How Touch of Modern saves thousands by staying ahead of fraud rings
Company Size
200-1,000
Region
- America
Country
- United States
Product
- Sift
Tech Stack
- Sift APIs
- Network Visualization tool
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Customer Satisfaction
Technology Category
- Analytics & Modeling - Real Time Analytics
- Application Infrastructure & Middleware - API Integration & Management
Applicable Industries
- Retail
Applicable Functions
- Business Operation
- Sales & Marketing
Use Cases
- Fraud Detection
Services
- System Integration
About The Customer
Touch of Modern is an online destination for the contemporary man to access daily sales on curated designer products. Their members-only e-commerce site and mobile apps allow users to easily discover and purchase interesting electronics, gadgets, fashion, furniture, and accessories at a variety of price points, ranging from low-cost phone accessories to high-end electronics and luxury watches. The company prioritizes customer experience and strives to maintain a low fraud rate. As the company grew, it faced an increasing amount of fraud, which it initially absorbed by paying the costs of any chargebacks incurred.
The Challenge
Touch of Modern, an online destination for curated designer products, was facing an increasing amount of fraud as the company grew. Initially, the company simply absorbed the cost of any chargebacks due to fraud, but this approach was not scalable. The company's customer service team had a very limited window to stop fraud, between processing an order and shipping it. They needed a solution that could accurately stop fraud without blocking legitimate users. The solution also needed to scale with their business, integrate with their internal systems, and automate decision-making to ensure quick processing and fulfillment times.
The Solution
Touch of Modern integrated Sift, a fraud solution that met all their criteria. Sift was integrated in a single day and immediately proved its value by detecting fraud rings among Touch of Modern’s users. Sift’s most powerful feature, according to Steven Ou, Touch of Modern’s CTO, is its ability to detect hidden and complex connections between users. Through the Network Visualization tool, Touch of Modern can easily prevent waves of fraud by unearthing hidden networks. Sift’s APIs provided the convenience and functionality that Steven needed. Touch of Modern pulled Sift Scores directly into its internal consoles using the Score API, which allowed Touch of Modern to quickly decide which orders to approve, block, or review, based on analysis of Sift’s machine-learning algorithms.
Operational Impact
Quantitative Benefit
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