with regulatory bodies in the U.S. and EU.
Naveed Asem is speaker of the following session:
Anasse Bari Ph.D.
Clinical Assistant Professor of Computer Science
Prof Anasse Bari holds a Ph.D. in Computer Science with a focus on Data Mining and is currently a clinical assistant professor of computer science at New York University. He was previously professor of computer science at George Washington University where he was awarded with the Computer Science Professor of the Year award in 2014 and was recognized by the Carnegie Foundation for his nomination for the United States Professor of the Year Award. He is the co-author of Predictive Analytics for Dummies.
Anasse Bari Ph.D. is speaker of the following session:
Senior Software Engineer
Leslie Barrett is a Senior Software Engineer at Bloomberg LP's Bloomberg Law division specializing in NLP and Machine Learning applied to legal and government text. Before Bloomberg she was Director of Search Technology at The Ladders Inc, an online resource for executive jobseekers and recruiters. Previously, she was Director of Language Technology at the Financial Times where she managed groups creating new online news search products and electronic news alerts. Leslie holds Ph.D. in Computational Linguistics from New York University. She has over 20 published papers in the fields of Natural Language Processing and Information Retrieval and holds 2 patents. She serves on the Program Committees for the International Conference on Computational Linguistics and Intelligent Text Processing and the International Workshop on Big Data for Financial News.
Leslie Barrett is speaker of the following session:
Managing Director, Enterprise Analytics
Jodi Blomberg leads the team that uses data, analytics and data science to understand and measure the events and interactions that make up a client journey as it crosses the enterprise. They connect big data across lots of silos and turn it into visualizations, insights, models and data products to understand and influence client experiences.
She is also responsible for model governance and risk management of data science models across the centralized analytics organization. She has over 15 years of experience in data science and predictive analytics in a variety of industries including software as service fraud solutions, text classification and financial services.
Jodi Blomberg is speaker of the following session:
Richard Boire's experience in predictive analytics and data science dates back to 1983, when he received an MBA from Concordia University in Finance and Statistics.
His initial experience at organizations such as Reader’s Digest and American Express allowed him to become a pioneer in the application of predictive modelling technology for all database and CRM type marketing programs. This extended to the introduction of models which targeted the acquisition of new customers based on return on investment.
With this experience, Richard formed his own consulting company back in 1994 which is now called the Boire Filler Group, a Canadian leader in offering analytical and database services to companies seeking solutions to their existing predictive analytics or database marketing challenges.
Richard is a recognized authority on predictive analytics and is among a very few, select top five experts in this field in Canada, with expertise and knowledge that is difficult, if not impossible to replicate in Canada. This expertise has evolved into international speaking assignments and workshop seminars in the U.S., England, Eastern Europe, and Southeast Asia.
Within Canada, he gives seminars on segmentation and predictive analytics for such organizations as Canadian Marketing Association (CMA), Direct Marketing News, Direct Marketing Association Toronto, Association for Advanced Relationship Marketing (AARM) and Predictive Analytics World (PAW). His written articles have appeared in numerous Canadian publications such as Direct Marketing News, Strategy Magazine, and Marketing Magazine. He has taught applied statistics, data mining and database marketing at a variety of institutions across Canada which include University of Toronto, George Brown College, Seneca College, and currently Centennial College. Richard was Chair at the CMA's Customer Insight and Analytics Committee and sat on the CMA's Board of Directors from 2009-2012. He has chaired numerous full day conferences on behalf of the CMA (the 2000 Database and Technology Seminar as well as the 2002 Database and Technology Seminar and the first-ever Customer Profitability Conference in 2005. He has most recently chaired the Predictive Analytics World conferences in both 2013 and 2014 which were held in Toronto.
He has co-authored white papers on the following topics: "Best Practices in Data Mining" as well as "Customer Profitability: The State of Evolution among Canadian Companies." In Oct. of 2014, his new book on "Data Mining for Managers-How to use Data (Big and Small) to Solve Business Problems" was published by Palgrave Macmillian. In March of 2016, Boire Filler Group was acquired by Environics Analytics where his current role is senior vice-president of innovation.
Richard Boire is speaker of the following session:
Senior Quantitative Researcher
Chakri Cherukuri is a senior researcher in the Quantitative Financial Research Group at Bloomberg LP in NYC. His research interests include quantitative portfolio management, algorithmic trading strategies, and applied machine learning. He has extensive experience in scientific computing and software development. Previously, he built analytical tools for the trading desks at Goldman Sachs and Lehman Brothers. He holds an undergraduate degree in mechanical engineering from the Indian Institute of Technology (IIT) Madras, India, and an MS in computational finance from Carnegie Mellon University.
