We were tasked by a major U.S. rapid transit system to determine the true rate of fare evasion at the turnstile, and assess the resulting potential revenue loss. Working in conjunction with a team of internal auditors, we adopted a stratified sampling methodology and developed methods for discreet (although not completely clandestine) observations at subway fare control areas. During this project, we discovered that the system in fact had a comprehensive pre-existing framework for managing and combating fare evasion, although it did not report any reliable statistics. The Automated Fare Collection (AFC) system actually features lessons learned from field trials of prototypes specifically designed to limit fare abuse. We found at that time the annual average subway evasion rate remained relatively low at approximately 1.3%, although there were distinct patterns by time of day, type of fare control, rider demographics, and geography. Evasion rate peaks at 3pm due to students dismissal, otherwise hovers around 0.9% peak, 1.9% off-peak. Busy times and locations have higher evasions per hour but lower evasions per passenger. More evasions occur in lower-income neighborhoods. Staff presence apparently doesn’t reduce evasions. Perhaps counterintuitively, we recommended that fare evasion enforcement should focus on high volume stations and time-of-day to maximize deterrent effect. The transit agency implemented a continuing program to monitor the true rate of fare evasion following this audit, and addressed issues relating to fare structure, probability of enforcement action, versus fixed-penalty fines.
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