05 September 2018
Increasing numbers of people are predicted to fly in the coming year which increases the potential number of claims sent to airlines for delays and cancellations. Under the European passenger rights rule, travellers who arrive at their destination later than 3 hours or whose flight is cancelled at the last minute are entitled to compensation. However, it is estimated that fewer than half of passengers who could claim do.
This is perhaps due to processing and time to reimburse taking several weeks or even months, potentially negatively impacting reputation and future sales. In addition to this, The Consumers’ Association is petitioning for all airlines to offer automatic payment of valid claims however, The Independent reported earlier in the year that airlines are reluctant to do so because of high costs.
Claims processing in the airline industry is, therefore, a prime candidate for the application of machine learning because this offers the chance to speed up claims processing time and generate efficiency savings. Celaton has been providing solutions to train operating companies (TOCs), such as Virgin Trains for over 2 years. These include:
• Manual Delay Repay (MDR) – a passenger is required to initiate the claims process
• Automatic Delay Repay (ADR) – a passenger is compensated automatically without any input
With MDR, inSTREAM receives the passenger claim and using either a booking reference or details from the ticket, it confirms that the passenger purchased a ticket for the journey for which they are claiming compensation. It determines if the journey was delayed using TOC and journey data feeds and then verifies both pieces of information against the claim document. If the claim is valid then inSTREAM calculates the compensation amount due and integrates with the TOC’s CRM system to create a case, enabling the claim to be processed with minimal manual effort. If the claim is not valid it will be rejected, and the customer will be notified. On average TOCs benefited from an 85% efficiency saving.
For ADR, inSTREAM receives a daily file from the TOC of all tickets that have been purchased in advance on their website, it can then identify delays from the previous day. If there are delayed journeys, inSTREAM calculates the amount of compensation due and creates a case in the CRM system. Unlike MDR where inSTREAM creates an action for the passenger to be compensated, with ADR it outputs a file back to the TOC with the details of all the passengers who are due compensation and the TOC automatically refunds the customer’s payment card and an email is issued informing of the refund.
The key advantage airlines have over the TOCs is that they know their customers and how they booked and paid for their flight. They also know if the passenger boarded the plane via the manifest, meaning MDR and ADR could both be beneficial options. Machine Learning technology applied in this way could enable airlines to provide better service to their customers, improve reputation and gain significant competitive advantage in a saturated industry.