Thursday, September 14, 2017
(Please "Sign In" if you are an INFORMS member.)
University of Notre Dame, Chicago Campus - 224 S. Michigan Avenue (2nd Floor), Chicago IL 60604
What’s Hot in Fin Tech and Sports Analytics
There’s no question that some of the hottest ideas in Data Science and Analytics come from FinTech and Sports. Chicago now ranks #5 globally for FinTech, and the local FinTech economy represents $25.9 Billion in gross regional product with 123,156 employees from 8,412 companies. Analytical techniques from these industries can be applied to areas of Customer Acquisition, Marketing, Sales, Fraud Analysis, Operations, Customer Relationship Management (CRM), and Financial and Economic Management.
Our FinTech track explores cutting edge financial technologies and methodologies – like real time analytics and digital decisioning play with analytics as a service, and areas of large scale machine learning automation for the financial industry. Our Sports Analytics track delves into the three areas of sports from the front-office “business side”, back office “team operations”, and health and safety analytics.
No matter what area you decide to explore, we know you’ll come away with ideas that will change how you approach Data Science and Analytics in your own field!
Program at a Glance
|8:30 – 9:00 a.m.
||Registration and networking
|9:00 – 9:15 a.m.
|9:15 – 10:00 a.m.
||Keynote Presentation- Patrick Lucey, Ph.D., Director of Data Science, STATS LLC – Interactive Sports Analytics: Going Beyond Spreadsheets
|10:00 – 10:15 a.m.
10:15 – 11:15 a.m.
|Panel Discussion – Role of technology and challenges in accelerating analytics concepts within an (YOUR) organization.
Joe DeCosmo, Enova; Tom Rauch, CGN Global; Don Kleinmuntz, Ph.D., University of Notre Dame; Derek Magilton, AnyLogic.
Moderator – Nikhil Thaker, HAVI Global Solutions
|11:30 – 12:30 p.m.
|1:00 – 4:30 p.m.
||Breakout sessions (Tracks)
|4:30 – 5:00 p.m.
||Q & A and Raffle
|5:00 – 6:30 p.m.
||Networking & Cocktail Reception
Track 1: FinTech
|1:00 – 1:45 p.m.
||Joe DeCosmo, Chief Analytics Officer, Enova – Real Time Analytics
|1:45 – 2:30 p.m.
||Justin Dickerson, Ph.D., Data Robot – Machine learning Fin Tech predictive Models – Default, Fraud, Scoring
|2:30 – 3:00 p.m.
|3:00 – 3:45 p.m.
||Michael Rechenthin, Ph.D., tastytrade – Data Science and Collaboration at tastytrade
|3:45 – 4:30 p.m.
||Jim Austin, Vertex Analytics – FinTech for Trading: See What Matters
Track 2: Sports Analytics
|1:00 – 1:45 p.m.
||Russell Walker, Ph.D., Northwestern University – Leveraging Big Data and Analytics for Digital Strategy Formation in Sports Management
|1:45 – 2:30 p.m.
||Zach Binkley, Ph.D., Lewis University – Analytics in Sports Performance: Communication, Implementation and Innovation
|2:30 – 3:00 p.m.
|3:00 – 3:45 p.m.
||Sundeep Maini, Executive Director, CGN - Increase Sporting Event Revenue Though Proximity Analytics
|3:45 – 4:30 p.m.
||Liz Wanless, Ph.D., Ball State University – Customer Relationships and Sales Optimization with Two Revenue Enhancement Case Studies
NOTE: INFORMS Chicago Chapter reserves the right to adjust the schedule based on speaker availability.
Door Prizes: There will be door prize giveaways for attendees.
INFORMS Member - $79
Non-Member - $99
Full time student - $49
Early registration discount $10 off, through August 21.
Refunds less $20 processing fee for cancellation through August 31. Substitutions allowed at any time. At the door, space permitting - $119.
FinTech Track Overview
This year we will see diverse applications of the latest technologies in financial technology. Hear from industry leaders on topics such as:
- How does real-time analytics and digital decisioning play with analytics as a service?
- What kind of data science goes on behind the scenes in providing the most relevant financial information?
- How do you automate large scale machine learning? How is it applied in financial industry?
If you are a strategist interested in what the latest financial technologies are or if you are interested in cutting edge technology (or both), the FinTech track is right for you. The technologies and methodologies we cover in the track can be applied to the broader FinTech area including customer acquisition, marketing, sales, fraud analysis and operations.
Sports Analytics Track Overview
The term "sports analytics" means different things to different people. An inclusive definition allows for division into three separate areas: front-office “business-side” analytics; back-office “team operations” analytics; and health and safety analytics. The Sports Analytics track of IMPAC 2017 will include speakers that span these three areas.