Chakri Cherukuri is speaker of the following session:
Christian Elsasser is part of Swiss Re's P&C (Property & Casualty) Analytics unit that focusses on delivering data-analytics services and solutions to insurers. In his role he is managing projects that support Swiss Re's clients with data-driven insights – both for Personal Lines and Commercial Lines – based on external as well as internal data sets and analytics methods. In addition, he is responsible for the identification of new needs and opportunities of insurers in the area of data analytics and hence to define the strategy of the P&C Analytics unit.
Before joining Swiss Re he worked for five years at CERN as a physicist where he was responsible for the analysis and interpretation of data samples collected by the Large Hadron Collider (LHC).
Christian studied physics, economics, and computer science and holds an MSc degree from the University of Zurich. For his research at CERN he was awarded a PhD in natural science. He is currently also appointed as a lecturer in scientific computing and data analytics by the University of Zurich.
Christian Elsasser is speaker of the following session:
Bas is a programmer, scientist, and IT manager. He works as an independent technology lead in the AI domain. His academic background is in Artificial Intelligence and Informatics. Bas has a background in software development, design and architecture with a broad technical view from C++ to Prolog to Scala. He occasionally teaches programming courses and is a regular speaker on conferences and informal meetings, where he brings a mixture of market context, his own vision, business cases, architecture and source code in an enthusiastic way towards his audience.
Bas Geerdink is speaker of the following session:
Head of Responsible Innovation, Global Affairs
Jen Gennai leads Google’s Responsible Innovation team which is responsible for operationalizing Google’s AI Principles, ensuring that Google’s products have fair and ethical outcomes on individual users and the world. Her team works with product and engineering, leveraging a multidisciplinary group of experts in ethics, human rights, user research, racial justice and gender equity to validate that products and outputs align with our commitments to fairness, privacy, safety, societal benefit and more. Before she co-authored the AI Principles and founded Responsible Innovation, Jen worked on machine learning fairness and founded the Ethical ML team in Trust & Safety.
Jen Gennai is speaker of the following session:
Keith Higdon serves as President of ESIS, Inc., with overall management responsibility for this business. He is based in Chicago.
ESIS is one of the industry’s oldest and largest risk management services companies, providing claim and risk management services to a wide variety of commercial clients in the U.S. and globally. ESIS maintains a sharp focus on helping its clients manage their total cost of loss, offering comprehensive and flexible programs and innovative approaches to claims administration. ESIS is committed to achieving measurable results through consistently superior execution, and employing data analytic and predictive modelling capabilities to track progress.
Previously, Mr. Higdon served as Senior Vice President of Partnership Services for ESIS where he oversaw the management and development of client partnerships across all ESIS lines of business. In addition, he has accountability for new client implementations, ESIS University, ESIS construction practice, and ESIS global initiatives.
Mr. Higdon has 20 years of industry experience. He began his career in consulting conducting and managing auditing, program evaluation, and program design projects for workers compensation and integrated disability management programs to large employers and service providers. He left consulting for the third-party administrator (TPA) space where he held a variety of positions under information technology and client services developing and delivering differentiated products and services to clients. With a strong focus on information delivery, his previous TPA experience culminated in the management of four departments focusing on client reporting, predictive modeling, client-facing system enhancement and support, and loss control consulting and OSHA administration. Mr. Higdon holds two Bachelor of Science degrees in the social sciences from Northern Illinois University and a master’s degree in information technology and management from Illinois Institute of Technology. He is a board member, and former Chairman, for the Center for Employee Health Studies associated with the School of Public Health at the University of Illinois at Chicago. Mr. Higdon supports industry development through participation in regional and national conferences and has published on key topics including integrated disability management, the data lifecycle, and predictive modeling over the years. He is also a volunteer mentor and guest speaker at YearUp, a community college based program for economically disadvantaged students.
Keith Higdon is speaker of the following session:
Connor Jennings Ph.D.
Senior Data Scientist, AI Model Development Center of Excellence
Connor is a Senior Data Scientist at Wells Fargo and led AI projects around credit card collections and fraud detection. Before Wells Fargo, he was a researcher at the National Science Foundation: Center for e-Design and worked on industrial/ manufacturing focused machine learning research projects with Boeing, John Deere, GE, and other companies. Connor holds a Ph.D. in Industrial Engineering from Pennsylvania State University. He also holds B.S. degrees in Industrial and Manufacturing Systems Engineering and Economics and a M.S. degree in Industrial Engineering from Iowa State University.
Connor Jennings Ph.D. is speaker of the following session:
Abhishek Joshi ‘AJ’
Abhishek Joshi ‘AJ’ is a Sr. Director in Visa’s consulting & analytics group. He is responsible for helping financial institutions with improving growth and profitability through advanced analytics techniques. AJ has diverse experience in employing analytics to solve business problems across multiple industries – Manufacturing & Engineering, Financial Services and Telecom.
