5 best practices for preventing refund fraud in food delivery Featured Image

5 best practices for preventing refund fraud in food delivery

Safeguard the integrity of your food delivery service! Learn five best practices for preventing refund fraud.

Food delivery services have revolutionized the way we enjoy our favorite meals, offering convenience and culinary delights at our fingertips.

When everything goes according to plan, the customer orders food using their favorite food delivery app, a driver picks up the order and delivers it, and payments are exchanged successfully.

Of course, occasional hiccups are a natural part of a platform’s operations, and sometimes customers receive the wrong food or no food at all. In these cases, it’s important that the app’s users have some sort of recourse to claim some or all of their money back.

However, problems start to arise when less scrupulous users take advantage of fair refund policies for their own benefit.

Refund fraud and its impact on food delivery 

Refund fraud happens when someone illegitimately claims a refund for a good or service they successfully received. Also known as “friendly fraud,” or “chargeback abuse,” refund fraud is a significant concern for food delivery apps and the restaurants they partner with.

Back in 2021, a popular Los Angeles restaurant was even forced to close permanently after receiving so many fraudulent chargebacks and scam refund requests that they could no longer keep up with the demands of the business. Though one person claiming a fraudulent refund for a pizza they didn’t want to pay for may seem like a non-issue, at scale this type of activity has the power to do real damage.

However, refund fraud can also be more difficult to identify and combat than other types of fraud. For example, in the case of someone using a stolen credit card to order food, determining whether there’s been fraud is much more cut-and-dried than determining whether someone that’s claiming their food delivery never arrived is telling the truth or not. The last thing a platform wants to do is react negatively to legitimate refund claims, but this presents the challenge of separating abusive refund requests from legitimate ones. And of course, even if the platform can identify an abusive refund request, there’s also the question of how they should respond.

Five best practices for preventing refund fraud 

Combatting refund fraud presents the food delivery industry with unique challenges, but it’s far from impossible. Below are a few best practices that can help reduce fraudulent refund numbers. 

1. Ask drivers to verify deliveries when possible 

Drivers can often verify deliveries by taking a photo of the food at the customer’s door or by asking the customer to provide a code generated by the app to confirm both recipient identity and successful delivery. Though these practices can add a bit of friction to the delivery experience for drivers and customers, it’s one way to help reduce refund fraud numbers by limiting the number of misunderstandings surrounding missing or failed food deliveries. 

2. Identify and block repeat offenders 

Many users, especially those who use the app frequently, are bound to encounter issues at some point or another that warrant a full or partial refund. While occasional refund claims are par for the course, users who abuse refund policies should be penalized appropriately.

Particularly dedicated refund abusers may create new accounts to get around bans, suspensions, or other penalties for abusing refund requests. In these cases, it’s important that platforms have a way to identify individuals across devices and accounts. Location and device intelligence can help prevent the multi-accounting and ban evasion that enables serial refund abusers to thrive with less accountability risk. 

3. Analyze refund fraud trends to assess risk of orders before completion

Some transactions are at a higher risk for refund fraud than others. For platforms struggling with high numbers of fraudulent refund requests, it may be beneficial to analyze existing data on legitimate and illegitimate refunds and identify trends that lend themselves to higher risk.

This is another area where location and device intelligence provide useful context. Device intelligence can identify common fraud risk factors like the presence of app cloners and app tampering tools. Location intelligence can help identify additional risk signals like a high concentration of risky devices in a single location, or activity from a location previously associated with confirmed fraud. 

4. Review refund requests thoroughly and ask customers for additional information where applicable 

While manual review may be expensive and time-consuming, relying on machine learning or algorithms to automatically accept or decline refund requests can leave an app vulnerable to refund abuse or to false positives (in which legitimate claims are denied with little explanation). By training humans to review refund requests with higher risk assessments, platforms can ensure a more holistic approach to this aspect of the customer service solution. 

5. De-incentivize refund abuse by limiting cash refunds 

In retail environments, offering store credit instead of cash refunds in the case of higher-risk returns (for example, returns without a receipt or beyond a certain time threshold) has been a standard practice for decades.

Mobile apps can use the same approach and de-incentivize refund abuse by limiting cash refunds unless requests meet certain criteria. Offering app credit or discounts as opposed to cash refunds for higher-risk requests can help discourage refund abusers by reducing any potential monetary reward for requesting fraudulent refunds.

Food delivery platforms are committed to providing a good experience for their users, and sometimes that means providing refunds when things go wrong. However, when people abuse these policies, it can hurt the platform and the restaurants it partners with. Using best practices like those outlined above, food delivery apps can safeguard the integrity of their refund process.