How a Leading Fashion Retailer Used Pinch AI to Reduce Return Fraud and Increase Profitability

Company Overview

A prominent e-commerce fashion retailer with ~$70M in annual online sales and a strong presence in North America processes approximately half a million online orders annually. Offering premium apparel and accessories, the company, like many other apparel retailers, has become a target for return abuse despite maintaining a fairly standard return policy. Some insights into their customer base behavior:

• Of all the customers who have returned items, ~50% have returned items from more than one order, while the rest have returned just a single order.
• The overlap between customers who purchase online and those who purchase in-store is about ~6% based on available data.

The Problem: Rising Return Abuse Impacting Margins

The retailer faced a ~10% return rate by dollar value, and their return and refund processing setup led to significant operational costs. Fraudulent return behaviors, including wardrobing, bracketing, and coupon abuse, resulted in substantial losses:

• Wardrobing (high-value items returned after use): Most wardrobed items require significant refurbishment before restocking. Often, these items cannot be sold as new, resulting in final sale markdowns or liquidation.
• Bracketing (ordering multiple sizes/colors and returning most): Customers who size bracketed tended to return more than 40% of such items. The return rate for such instances was 4x that of overall return rates.
• Coupon abuse (multiple accounts exploiting discount codes): A significant number of new accounts were observed using coupons and promos but belonging to the same user—tell-tale signals included identical shipping and billing addresses.

Beyond financial impact, the returns team struggled with manually processing all refunds, leading to delays, inefficiencies, and a suboptimal customer experience. The retailer charged all customers a prepaid return label fee, which reduced customer satisfaction and did not foster long-term loyalty.

The Solution: Pinch AI’s AI-Powered Returns Fraud Prevention

To combat fraud and optimize return workflows, the retailer deployed Pinch AI, an advanced AI platform that helps retailers prevent return abuse while keeping loyal customers happy. The seamless integration with the retailer’s e-commerce, returns management, and warehouse systems enabled proactive fraud mitigation while maintaining a delightful experience for their best customers. Implementation was done in phases with an initial setup involving manual interventions during checkout, returns initiation and returns receiving with the view to automate all interventions over a 30 day period as described below.

Pinch AI Implementation

• 🛒  Dynamic Order Optimization: VIP customers receive elevated return and refund experiences at checkout, promoting customer loyalty and a frictionless return process, including faster refunds. Meanwhile, abusers automatically flagged, restricted, or blocked. Pinch identifies bracketing orders, enabling proactive customer outreach to resolve sizing confusion before order fulfillment. Serial promo code abusers detected, and their discounts canceled.
• 🚚  Adaptive Returns Engine: Pinch AI flags high-risk return requests based on historical abuse patterns, return timing, and customer behavior analysis. These customers encounter friction such as delayed refunds, mandatory in-store returns, and automated return denials. High-trust customers, on the other hand, benefit from extended return windows, instant refunds, and free returns—driving retention and lifetime value.
• 🏪  Smart Returns Receiving: Pinch’s risk signals helps sort and review return parcels from suspected wardrobers separately in the warehouse, improving processing efficiency.
• 🔹  Seamless E-Commerce Integration: Directly connected with the retailer’s order management system (OMS), returns management system (RMS), and warehouse management system (WMS) for real-time fraud prevention.

The Results: $230K+ Saved, 20% Increase in Customer Retention

A lookback analysis of historical data showed that the Pinch platform drove the following annualized outcomes:

✅ $230K+ in Savings – Reduced return fraud losses, operational costs, and coupon abuse.

✅ 50% Reduction in Return Fraud – Lowered fraudulent return attempts.

✅ 11% Returns Automated – Automated approvals and denials improved efficiency.

✅ 20% Increase in VIP Customer Retention – Enhanced return experiences built trust and loyalty.

These results represent just the baseline of what Pinch AI can achieve, with real performance expected to surpass these numbers.

Conclusion: A Future-Proof Return Fraud Strategy

By leveraging Pinch AI’s machine learning-powered fraud detection, this fashion retailer successfully curbed abusive returns, optimized operations, and improved customer trust. The AI-driven return policy enforcement allowed the company to increase profits without alienating genuine customers—creating a scalable, long-term solution for e-commerce return optimization.