How PayMongo minimized fraud losses and scaled securely by 10-20x
公司规模
SME
地区
- Asia
国家
- Philippines
产品
- Sift Payment Protection
技术栈
- Machine Learning
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Productivity Improvements
- Customer Satisfaction
技术
- 分析与建模 - 机器学习
适用行业
- 金融与保险
适用功能
- 商业运营
用例
- 欺诈识别
服务
- 数据科学服务
关于客户
PayMongo is a financial technology company that provides simple, modern payments for forward-thinking businesses. The company helps businesses in the Philippines accept online payments from multiple channels quickly and easily, in a matter of minutes. Their mission is to become the invisible engine of commerce that gives everyone the opportunity to participate and succeed in the rapidly transforming digital economy.
挑战
During the early stages of the company, PayMongo encountered fraud attacks that resulted in financial losses, including an alarming 4% dispute rate. It was crucial for the startup company to prevent this fraudulent activity in order to enable their merchants’ success and scale their own business. In their search for the perfect fraud solution, PayMongo was introduced to Sift at a Y Combinator event and agreed to an assessment. Following the review, PayMongo concluded Sift Payment Protection was an ideal fit for what they were looking for in a fraud tool.
解决方案
Members of PayMongo’s Fraud Operations team use Sift for transaction monitoring, case management, setting workflow rules, and routing payments. The team utilizes almost every feature of the Payment Protection product, including automated workflows to set up review queues, as well as create rules and thresholds. The team also relies heavily on insights within the console to monitor workflow metrics, reports, and team performance. Sift’s machine learning capabilities help PayMongo automatically block high-risk and possibly fraudulent transactions. The team tailor-fits workflows according to the observed fraudulent patterns on their platform and is able to update them as fraud trends evolve. For additional support, PayMongo consults with senior engineers, fraud experts, and others at Sift for guidance and consultation.
运营影响
数量效益
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