Sift Case Studies Reducing friction for good travelers across the globe

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	Reducing friction for good travelers across the globe Sift

Reducing friction for good travelers across the globe

Sift

Technology Category	Analytics & Modeling - Machine Learning Application Infrastructure & Middleware - API Integration & Management
Applicable Functions	Business Operation Sales & Marketing
Use Cases	Fraud Detection
Services	Data Science Services
Challenge	Destinia, a Spain-based online travel agency, faced challenges with payment fraud, fraud rings, and occasional friendly fraud due to the global nature of its offerings. The quick access to flights, hotels, and other digital bookings made manual review unscalable, as the team had a narrow window to investigate hundreds of suspicious orders daily. When chargebacks did hit, it often took over two months for the fees to appear in Destinia’s books, affecting analytics. To prevent chargebacks, rather than simply respond to them, Destinia felt that it was necessary to invest in a solution that required less hands-on maintenance and increased the team’s efficiency. Read More
About Customer	Destinia is a rapidly-growing, Spain-based online travel agency (OTA) with offices in Madrid, Cairo, Dubai, and Tehran. There are more than 2 million global travelers using Destinia’s services in 90+ markets. Their website is accessible in over 30 languages, and offers over 500,000 hotels, 600 airlines, and all the travel-related services a traveler might need. The company is among the top 5 OTAs in Spain, and sees 70% of users booking through desktop and 30% on mobile. Destinia is committed to a great experience for both their customers and their business partners, and has worked to stay competitive in an ever-changing market. Read More
Solution	Destinia turned to machine learning to stay ahead of the inevitable surge in fraud. After much research and deliberation, Destinia came across Sift and found that its products came highly recommended among other OTAs and businesses in the travel industry. Destinia committed one developer and one analyst to integrating Sift, and they found the APIs to be clearly documented and very user friendly. Once the solution was in place, Destinia was pleasantly surprised with the speed and accuracy of the Sift Scores and data visualizations. This ratio of high accuracy to low time was essential in proving Sift’s value early on; a rules-based system would have required extensive analysis and continual creation of new rules in order to compete. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Application Infrastructure & Middleware - API Integration & Management

Applicable Functions

Business Operation

Sales & Marketing

Use Cases

Fraud Detection

Services

Data Science Services

Challenge

Destinia, a Spain-based online travel agency, faced challenges with payment fraud, fraud rings, and occasional friendly fraud due to the global nature of its offerings. The quick access to flights, hotels, and other digital bookings made manual review unscalable, as the team had a narrow window to investigate hundreds of suspicious orders daily. When chargebacks did hit, it often took over two months for the fees to appear in Destinia’s books, affecting analytics. To prevent chargebacks, rather than simply respond to them, Destinia felt that it was necessary to invest in a solution that required less hands-on maintenance and increased the team’s efficiency.

About Customer

Destinia is a rapidly-growing, Spain-based online travel agency (OTA) with offices in Madrid, Cairo, Dubai, and Tehran. There are more than 2 million global travelers using Destinia’s services in 90+ markets. Their website is accessible in over 30 languages, and offers over 500,000 hotels, 600 airlines, and all the travel-related services a traveler might need. The company is among the top 5 OTAs in Spain, and sees 70% of users booking through desktop and 30% on mobile. Destinia is committed to a great experience for both their customers and their business partners, and has worked to stay competitive in an ever-changing market.

Solution

Destinia turned to machine learning to stay ahead of the inevitable surge in fraud. After much research and deliberation, Destinia came across Sift and found that its products came highly recommended among other OTAs and businesses in the travel industry. Destinia committed one developer and one analyst to integrating Sift, and they found the APIs to be clearly documented and very user friendly. Once the solution was in place, Destinia was pleasantly surprised with the speed and accuracy of the Sift Scores and data visualizations. This ratio of high accuracy to low time was essential in proving Sift’s value early on; a rules-based system would have required extensive analysis and continual creation of new rules in order to compete.

Impact #1	Sharp decrease in time needed for manual review of transactions
Impact #2	More reliable automated decisions
Impact #3	Fewer blind spots due to not needing to rely on rules

Impact #1

Sharp decrease in time needed for manual review of transactions

Impact #2

More reliable automated decisions

Impact #3

Fewer blind spots due to not needing to rely on rules

Benefit #1	Reduced chargeback rate
Benefit #2	Increased sales

Benefit #1

Reduced chargeback rate

Benefit #2

Increased sales

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Overview

Reducing friction for good travelers across the globe

Operational Impact

Quantitative Benefit