Research Working Group Meeting: Fraudulent Tickets and Robocall Scam Tactics
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The meeting featured research from Prof. Yaniv Hanoch, Professor of Decision Science at the University of Wolverhampton; Ryan Moore, Assistant Professor at The University of Texas at Austin; and Dr Doug Shadel, Managing Director at Fraud Prevention Strategies .
Prof. Yaniv Hanoch presented research examining how accurately consumers can distinguish genuine event tickets from fraudulent ones.
Across three studies involving 604 participants , researchers tested participants’ ability to identify real and fraudulent tickets, including scams featuring misspelt text and non-existent seating.
The first study found that participants correctly identified only 42% of fraudulent tickets , while 36% of genuine tickets were incorrectly classified as fraudulent . Participants had particular difficulty detecting scams involving non-existent seating.
A second study examined whether time pressure and ticket scarcity affected participants’ ability to identify fraudulent tickets, but found no significant effect.
The third study tested two scam-focused interventions. Both significantly improved participants’ ability to distinguish fraudulent from genuine tickets and reduced the number of genuine tickets incorrectly identified as fraudulent.
The findings show the challenges consumers face when trying to identify fraudulent tickets based on the ticket itself, while also indicating that targeted interventions can improve detection.
Ryan Moore and Dr Doug Shadel presented research analysing 4.49 million robocall transcripts collected through a honeypot of 295,749 decoy phone lines between 2018 and 2022 .
The researchers used computational text analysis to compare scam robocalls with spam calls and examine how scams targeting older adults differed from those targeting the general public.
The analysis found that scam robocalls used greater emotional arousal, time pressure, threats of loss and appeals to authority than spam calls. Scams targeting older adults showed even greater use of time pressure and threat-of-loss language and were more likely to contain language relating to health, illness and risk.
The research also found a substantial difference in the use of authority. Appeals to authority appeared in 73.8% of scams targeting older adults , compared with 7.1% of scams targeting the general public .
The dataset covers calls collected before the widespread availability of generative AI. The presentation therefore also considered how generative AI could affect robocall scams and what this could mean for consumer vulnerability.
The GASA Research Working Group brings together GASA members and scientific researchers to help develop a stronger evidence base for global anti-fraud policy and interventions.
Its work aims to strengthen global baseline research, identify gaps in current knowledge and improve collaboration between academia and industry. Researchers interested in presenting their work at a future meeting are invited to contact GASA.