About the challenge

The Financial Entity Identification and Information Integration (FEIII) challenge series aims to provide interesting datasets to researchers at the intersection of finance and big data. These datasets have sufficient data for exploration, but are left noisy and incomplete as they are found "in the wild". Each year we provide a specific evaluation task but we also strongly encourage participants to define tasks that match their research interests.

In year one, we posed an "identifier alignment" challenge: given four databases of financial entities from four different sources, participants needed to find the entities in common across the databases.

For year two, we continued with the theme of identifying and understanding the relationships among financial entities and the roles that they play in financial contracts as represented in documents and databases. The year two dataset consists of 10-K and 10-Q filings, and the task is to identify sentences in the filings that provide evidence for a specific relationship between the filing financial entity and another mentioned financial entity.

Year three continued the work of discovering and understanding relationships among financial entities. The task was to predict the competitors of an organization.


Who can participate?
Anyone is welcome to take part in the challenge: academics, industry, and government, worldwide.

What do I get if I win?
The goal is not to win, but to rise to the challenge. You may have a few different ideas about how to do that. When you submit multiple results, you will be able to see which ideas work and which don't. It might be that your best idea is something that can be added to any system, even the top scoring system, and make it even better. We want to promote research and solutions, not leaderboards and sports matches. We will provide feedback on results distinguished by the following categories of users; you can include these results in your workshop paper:
  • Experts / Vendors
  • Academic teams / Researchers
  • Student teams / Newcomers
Did you say workshop?
Why, yes we did. Organizers and participants will report on the methods and results at the Workshop on Data Science for Macro-Modeling with Financial and Economic Datasets (DSMM2019) - in conjunction with ACM SIGMOD http://sigmod2019.org/ - on June 30, 2019, Amsterdam, NL.

Advisory Committee

Ian Soboroff, NIST
H.V. Jagadish, University of Michigan

Organizing Committee

Doug Burdick, IBM
Cesar de Pablo, BBVA Data & Analytics
Mark Flood, University of Maryland
John Grant, University of Maryland
Joe Langsam, University of Maryland
Jay Pujara, USC/ISI
Louiqa Raschid, University of Maryland
Elena Tomas, BBVA Data & Analytics
Mohammad Zaki, RPI
Elena Zotkina, University of Maryland

Thanks to the following experts for labeling sentences: Don Berndt, Eric Fu, Andrew Staedeli, Mike Bennett, Joseph Proctor, Chetan Saran Mehra, Nitish Sinha, Mohamed Boraie.