Leading UK airline, Virgin Atlantic, was looking to improve its customer experience in refund requests which had increased 400x more due to the global lock-downs
The airline partnered with WNS to deploy intelligent automation and transform its operations in processing claims
WNS’ robotic process automation-led solution now ensures swift processing of refund requests and increased accuracy, leading to improved customer satisfaction
This is our story of co-creating and deploying an intelligent automation solution to transform customer experience for Virgin Atlantic, a leading UK airline, when COVID-19 resulted in thousands of flight cancellations during an unprecedented crisis in the history of aviation.
Airlines lose billions of dollars in revenue every year due to poor customer service. The industry is also subject to close scrutiny by aviation regulators. From bookings to refunds to cancellations, airlines need holistic digital transformation, powered by Robotic Process Automation (RPA) and intelligent automation, to ensure timely response to customers and meet stringent regulatory requirements.
It had to deal with a sudden surge in refund requests due to COVID-19. It became apparent quickly that the exponential rise in requests — 400x more than the norm — required a lot more than the high standards that Virgin Atlantic is renowned for.
Delivering superior customer experience across operations had always been at the heart of Virgin Atlantic since inception. In order to maintain customer trust and its reputation, the airline began exploring intelligent automation solutions that could improve efficiencies and reduce the turnaround time in processing and closing claims. The aim was to offer the best possible service to customers during difficult times by meeting their expectations more quickly and efficiently. At the same time, it was crucial to comply with regulatory requirements. The airline industry’s systems and processes in executing claims are complex due to many regulatory and interlinked components.
Virgin Atlantic partnered with WNS, an experienced collaborator with in-depth knowledge of the industry, as it began its digital transformation journey.
WNS leveraged its 20+ years of experience in the airline industry and technology expertise to deploy RPA interventions with zero disruption to Virgin Atlantic’s core operations.
Manual activities that involved processing refunds against multiple airline systems were automated. We worked jointly with Virgin Atlantic to design an optimized to-be process, and choose a third-party RPA platform. Speed and agility came together as we developed and deployed BOTs in less than eight weeks. The BOTs enabled Virgin Atlantic to significantly improve productivity and accuracy, and quicken the refund process.
Diligent planning and innovative design were essential cogs in a collaborative process that brought together various teams such as IT, information security, operations and management across Virgin Atlantic, WNS and the third-party platform provider.
An implementation that would have taken years was completed in eight weeks. Other outcomes include:
~90 percent of the ‘refund-carding’ process is managed through BOTs without manual interventions; each BOT completes three times the transactions as that of a human agent
~30 percent productivity benefits and higher accuracy of claim closure in ticket refunds
~93 percent improvement in the quality of claims processing – without any process re-engineering
The BOTs augment and accelerate the validation of requests by verifying the accuracy of data, rejecting incomplete and duplicate requests, and ensuring country-specific compliance. Virgin Atlantic is now able to work through high claim volumes while reducing backlogs and hold time, resulting in increased customer satisfaction.
The strength of this partnership and the speed at which the process kicked in has enabled Virgin Atlantic to maintain its position as a reputed airline that its customers love and trust — elements that are crucial for its long-term success.
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Travel and Leisure
19 March 2022
31 December 2019
18 December 2019