The business side of sports includes ticket pricing, merchandising and brand licensing, venue management, sponsorship return on investment, etc. Sports business shares many analytical techniques with customer relationship management (CRM) techniques used by marketing and sales, as well as analytic approaches by the finance organization. The operations side of sports uses a variety of big data and analytics techniques, for game planning and competitive analysis using data from video and wearable sensors. In many ways, this is related to Internet of Things (IoT) techniques in several other industries. Finally, but no less important, the health and safety aspects of sports are closely related to techniques used in the healthcare industry, an area of vibrant research. Using predictive models for injury prevention, sleep and rest, and nutrition are all areas of current research and application.
Pan Chen, Ph.D., HAVI Global Solutions
Vinod Cheriyan, Ph.D., ENOVA DECISIONS
Jay Jayaraman, Accenture
Andrea Leiter, Leiter Communications, Inc.
Scott Nestler, Ph.D., University of Notre Dame
Nikhil Thaker, HAVI Global Solutions
James Weber, Ph.D., UIC (retired)
About our Presenters:
Jim Austin, Founder / Chief Strategy Officer, Vertex Analytics – Session: FinTech for Trading: See What Matters. In a time when big data is king, visualizations are what really rule. Most trading firms only have access to their own trading data and analytics, which only tells half the story. Both traders and compliance officers are losing out on crucial information that can inform their strategies by not having access to market data, and the visualizations that allow them to really SEE the market.
Jim is one of the founders of Vertex Analytics and currently leads innovation strategy. He has had a career entrenched in technology and the financial markets; prior to co-founding Vertex in 2011, he was a Financial Engineer for Quantitative Analytics, Inc., which was acquired by Thomson Financial.
Zach Binkley, Ph.D., Assistant Professor Program Director for Exercise Movement Science, Lewis University – Session: Analytics in Sports Performance: Communication, Implementation, and Innovation - This presentation will highlight important concepts within using analytics and data in today’s sports performance world. Strategies on analytics communication will be discussed as well as the implementation of data-driven programs and initiatives. Barriers to the implementation of analytics within sports is explored and in this presentation, strategies to break through those barriers are discussed. Three current analytical platforms will be investigated and future technologies are discussed to see how innovation will impact this rapidly growing field.
Zach received his bachelor’s degree from Millikin University and master’s degree from California University of Pennsylvania and PhD at Northcentral University. Zach specializes in student learning assessment data, education technology and eLearning, data and analytics, and innovation in sports. Last summer, he launched his own innovation incubator called zLine Technologies LLC that focuses on consulting and creating new developments in the areas of VR, AR, IOT, analytics, and wearable technology within sports and exercise.
Joe DeCosmo, Chief Analytics Officer, Enova International and Enova Decisions - Session: Master Your Data Science Approach with Digital Decisioning - At many organizations, the cost and difficulty of building and activating predictive models and infrastructure into business processes is prohibitive, not to mention incredibly time-consuming. Analytics-as-a-service and real-time digital decisioning methods and platforms provide lower-cost, more efficient solutions. In this session Joe will explain how businesses can utilize these solutions to vastly improve operational decision-making capabilities and create measurable results around credit risk, fraud, verification, payments, collections, and marketing. He will teach you how to think beyond model building and consider the activation of analytics within decision models and business processes to increase effectiveness in operational decisions; and how to combine decision modeling, business rules, machine learning, and optimization in a digital decisioning system to provide a repeatable, proven approach to problem solving.
Joe joined Enova as Chief Analytics Officer in 2014. He leads a multi-disciplinary analytics team that provides end-to-end data and analytic services including data warehousing, business intelligence, fraud, credit risk, marketing and business analytics. The team supports lending products and corporate services for Enova’s global business units. Prior to Enova, he served as Director and Practice Leader of Advanced Analytics for West Monroe Partners. He also held executive positions at HAVI Global Solutions and the Allant Group. Joe received a BA in Economics from Lewis University and an MA in Economics from the University of Illinois at Chicago. He is Immediate Past-President of the Chicago Chapter of the American Statistical Association and is on the Advisory Board of the UIC College of Business Administration.
