What Challenges Were Limiting Baggage Fraud Detection and Claims Auditing?

Low Audit Coverage. High Payout Risk. Sluggish Turnaround.

The airline was struggling with increasing baggage fraud incidents, auditing less than 2 percent of claims manually. With no visibility into repeat offenders and a 3–5 day average resolution time, costs were rising and genuine customers were left waiting.

How Did AI-Powered Auditing Improve Baggage Fraud Detection?

AI-Powered Auditing That Detects, Flags and Learns

WNS deployed a proprietary AI / ML model integrated directly into the claims workflow. The system analyzed 100 percent of claims in real-time (30–50 seconds per case), flagged suspicious activity, identified repeat claimants and delivered over 85 percent fraud detection accuracy. Built, tested and scaled within 8 months, the solution became the airline’s first line of defense in proactive fraud prevention.

What Results Did AI Deliver for Baggage Fraud Detection and Claims Processing?

Baggage fraud prevention is no longer a back-office compliance task. By combining domain knowledge with AI, WNS helped the airline move to an intelligent, scalable and customer-first approach — co-creating a smarter business that is human-led and future-ready.