Fraud is a major pain point for airlines with huge cost implications. In spite of the revenue leakage, high penalty for chargebacks, and losses incurred through data theft and reputation damage, most of the airlines are not equipped to prevent and manage fraud robustly. They still use traditional rule-based legacy systems that fail to detect fraud completely, depend on manual reviews which makes the fraud detection process slow and, at times, ineffective.
Moreover, with the traditional techniques, airlines fail to recover the loss incurred. For example, take the case of friendly fraud. When a card issuer submits a chargeback, the amount of the disputed transaction is deducted forcibly from an airline merchant’s account in addition to any applicable fees. However, since this is typically done after the flight completion, airlines are unable to resell the seat. Similarly, in genuine cases, delay in the processing of the chargeback requests frustrate customers.
To mitigate such instances and other frauds, airlines need to embrace digital technologies such as Machine Learning and Artificial Intelligence. Let’s first understand the different types of fraud and the challenges airlines encounter when fighting these before we look at the relevant solution.
Fraud scenario in the Airlines industry
In 2019, the Airlines industry witnessed 61% increase in frauds – the highest compared to other sectors. Fraud can occur at any stage – be it booking, payment or even after sales. The most frequent frauds encountered by airlines include:
- Account hacking and synthetic accounts: Fraudsters hack customer accounts, or create new accounts with a false or stolen identity, and use these to book tickets or misuse other services.
- Loyalty fraud: Use of stolen loyalty points for booking tickets, accommodation, purchase merchandises or other services; and use of stolen cards to open a fake loyalty account.
- Rewards abuse: Fraudsters buy high-value tickets to win reward points. Once these reward points are sold or used, they cancel the ticket.
- Agent fraud: Some agents fraudulently charge cancellation fees to customer
- Card fraud/Chargebacks: This involves using stolen cards for different purchases, or “friendly fraud” where a fraudster files a chargeback for a genuine transaction.
Challenges Airlines encounter while fighting fraud incidents
- Checking legitimacy of transactions – a problem of false positives: Traditional fraud filters reject the probable fraud transactions and manual process often takes time to verify whether the transaction is genuine.
- Increase in chargebacks/friendly fraud leading to revenue loss for airlines: Friendly fraud is on the rise, and airlines fail to detect it quickly. As a result, airlines end up paying a high penalty against chargebacks.
- Absence of internal capability to fight fraud efficiently: Airlines lack the latest technology platform and in-house domain expertise.
- Negative impact on brand image through social media: When airlines fail to provide adequate support to customers who encountered fraud, the experience is shared on social media – thus creating negative sentiment.
Mitigating fraud with a smart hybrid model – The combined power of human and artificial intelligence
The smart hybrid model combines technology platforms and service layers along with analytics to manage fraud end-to-end. It brings together technology and humans where Machine Learning and Artificial Intelligence-driven platforms analyze and detect fraud, while highly skilled subject matter experts verify grey areas. This model offers a one-stop solution that can identify and process fraud across different channels starting from the consideration phase of booking to the feedback phase of a customer. This smart hybrid approach fights various types of fraud in the following ways:
Mitigating fraud in web channel sales and loyalty account: Analyze the pattern of the customer starting from booking until he/she logs out, and identify anomalies in transactions in different channels.
Mitigating friendly fraud/chargebacks: Identify and dispute bogus chargebacks across different channels and process refund or adjust loyalty awards.
Mitigating agent fraud through sales transaction monitoring: Identify suspicious booking agents by analyzing sales transaction details, and then investigating each outlier case manually for fraud positive.
Improving online reputation across social media: Recognize potential fraud by examining various social media channels and then resolve the issue by working with the concerned teams. Within social media, it is possible to promote customer engagement, participate in conversations, and address concerns.
The smart hybrid approach not only follows the reactive mechanism to detect fraudulent activities but also involves a proactive method to prevent fraud using AI tools like Adaptive Behavioral Analytics. It ensures complete checking of transactions irrespective of the type and source, and reduction in false positives and turnaround time. Overall, airlines can reduce revenue loss and improve customer satisfaction by adopting this approach.
Winning with collaboration
The smart hybrid model for mitigating fraud blends technology and people that allows airlines to block suspicious customers or agents, monitor fraudulent transactions, and minimize the penalty for chargeback rates. For an ultra-competitive and expanding airline business, this reduction in revenue loss and improvement in brand image and loyalty will enhance business growth as well as market share.