Award Date

12-1-2022

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

William F. Harrah College of Hospitality

First Committee Member

Bo Bernhard

Second Committee Member

Brett Abarbanel

Third Committee Member

Ashok Singh

Fourth Committee Member

Shane Kraus

Abstract

Payment providers in the gambling industry facilitate transactions, allowing customers to transfer money to and from wagering accounts. Payments transaction data is information that is captured from these transactions, including, for example, the type, amount, time, and location. How this data may be used for gambling harm minimization and prevention has garnered significant interest, particularly due to accelerated payments modernization in the wake of the COVID-19 pandemic. With this study, I explored the utility of payments transaction data to categorize subgroups of gamblers in order to identify individuals who may be at-risk of harm. I benchmarked six cluster analysis methods using a discovery dataset of 2,286 online casino gamblers obtained from a U.S. gambling payments service provider. The k-means algorithm with five centers was optimal. Two large clusters contained the majority of the dataset (88%) and characterized customers at a low risk of harm from gambling. Three smaller clusters characterized by a high deposit-to-withdrawal ratio (8%), high activity, high intensity (2%), and high volume, high variability (1%) comprised customers at a potential risk of harm. Using a separate validation dataset of 5,580 online sportsbook gamblers, I evaluated the validity of the discovery clustering in terms of (1) the method selected, (2) the results produced, and (3) the stability of membership. The discovery method and results clustered the validation dataset comparatively well, but the stability of membership across the potential risk clusters was low. My results establish that payments transaction data can be used to identify distinct subgroups of gamblers and reveals payment behaviors that could be markers of gambling-related harm.

Keywords

cluster analysis; consumer protection; digital payments; fintech; gambling; responsible gaming

Disciplines

Business Administration, Management, and Operations | Public Health | Social and Behavioral Sciences

File Format

pdf

File Size

2900 KB

Degree Grantor

University of Nevada, Las Vegas

Language

English

Rights

IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/

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