How to stop returns fraud and abuse with Loop’s fraud detection tool
Vaishali Ravi
·October 29, 2024
Returns fraud and abuse is on the rise all over the globe. Nearly 40% of shoppers said that they or someone they know had engaged in abusive or fraudulent return practices over the past year, according to our recent Fraud Consumer Report. Ninety percent of retailers who’ve experienced fraud and abuse say that the rate has increased over the last 12 months.
The National Retail Federation’s data echoes our findings: Last year, fraudulent returns in the United States increased to an estimated 13.7%, representing $101 billion lost to returns abuse and fraud.
With fraud and abuse on the rise, merchants can no longer afford to automate returns without added protection against unwanted customer behaviors.
Stop fraud and prevent lost revenue in real time
Many merchants don’t have the resources to solve fraud and abuse on their own. Others are oblivious to the problem because they're not actively tracking it, only becoming aware of it when it has hit a costly critical mass. By leveraging data across customers, orders, returns, and returns processing via warehouse integrations, Loop can help merchants level the playing field and tackle fraud at scale.
Loop's machine learning fraud detection model has learned from over 17 million returns which returns are most likely to be fraudulent. Our model automatically evaluates returns in real time, as they are submitted, to flag high-risk returns and prevent revenue loss to fraud
Loop has data on:
- 17.6M returns
- $2.44B in returned value
- 4,000+ active Shops
- 10.8M customers with a return through Loop
- Integrations with Whiplash, Quiet Logistics, NRI, and others
- More than 5,000 return policies configured on the platform
Loop is one of the first companies to offer a specialized fraud detection model for returns.
Loop’s Fraud Model uses machine learning to evaluate fraud risk on returns in real time as they are submitted. Built on state-of-the-art ML algorithms, our Fraud Model enhances accuracy and minimizes false positives to ensure higher trust and confidence while keeping legitimate customers safe from unnecessary disruptions in their shopping experience.
Returns with high risk of fraud can then be actioned using Workflows. For instance, you can exclude the option for the customer to keep the item, or process the return after manual inspection instead of on scan.
On October 1, Loop turned on our fraud prevention feature at no extra cost for nearly 4,000 shops. Since then, we’ve learned quite a bit about who is hiding behind the fraud veil. Our data insights tool has uncovered meaningful trends, and we can break down data to a granular level to closely track individual fraud attempts.
And this is just the beginning. The model improves its accuracy and performance with every new transaction, ensuring it stays up-to-date and continually adapts to emerging fraud patterns.
Uncover the hidden truths behind your returns
Book a demoUsing our Fraud Model to protect your business
By partnering with Loop, you’ll gain complimentary access to our Fraud Model as part of our comprehensive returns operations platform. You can use the tool to automatically monitor for and flag high-risk return attempts, helping you act quickly and reduce your business losses from fraud and abuse. Set up customizable workflows to take action, based on your business’ priorities for balancing a positive customer experience against fraud reduction.
You’ll gain the insights to easily identify and prevent returns policy abuse, protecting your business from customers who take advantage of lenient return practices and ensuring fair usage.
Our Fraud Model successfully detects $0.87 of every $1 of confirmed fraudulent transactions.
Our Fraudsters’ Hall of Fame
Let’s take a moment to appreciate the more than 3,500 fraudsters that Loop has caught to date with their hands in the proverbial e-comm cookie jar!
- Number of fraudsters identified to date: 3,516
- Total amount of revenue these individuals have attempted to steal from Loop merchants: $179,000 (Our model caught 87% of that theft! )
- Average value of fraudulent returns: $326.54
- Record for highest fraud count by an individual: 52, held by an Ohioan—Go Buckeyes!
- Record for most money sought in a single fraudulent return: $5735 (they were trying to steal dresses! )
- Most fraudulent city: Los Angeles
- Most fraudulent city per capita: Yorkville, OH (Go Buckeyes, again! )
- US states NOT represented by our fraudsters: None!
- Percentage of fraudsters who use Hotmail: 4%
- Products most frequently targeted: Cell phone accessories (Apple watch bands, iPhone cases, etc.)
As shoppers are waiting for BFCM deals, so are fraudsters! Learn how Loop’s fraud model can help your brand to identify fraud before it hits your bottom line. Our streamlined platform will reduce the burden on your business to manage fraud, freeing you up to focus on business growth.
Ready to explore what Loop can do for you? Book a demo today.
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