Facteus Collaborates with New York University to Bring Unique Alternative Financial Data to the Courant Institute
Agreement with Courant Institute of Mathematical Sciences will help students and faculty uncover critical insights on consumer behavior while maintaining data privacy
Facteus, the leading provider of actionable insights from alternative financial data, announced an agreement with New York University’s (NYU) Courant Institute of Mathematical Sciences to provide faculty and students access to consumer spending data for use in the classroom, as well as for a multi-faceted capstone project intended to encourage students to think critically and solve challenging problems prior to entering the workforce.
The use of Facteus data for the capstone project, Debiasing Transactional Alternative Data to Maximize Population Representativeness, will begin immediately. The M.S. in Mathematics in Finance program at NYU Courant will implement the use of Facteus data as part of the curriculum for graduate students taking the course Alternative Data in Quantitative Finance, taught by Prof. Gene Ekster, beginning in October of 2021. NYU’s Mathematics in Finance program is an educational leader in quantitative finance and financial data science globally.
NYU’s Courant Institute is a leading center for research and education in mathematics and computer science. Faculty and students are engaged in a broad range of research activities, which includes application of these disciplines to problems in the biological, physical, social, and information sciences.
“In order for our faculty and students to produce thorough, impactful and meaningful research, it is critical they have access to the most important data sets used by today’s quantitative financial practitioners,” said Prof. Petter Kolm, Director of the Mathematics in Finance program. “Facteus’ consumer transaction data provides NYU’s students with one of the most widely used types of alternative data utilized by investors.”
To protect consumer privacy and comply with data regulations, Facteus goes beyond the process of simply trying to anonymize the data. Facteus’ Mimic synthetic data engine transforms raw transaction data into a new synthetic data set that maintains the statistical value of the original transactional data, while removing Personally Identifiable Information (PII) that could be traced back to the original raw data. This completely secure synthetic data can be used for research, analytics, machine learning, and other business or investment initiatives.
“Facteus data provides a unique understanding of the drivers behind consumer behavior and business trends not available in other transactional data panels today,” said Chris Marsh, CEO of Facteus. “Particularly given the challenges of the current environment, the ability for the next generation of data scientists, researchers and analysts to quickly tap into a comprehensive, real-time view of shifting customer behaviors is critical to learn and ultimately to compete at the highest level.”
Business and investment analysts using Facteus data can gain granular insight into consumer spending and business impact at the industry level (retail, entertainment, hospitality, etc.) or at the specific company level. The transactional data offers a comprehensive, real-time perspective into evolving customer behaviors, such as where consumers are shopping, how much they are spending at specific merchants, and through which point of sale (in-person or online). This granular view can provide investors and analysts an informational edge when making investment decisions, sizing markets, or developing new products.