Justin Dickerson, Ph.D., General Manager, Global FinTech, Data Robot - Justin is a data scientist and business leader with nearly 20 years of experience helping some of America's most respected companies realize the power of predictive analytics. Most recently, Justin has focused his time on building machine learning predictive models for the fintech industry. As the former Chief Data Scientist of a successful alternative finance company, Justin has been responsible for developing the latest methodologies to predict payment defaults, spot fraud before it occurs, and score lists of marketing prospects. Justin has experience developing predictive analytics platforms and was the CEO of Crossfold Analytics, a successful data science consultancy he founded in the alternative finance industry. Justin holds a PhD from Texas A&M University, and has been recognized by the American Statistical Association with the prestigious Accredited Professional Statistician (PStat) credential. At DataRobot, Justin is the General Manager of the Global Fintech business.
Don N. Kleinmuntz, Ph.D., Principal Kleinmuntz Associates; Adjunct Teaching Professor of IT, Analytics, & Operations, University of Notre Dame – Don is a recognized expert on decision and risk analysis, business analytics and leveraging information technology to improve organizational decision making. Prior to joining the faculty at Notre Dame, he was founder and board member at Strata Decision Technology, a leading provider of financial analytics software to the healthcare industry, where he filled a variety of executive positions including CEO, CFO and CIO. Kleinmuntz collaborated in the design and implementation of budgeting and planning systems that are in use at approximately 1,000 hospitals across the United States, including many large health-care systems and academic medical centers. Over the course of his career, he has consulted with hospitals, multi-hospital healthcare systems, a variety of companies and organizations, and several government agencies, including the U.S. Department of Homeland Security. After receiving his Ph.D. from the University of Chicago, Kleinmuntz held tenure-track or tenured faculty positions at the University of Texas at Austin, the MIT Sloan School of Management, and the University of Illinois at Urbana-Champaign, as well as a part-time research appointment at the University of Southern California
Patrick Lucey, Ph.D., Director of Data Science, STATS LLC - Session: Interactive Sports Analytics: Going Beyond Spreadsheets - Interactive Sports Analytics: Going Beyond Spreadsheets - Imagine watching a sports game live and having the ability to immediately find all past plays which are similar to the play that just happened. Better still, imagine having the ability to draw a play with the x’s and o’s on an interface, like a coach draws up on a chalkboard and finding all the plays like that instantaneously and conduct analytics on those plays (i.e., when those plays occur, how many points a team expects from that play). Additionally, imagine having the ability to evaluate the performance of a player in a given situation and compare it against another player in exactly the same position. We call this approach “Interactive Sports Analytics” and in this talk, I will describe methods to find play similarity using multi-agent trajectory data, as well as predicting fine-grain plays. I will show examples using STATS SportVU data in basketball and soccer soccer.
In his role of Director of Data Science at STATS, Patrick’s goal is to maximize the value of 35 years’ worth of sports data. Previously, he was at Disney Research for 5 years, where he conducted research into automatic sports broadcasting using large amounts of spatiotemporal tracking data. Prior to that, Patrick was a Postdoctoral Researcher at the Robotics Institute at Carnegie Mellon University/Department of Psychology at University of Pittsburgh conducting research on automatic facial expression recognition. Dr. Lucey received his BEng(EE) from USQ and his PhD from QUT, Australia in 2003 and 2008 respectively. He was a co-author of the best paper at the 2016 MIT Sloan Sports Analytics Conference and in 2017 was co-author of best-paper runner-up at the same conference. Additionally, hewon best paper awards at INTERSPEECH (2007) and WACV (2014) international conferences. His main research interests are in artificial intelligence and interactive machine learning in sporting domains.
Sundeep Maini, Executive Director Digital Transformation Group, CGN - Session: Increase Sporting Event Revenue Though Proximity Analytics - CGN uses location technology to capture movements and dwell times of unique individuals in stadiums and arenas without using a mobile app. The data reveals attendee interaction with concessions and vendors, enabling testing to increase sales and consumption. Our optimization analytics are based on many metrics including; wait times; the number of attendees that stop at each concession and the number that pass by; traffic pathways for optimal vendor placement; tracking unique individuals pre- and post-event to restaurants, bars and other nearby establishment.
Over the past 25 years, Sundeep has been working with businesses in a cross section of sectors such as Manufacturing, Health CRWe, Public Sector, Financial, Consumer Products and Utilities on building transformative business strategies and managing complex transformations to deliver exceptional results. Sundeep’s passion has been using technology to make core value streams of a business more competitive and resilient. Currently, he is leading Digital Transformation Group (DTG) within CGN that helps create digital transformation strategies, prepare CIO agenda and improve leverage of technology teams for the enterprise. DTG staffs business intelligence analysts and data scientists to provide business insights for growth opportunities and managing risks. Sundeep also helps small non-profits such as Easter Seals of Central Illinois and Red Cross improve alignment to their mission and strategies on a pro-bono basis. Sundeep has a diploma in general management from Kellogg school at Northwestern, masters in computer science from Wayne State, masters in Economics and bachelor of engineering from BITS.