Abhishek Joshi ‘AJ’ is speaker of the following session:
Chief Data Officer
Seasoned industry recognized Data Analytics leader with over 25 years of experience in Information Management, Analytics and Enterprise Architecture Leadership. As Technology Leader and Head of Data Management delivered results for Fortune 100 Insurance, Financial Services and Retail companies. Proven track record of running complex IT operations, providing innovative solutions and developing business aligned strategies. Core expertise spans running Enterprise Architecture, Information Strategy, Business Intelligence and Master Data Management.
Associate Professor of Analytics
A Teaching Associate Professor in the Institute for Advanced Analytics, Dr. Aric LaBarr is passionate about helping people solve challenges using their data. There he helps design the innovative program to prepare a modern workforce to wisely communicate and handle a data-driven future at the nation's first master of science in analytics degree program. He teaches courses in predictive modeling, forecasting, simulation, financial analytics, and risk management.
Previously, he was Director and Senior Scientist at Elder Research, where he mentored and lead a team of data scientists and software engineers. As director of the Raleigh, NC office he worked closely with clients and partners to solve problems in the fields of banking, consumer product goods, healthcare, and government.
Dr. LaBarr holds a B.S. in economics, as well as a B.S., M.S., and Ph.D. in statistics — all from NC State University.
Aric LaBarr is speaker of the following session:
Director of Data Science, US EOIT Advanced Analytics & AI
Richard Lee is Director of Data Science for John Hancock, the U.S. division of Toronto-based Manulife.
Richard leads the Advanced Analytics & AI group, which supports operations decision analytics across all U.S. businesses.
In his current role, Richard finds opportunities for efficiencies in Life Insurance as well as Long Term Care Insurance operations. Much of his focus is on innovation to enhance the relevance and understanding of analytics and its impact on operations decision-making.
Prior to his current role, Richard has spent 15 years at John Hancock in various analytics roles.
Richard Lee is speaker of the following session:
AI and Data Science Center of Excellence Leader, Workplace Investing
Victor S.Y. Lo is a seasoned Big Data, Marketing, Risk, and Finance leader with over 25 years of extensive consulting and corporate experience employing data-driven solutions in a wide variety of business areas, including Customer Relationship Management, Market Research, Advertising Strategy, Risk Management, Financial Econometrics, Insurance, Product Development, Transportation, and Human Resources. He is actively engaged with causal inference and is a pioneer of Uplift/True-lift modeling, a key subfield of data science.
Victor has managed teams of quantitative analysts in multiple organizations. He currently leads the AI and Data Science Center of Excellence, Workplace Investing at Fidelity Investments. Previously he managed advanced analytics/data science teams in Personal Investing, Corporate Treasury, Managerial Finance, and Healthcare and Total Well-being at Fidelity Investments. Prior to Fidelity, he was VP and Manager of Modeling and Analysis at FleetBoston Financial (now Bank of America), and Senior Associate at Mercer Management Consulting (now Oliver Wyman).
For academic services, Victor has been a visiting research fellow and corporate executive-in-residence at Bentley University. He has also been serving on the steering committee of the Boston Chapter of the Institute for Operations Research and the Management Sciences (INFORMS) and on the editorial board for two academic journals. He is also an elected board member of the National Institute of Statistical Sciences (NISS). Victor earned a master’s degree in Operational Research and a PhD in Statistics, and was a Postdoctoral Fellow in Management Science. He has co-authored a graduate level econometrics book and published numerous articles in Data Mining, Marketing, Statistics, Analytics, and Management Science literature, and is completing a graduate level book on causal inference in business.
Victor Lo is speaker of the following session:
Carrie Lu Ph.D.
Senior Data Scientist
Carrie (Caimei) Lu is a Senior Data Scientist at Safety National. She has over eight years of experience in using machine learning to generate insights from huge amounts of data, and using data science technologies to solve challenging business problems where data holds the key. At Safety National, Carrie Lu works with insurance business stakeholders on developing predictive models that can flag potential high risk and help the company reduce cost on long-term developmental claims. Carrie Lu holds Ph.D. in Information Science from Drexel University. She has over 15 published papers in the fields of Data Mining and Machine Learning.
Carrie Lu Ph.D. is speaker of the following session:
CSPA, Founder and Lead Data Scientist
Advanced Analytics Consulting Services, LLC
Mrs. Mei Najim, CSPA, Founder and Lead Data Scientist is the Co-Chair of PAW for Financial.
