下载PDF
Reducing friction for good travelers across the globe
技术
- 分析与建模 - 机器学习
- 应用基础设施与中间件 - API 集成与管理
适用功能
- 商业运营
- 销售与市场营销
用例
- 欺诈识别
服务
- 数据科学服务
挑战
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.
关于客户
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.
解决方案
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.
运营影响
数量效益
相关案例.
Case Study
Largest Production Deployment of AI and IoT Applications
To increase efficiency, develop new services, and spread a digital culture across the organization, Enel is executing an enterprise-wide digitalization strategy. Central to achieving the Fortune 100 company’s goals is the large-scale deployment of the C3 AI Suite and applications. Enel operates the world’s largest enterprise IoT system with 20 million smart meters across Italy and Spain.
Case Study
KeyBank's Digital Transformation with Confluent's Data in Motion
KeyBank, one of the nation's largest bank-based financial services companies, embarked on a national digital bank initiative following the acquisition of Laurel Road, a digital consumer lending business. The initiative aimed to build a digital bank focused on healthcare professionals looking to refinance student loans and buy homes. A significant challenge was reducing the time to market for new products by democratizing data and decoupling systems across the IT landscape. Like many large enterprises, KeyBank had a variety of vendor applications, custom applications, and other systems that were tightly coupled to one another. New projects often required developing specific point-to-point integrations for exchanging data, which did not address the needs of other downstream systems that could benefit from the same data.
Case Study
Bank BRI: Revolutionizing Financial Inclusion in Asia with Digital Banking
Bank Rakyat Indonesia (Bank BRI), one of the largest banks in Indonesia, was faced with the challenge of increasing financial inclusion among unbanked Indonesians. The bank had an ambitious target of having 84 percent of Indonesians participating in the banking system by 2022. However, the bank's legacy technologies were proving to be a hindrance in achieving this goal. Each of the bank's products had their own public APIs, which were difficult to manage, secure, and monetize. Additionally, the process of onboarding new partners using host-to-host and VPN technology was time-consuming, taking up to six months. The bank also faced the challenge of reaching a largely rural population, with an estimated $8.3 billion in currency being held outside the banking system.
Case Study
Neobank Transformation: Enhancing Compliance and Security
The client, a leading specialist digital challenger bank based in the UK, was faced with the challenge of redesigning and rebuilding their mobile banking application. The goal was to provide a more convenient way for their customers, primarily small businesses, entrepreneurs, and consumers, to interact with their platform. Additionally, they needed to implement Open Banking, a mandatory requirement from the UK financial institution. Prior to this, the client had outsourced the development of its mobile app to other vendors. However, they needed a strong team that would take over the development completely and implement new features to improve the functionality for both the client and its customers.
Case Study
Increasing Efficiency Through Automation and Modernization for Boohoo Group
Boohoo Group, a leading British online fashion retailer, faced significant challenges due to rapid growth and acquisition of other retailers. The company needed to modernize several internal systems used for warehouse management and tax calculation to maintain efficiency. The existing systems were causing data discrepancies and issues in product tracking. Additionally, a lot of data was stored in Excel files and had to be processed manually, which slowed down operations and increased expenses. The company aimed to automate these manual processes and modernize the existing solutions to boost their efficiency.
Case Study
Aerospike Achieves One Million Writes Per Second on Google Compute Engine with Just 50 Nodes
Aerospike, an open-source, flash-optimized, in-memory NoSQL database, was looking to push the boundaries of Google's speed on Google Compute Engine. The challenge was to meet high throughput, consistently low latency, and real-time processing, which are characteristic of future cloud applications. The team at Aerospike was inspired by Ivan Santa Maria Filho, Performance Engineering Lead at Google, who demonstrated 1 Million Writes Per Second with Cassandra on Google Compute Engine. The goal was to benchmark Aerospike's product performance on Google Compute Engine and see if it could scale with consistently low latency, require smaller clusters, and be simpler to operate.
