Top Indian Airline Uses Sutherland Robility Automation for 40% Faster Refund Audits

Read our case study on how Sutherland helped a top India airline save time and manpower with Sutherland Robility.

The Challenge

Boosting Efficiency with Less Manpower

India’s largest airline comprises 127 Airbus and Boeing aircraft, serving 102 domestic and international destinations from its hub at Indira Gandhi International Airport in New Delhi and several additional cities across the country. In 2019, it occupied 18.6% market share with $3.7 billion in revenue.

Relying on agency debit memos (ADM) to recoup losses from travel agencies that were processing refunds in error or in violation of policy, the airline’s manually oriented system was time consuming, labor intensive, and wrought with inefficiencies. In fact, 32% of all refunds were not being audited due to complexities. The airline needed a solution for speeding turnaround time on spotting violations and recovering funds with less cost and personnel so that no refunds would go unaudited.

The Outcome

Automated Solutions Driving Real Business Outcomes

Fusing robotic process automation (RPA) bots with the travel industry’s largest reservation system – Sutherland’s engineers applied a streamlined, end-to-end solution for finding, tagging, and resolving refund violations. Once the industry platform tags potential violations, the RPA tool verifies and groups them by non-refundable tickets and those refundable with a normal cancellation or no-show fee. RPA further tracks potential malpractice by comparing ticket fees and penalties against agent payouts and raising ADM amounts to match any discrepancies without manual intervention.

Freeing up personnel for business-driven tasks and speeding turnaround time for resolving violations and eliminating human error, the automated Sutherland Robility solution produced immediate recovery results. Moreover, the airline continues realizing benefits from the expertise, insights, and best practices gained through its Sutherland partnership.

20%

Improvement in identifying the ADMs

50%

Overall workforce was reduced

40%

TAT reduction