
.png?width=13&height=13&name=Vector%20(1).png)

We enabled frictionless UX and more revenue growth for airline company Azul
The Brazilian airline company Azul is now fully effective in preventing fraud while ensuring frictionless customer UX.
Industries
User’s Lifecycle
About
General Contact
Career Opportunities
Media Inquries
Industries
User’s Lifecycle
About
General Contact
Career Opportunities
Media Inquries
The Brazilian airline company Azul is now fully effective in preventing fraud while ensuring frictionless customer UX.
Industry:
TravelProduct type:
Enterpriseof fraudulent transactions detected during a fraud episode
of new total transactions rejected, significantly lower than before
Azul Linhas Aéreas is a Brazilian airline with the largest air network in Brazil, serving more than 100 national destinations, in addition to operating selected international routes to the United States and Portugal.
The airline sought to enhance its existing anti-fraud capabilities, seeking an option that would work effectively and automatically, cutting operational costs by reducing time-consuming manual reviews. Additionally, they wanted an advanced solution that would identify and prevent all types of fraud affecting their business. There was a strong emphasis on providing a frictionless customer experience, from start to finish of the customer journey.
Coordenador Prevenção a Fraude
Azul
Industry: Travel
Coordenador Prevenção a Fraude
Azul
Industry: Travel
While high fraud rates can be detrimental to a company, false positives - a transaction labeled as suspicious despite being initiated by a legitimate customer - can lead to a huge negative impact on customer UX, resulting in lost custom.
The growing amount of time-consuming manual review traffic generated resulted in large financial costs and unnecessarily burdened the company’s fraud management team.
Rules-based systems can be ineffective in identifying and preventing all types of fraud as they focus primarily on knowing your customers (KYC). The customer wished to have an improved understanding of all the types of fraud affecting their business while having an effective means to prevent them.
Upon successful implementation of our advanced fraud detection and prevention solution with the help of our customer-centric approach, the customer quickly discovered their payments process was much safer than before. They were able to identify new types of fraud affecting their business - something that was not possible with their previous rules-based setup.
The customer was impressed with the capabilities of behavioral biometrics and digital fingerprinting, backed up by machine learning (ML) models to distinguish between good and bad customers and fraud actors. During a specific fraud attack episode, our ML models and signals (triggers that indicate suspicious behavior indicative of a high probability of fraud) detected 89% of fraudulent transactions, compared to 16% detected by the rules-based system, through discrepancies between user account purchase history and use of multiple email accounts. Such detailed analysis is only possible with an advanced fraud solution.
Take advantage of ready-to-take or custom machine learning models for data of all sizes.
Use an intuitive user panel, create rules, automize and customize fraud detection.
Empower your fraud prevention with a dedicated customer success manager and data scientist.
The customer is now delighted to be fully effective in preventing fraud, understanding it is necessary to know your users (KYU) as opposed to knowing your customer (KYC). With KYU it is possible to ensure a frictionless experience for regular customers while blocking fraudsters before they can act.
The benefits of the customer’s improved anti-fraud setup have allowed the company to eliminate unnecessary revenue losses through a reduction in chargeback rates and false positives. Operational costs are down thanks to significantly reducing time-consuming manual reviews.
of fraudulent transactions detected during a fraud episode
of new total transactions rejected, significantly lower than before
Industry: Travel
Fraud type:
Felipe Maia
Coordenador Prevenção a Fraude
Check how we yielded a substantial decrease in ATO incidents and other account-related scams with no harm to the user and with a low false positives rate.
Industry:
Travel, Digital goods & services
How we solved two types of fraud attacks, identity theft and investment fraud, without touching affecting UX.
Industry:
Online lending & BNPL
Luxury eCommerce
We enabled increased conversion rates and lowered the overall chargeback rate and the amount of manually-reviewed traffic for a large fashion marketplace.
Industry:
Ecommerce