CGN Global is a business consulting firm that provides innovative solutions, flawless execution and winning strategies to our clients by tackling their Strategic, Operational and Digital footprints. We transform businesses through disruptive models and technologies, and specialize in analytics as well as supply chain and operations. We have recently been named a Forbes 2017 top management consulting firm.
Michael Rechenthin, Ph.D., Lead Data Scientist, tastytrade - Session: Data Science and Collaboration at tastytrade - tastytrade produces eight hours of content and research for active traders and investors. Using financial backtesting and Monte Carlo simulations the research team explores different trading strategies to discover what works and what doesn't. Michael will also speak about how tastytrade is able to create data driven results with a diverse group of researchers.
Michael Rechenthin earned his undergraduate in Finance at Louisiana State University. Upon graduation, he went to work for the Chicago Stock Exchange where he worked as a specialist/trader on the floor of the exchange. After 7 years, he pursued his Masters in Information Technology from Loyola University Chicago and then from the University of Iowa in Management Science. There he studied data science and specifically machine learning techniques for the prediction of stock prices. He currently leads the Research Team at tastytrade, the largest online financial network with 8 hours of daily education content for options traders.
Liz Wanless, Ph.D., Assistant Professor, Undergraduate Coordinator of Sport Administration Program, Ball State University - Session: Customer Relationships and Sales Optimization with Two Revenue Enhancement Case Studies - This two-part session addresses two new applications of traditional predictive and prescriptive modeling techniques to advance critical sport business functions. First, survival analysis is utilized to inform sport customer relationship management, specifically to understand when a customer is likely to defect and the factors that might impact the length of the customer relationship. Second, optimization modeling is leveraged to advance sport salesforce effectiveness, illuminating the optimal balance of revenue-generating activities according to salesforce objectives, constraints, and non-revenue-generating obligations. Attendees will gain an understanding of survival and optimization modeling through the step-by-step exploration of two specific sport cases where the application of both analyses have improved sport business practice. Future applications and the benefits of academic-practitioner partnerships will also be discussed.
Dr. Liz Wanless is currently pursuing a master’s in data analytics from Penn State University. Her research interests surround advanced analytics application to sport business revenue generation strategy. Dr. Wanless actively consults for university athletic programs, professional sport teams, sport event management companies, and community non-profits in the areas of sport fan experience surveys and analysis, donor prioritization and retention tactics, salesforce effectiveness, and customer relationship management. She earned her undergraduate degree from Bates College, master’s degree in sport administration from Ball State University, and her doctorate in higher education from Ball State’s Department of Education.
Russell Walker, Ph.D., Clinical Professor of Managerial Economics and Decision Sciences, Northwestern University - Session: Leveraging Big Data and Analytics for Digital Strategy Formulation in Sports Management - The emergence of digital platforms, especially mobile phones, has disrupted many industries, including many in media. In all of these examples, the operators of the digital platforms, such as Netflix, Uber, Airbnb, Amazon (to name a few) gain a unique ability to influence customers and control markets in powerful ways. That ability is made possible because of the data collected through the digital platform and the analytics enabled. Today, most fans watch sporting events through cable or streaming events that involve a digital platform partner. That digital partner has the ability to measure and even influence the customer in powerful ways. Sports are becoming increasingly digital and with digital comes large amounts of data. Who owns or controls that data? Secondary ticket vendors are a key example of disruption through data in the sports industry. This presentation will examine opportunities and strategies for sports enterprise to leverage digital assets and big data analytics to grow.
Russell Walker helps companies develop strategies to manage risk and harness value through analytics. Professor Walker founded and teaches the Analytical Consulting Lab, Risk Lab, Global Lab, and Digital Lab, all very popular experiential learning classes at the Kellogg School of Management, which bring MBA students together with corporate opportunities focused on data and strategy. Through these classes he has led many studies with leading sports franchises in the NFL, NBA, MLB, NHL and NCAA, and numerous sports management firms. His work has examined the role of digital platforms in the sports and media industry and the use of analytics in the improved management and operation of sports enterprises. He was awarded the Kellogg Impact award by Kellogg MBA students for excellence and impact in teaching. His most recent book, From Big Data to Big Profits: Success with Data and Analytics is published by Oxford University Press (2015), which explores how firms can best monetize Big Data and focuses on the strategic use of digital platforms. He received his Ph.D. from Cornell University. He also holds an MS from Cornell University, an MBA from the Kellogg School of Management and a BS from the University of South Florida.