Trainline partners with Great Western Railway to reduce refund fraud by 39%

Trainline has partnered with Great Western Railway (GWR) to reduce refund fraud by 39% across all its routes.

Trainline’s fraud and tech teams work together to identify customers most likely to claim a fraudulent self-serve refund through analysis of a combination of factors, including previous behaviour. Those most likely to have submitted a fraudulent claim are then systematically contacted in order to prevent further refund abuse.

Collaborating with Ravelin, the leading fraud detection and payments authentication provider, Trainline created the bespoke Refund Protect solution, available to all rail operators, providing them with the insights and support to prevent the refund system from being abused.

Trainline has successfully reduced its online fraud by half since October 2020, including a significant reduction in card payment fraud across its own app and website. Card fraud is where people attempt to buy tickets using stolen details, typically purchased on the dark web. Trainline’s data capabilities have also been key in identifying customers who have bought tickets with a railcard discount applied, without owning a valid railcard.

Champa Magesh, President, Trainline Partner Solutions, comments: “We’re pleased that our technology is supporting our rail operating partners in preventing fraudulent refunds from being claimed. Working closely with our partners to minimise fraud means our teams can be focussed on driving innovation for the benefit of customers, and attracting more travellers to rail.”

Kevin Forrest, Head of Revenue Protection Development, GWR, comments: “GWR has been working closely with Trainline in order to prevent, deter, identify and pursue fraud and fraudsters who commit journey related fraud within the rail industry. Part of the work involves looking at the volume and impact of potentially dishonestly obtained refunds. This project is significantly helping GWR create and deliver an intelligence-led revenue protection function.”

Photo credit: Trainline

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