She provides advanced analytics consulting services including developing full life cycle predictive modeling processes from raw data exploration to model implementation into IT data systems, thorough documentation, and related training. Mei has over 14 years hands-on advanced analytics and machine learning experience dealing with large and complex data sets in various types of predictive analytics settings (claims, underwriting, pricing). She also has extensive traditional actuarial analysis experience including pricing, reserving, and research & development in the insurance industry. She has presented at many conferences to share and discuss her papers and expertise in predictive analytics with industry analytics experts.
Mei holds a Bachelor of Science in Actuarial Science from Hunan University and two Master of Science degrees, in Applied Mathematics and in Statistics, from Washington State University. Mei is a member of the American Statistical Association and a Certified Specialist in Predictive Analytics (CSPA) of the Casualty Actuarial Society.
Mei Najim is speaker of the following session:
Andreas is working as a Quantitative Researcher at Goldman Sachs Quantitative Execution Services, with an emphasis in machine learning techniques for execution algorithms. Andreas has received a PhD in Information Engineering at the University of Cambridge, focusing on the interface of stochastic control theory and Bayesian machine learning, where he developed graph theoretic tools for predicting the shapes of the probability distributions to arise in the observable time-series due to the underlying non-linear stochastic interconnections. Andreas’ teaching experience included several engineering undergraduate courses, including Inference and Machine Learning, Linear Algebra, Probability, Control and Signal Processing. During his PhD, he has also worked at Informetis Europe as a Machine Learning Algorithm Engineer, developing efficient Bayesian inference techniques for smart electricity meter applications. Andreas also holds a BA and an MEng degree in Electrical and Information Sciences from Trinity College, University of Cambridge, during which he has received the G-Research and The Technology Partnership (TTP) awards, while his Master’s thesis was done in collaboration with British Cycling, developing a racing cyclist fitness predictor.
Andreas Petrides is speaker of the following session:
Global Head of Risk Strategy and Analytics
Senior Data Scientist
Mohammad is currently a Senior Data & Applied Scientist at Microsoft, and Instructor at Stanford University. He is a former Data Scientist at Apple and previously worked for Samsung, Bosch, General Electric and UCLA Research Labs. He received a PhD in Computer Science from the University of California, Riverside and B.Sc. from University of Tehran. Mohammad is the author of the book, ‘Applications of Mining Massive Time Series Data'. He has also been a keynote speaker at more than 40 Data Summits/Conferences around the globe.
Mohammad Shokoohi-Yekta is speaker of the following session:
Eric Siegel, Ph.D., founder of the Predictive Analytics World conference series and executive editor of The Machine Learning Times, makes the how and why of predictive analytics understandable and captivating. He is the author of the award-winning Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, a former Columbia University professor who used to sing to his students, and a renowned speaker, educator, and leader in the field.
Eric has appeared on Bloomberg TV and Radio, Business News Network (Canada), Fox News, Israel National Radio, NPR Marketplace, Radio National (Australia), and TheStreet. He and his book have been featured in Businessweek, CBS MoneyWatch, Contagious Magazine, The European Business Review, The Financial Times, Forbes, Forrester, Fortune, Harvard Business Review, The Huffington Post, The New York Review of Books, Newsweek, Quartz, Salon, Scientific American, The Seattle Post-Intelligencer, The Wall Street Journal, The Washington Post, and WSJ MarketWatch. Follow him at @predictanalytic.
Eric Siegel is speaker of the following session:
Michael Steliaros is the global head of Quantitative Execution Services at Goldman Sachs. He is responsible for the research, development and implementation of quantitative processes for portfolio and electronic trading as well as managing the bank's relations with the quantitative client base. Previously, Michael held a variety of senior roles at BofAML in London and New York, most recently running the global agency portfolio trading and quantitative equity businesses. Earlier in his career, he spent a decade on the buy-side (most notably BGI and Winton) building quant stock-selection models and managing global market neutral equity portfolios. Michael received a bachelor's degree in Economics & Econometrics from the University of Nottingham, and an MSc and PhD in Finance from City University (CASS) Business School in London
Michael Steliaros is speaker of the following session:
Chief Risk and Data Analytics Officer
William (Bill) Wilkins is a multi-purpose actuary for the Safety National Casualty Corporation(SNCC). He is a CERA, FCAS, ASA and MAAA. While his main focus is on Enterprise Risk Management and Predictive Analytics, Bill has experience in pricing insurance, reinsurance, credit risk products, risk management, reserving and broker management. He is currently Co-Chair of the SNCC Data Analytics Committee. The Data Analytics Committee is a cross-functional group tasked with all aspects of data for SNCC. The Committee works on data to be collected, how it is collected, where it is collected from, how it stored, standards and practices of usage, etc. This includes the populating items like benchmarking reports or how best to create and use predictive analytics. The goal is to establish a process that is repeatable and adaptable so SNCC can deliver both internally and externally.
William WIlkins is speaker of the following session: