Returns Fraud Prevention: How Growing Brands Protect Margin Without Punishing Honest Customers

Returns Fraud Prevention: How Growing Brands Protect Margin Without Punishing Honest Customers

Why returns fraud grows as fast as your ecommerce success

As your brand grows, so do your returns. Alongside legitimate returns sits a quieter problem: returns fraud. It shows up as wardrobing, where shoppers buy, use, and return as if the product were a free rental. It appears as bracketing, where customers order multiple sizes with no intention of keeping most of them. It includes fake damage claims, returning used or swapped items, or sending back completely different products under the same order number. One return might not hurt much. At scale, these behaviors quietly erode margin.

Returns fraud prevention is about design, not suspicion. You are trying to stop high risk patterns without creating a miserable experience for honest customers who just received the wrong size or a defective item. That balance gets harder as order volume and channel complexity grow.

How common returns fraud practices show up in real life

Returns fraud rarely looks like a movie plot. It looks like everyday behavior pushed just beyond the line. A shopper wears a dress to an event, does a careful rebag and claims it did not fit. A customer orders a premium item, swaps in a cheaper version during the return, and hopes no one notices. Some buyers repeatedly mark items as damaged to avoid restocking fees. Others submit the same receipt across multiple accounts, or return stolen merchandise for store credit.

At scale, you see recognizable patterns: high return rates from specific customers, frequent claims of non delivery followed by returns, repeated size or fit complaints on items that normally fit well, or clusters of damage claims by region or carrier. None of these patterns are proof by themselves. Together, they show where you need better controls.

Where operational gaps make returns fraud easier

Fraudsters do not need sophisticated tools if your operations give them easy openings. Missing scans, inconsistent triage, incomplete inspections, and poor documentation all create weak spots. When the warehouse cannot confirm what arrived, what condition it arrived in, or which order it belongs to, fraud becomes hard to prove and even harder to prevent.

Connor Perkins, Director of Fulfillment at G10, sees how nuance makes returns challenging. "Returns can be tricky," he said. "A good example is apparel, there are times where people order something online, try it on, wear it once, and then want to return it. When that comes back, if the client decides to refund, we have to do our due diligence." He added, "Returns involve a lot of subjectivity."

That subjectivity becomes a doorway for abuse when teams lack structured workflows and clear evidence.

Why inventory accuracy is your first line of defense

Fraud prevention starts with boring basics. If your inventory data is unreliable, you cannot separate honest mistakes from intentional abuse. Missing units might be internal shrink, picking errors, carrier problems, or external fraud. Without accurate tracking, you cannot tell which is which.

Connor described the cost of weak accuracy in general operations. "One of the pain points our clients have experienced with previous 3PLs is inventory accuracy; maybe their previous 3PL was not great at picking the orders accurately. So they were losing money by shipping wrong items or wrong quantities of items." The same issue applies to fraud. If your records are shaky, fraud hides inside the noise.

Policy design that slows fraud without blocking good customers

Returns fraud prevention often begins on your website. Clear, specific policies reduce gray areas. For example, stricter timelines for high risk categories such as electronics or seasonal apparel, more detailed rules for worn items, separate guidelines for final sale, or different rules for repeat high value orders. Many brands now use softer tools as well: sending reminders that items are tracked by serial, including photos on pick confirmation, or clarifying that worn products may be rejected.

The goal is not to scare honest shoppers. It is to signal that your returns process is organized, tracked, and evidence based. Fraudsters prefer disorganized brands.

Omnichannel complexity raises the stakes for fraud prevention

Fraud looks different across channels. On your Shopify site, you may see wardrobing and high bracketing. On Amazon, policy gaming and repeated claims of non receipt can dominate. Wholesale and B2B channels see different risks, such as bulk returns that hide damaged or substituted items. If your fraud prevention approach is identical across every channel, you will miss important patterns.

Jen Myers, Chief Marketing Officer at G10, sees this every day. "We have some customers that come in and build a successful business. They go B2B primarily, and then they know they have to be successful in the D2C space or e-commerce. And they know Amazon is the big gorilla in that space, but maybe they do not know how to navigate it." She added, "It is still e-commerce, right? And so it is still the same beast in a different skin."

Fraud prevention needs to recognize those skins so you can set the right thresholds, rules, and reviews for each one.

The WMS backbone that gives you evidence instead of guesses

A warehouse management system is not just an efficiency tool. It is a fraud prevention tool. A good WMS logs every scan, location change, inspection result, and disposition step. That audit trail is what lets your team say with confidence what happened to each unit and when.

Bryan Wright, CTO and COO at G10, explained this clearly. "A good WMS tracks inventory through the warehouse at every point that you touch it," he said. "At any point in time, I know that Bobby has this product on fork 10 right now."

When your system can show that level of detail, dishonest claims become much easier to dispute and honest customers can be helped quickly.

Using data analytics to spot fraud patterns early

Fraud prevention at scale is a data problem. You cannot investigate every order by hand, but you can use analytics to surface high risk behavior. Common signals include unusually high return rates by customer, address, card, or region, abnormal use of certain reasons such as damaged or not as described, repeated returns of high value SKUs, or patterns where items marked as damaged consistently pass internal quality checks.

Returns data analytics can highlight these patterns long before they show up in your financials. That lets you tighten rules for repeat offenders, adjust product descriptions, improve packaging, or add an extra layer of verification for certain flows without hurting your broader customer base.

Fraud prevention tactics that balance friction and fairness

Practical fraud prevention steps include identity checks for high value orders, requiring photos for certain damage claims, limiting free returns on serially abused products, using RMAs or returns portals with unique identifiers, or delaying refunds for suspicious patterns until inspection is complete. Some brands use tiered policies, where trusted customers enjoy easier returns while high risk profiles face more verification.

The art is in applying these controls precisely. Too much friction for everyone, and you lose good customers. Too little, and you train fraudsters that your brand is an easy target.

Why human judgment still matters in fraud prevention

Automation can flag patterns, but humans decide what to do next. A spike in returns might be fraud, a sizing problem, a bad batch from a supplier, or a marketing misstep. Only a combination of data and human investigation can tell the difference. That is why accessible, informed support still matters.

Joel Malmquist, VP of Customer Experience at G10, contrasted impersonal models with a more direct approach. "It is an offshore team," he said of many providers, and merchants hear only, "'We are looking into this.'" At G10 he explained, "Every single account at G10 has a direct point of contact. You can either email or call your direct point of contact. It is that simple."

Fraud cases often need that level of direct engagement to resolve quickly and fairly.

Stable warehouse teams reduce both mistakes and opportunities for fraud

Internal errors and internal fraud are part of the risk picture too. High turnover increases the chance of miscounts, mislabels, and mishandled items. It also makes it harder to spot unusual behavior because everyone feels new. Stable teams build familiarity with products, processes, and red flags.

Matt Bradbury, Director of Sales at G10, highlighted this advantage. "We have a very low churn rate," he said. "As far as industry standard goes, we have to be well below the norm. We churn fewer customers, and we churn fewer employees."

That stability helps close the loop on both external and internal fraud risks.

Turning returns fraud prevention into a long term advantage

Returns fraud prevention is not about catching every bad actor. It is about building systems that make abuse harder, evidence clearer, and honest customers better served. With clear policies, strong WMS tracking, thoughtful use of data analytics, and stable teams, you can reduce fraud losses without turning your store into a fortress.

G10 Fulfillment builds fraud conscious returns workflows that combine visibility, structured inspection, and data driven insight. If returns feel expensive, murky, or easy to game today, improving fraud prevention may be one of the fastest ways to protect margin as you grow.