Analyze Holiday 2020 Fraud

February  26, 2021

The holiday season has come and gone, which means that there is planning ahead for the 2021 season. Planning further entails looking at 2020 holiday fraud-prevention tactics to identify best practices and areas for improvement.

One of the key differences has been the trend to earlier holiday sales that did not primarily focus on Black Friday and Cyber Monday. Systems might have performed differently than presumed during other sales peaks, so let’s take a look at the process.

Fraud Prevention Performance

Now is a good time to track and analyze chargeback ratio for November through December. Once calculated, you can compare those ratios to the rest of 2020. How did fraud occurrences during the 2020 holiday season compare to the rest of the year and even to 2019?

If there was a measurable increase in fraud during the 2020 holiday season, what kinds of transactions managed to shirk fraud filters in place? Possible attributes needing examination:

Commerce channels: Mobile, social, web, BOPIS and point-of-sale all have their own fraud risk profiles.

Products: Fraudsters often target products or categories that ship fast and are easy to resell.

Locations: Fraud ring activity can show up as a surge in orders from or to a specific area.

Customer profile: New customers can be fraudsters, while fraud by existing customers can indicate account takeover.

Payment methods: Which were used most often in transactions that were charged back?

Now, if your chargeback ratio managed to decline, great job! What did you implement during the holiday season that led to lower rates of fraud? Was a new system enacted? Were only fraudulent charges captured or were good orders rejected, as well?

Rejecting Good Customers/ Orders Change

In the event you do not manually review flagged transactions, you are likely to deal with false declines. While fraud screening tools are excellent filtration systems they can record simple errors, such as mismatched billing addresses, as a means for declining orders that could easily have been verified by a human.

Declining good order is costly in both the short and long term. According to a March 2020 Sapio survey, the immediate hit to profits is dwarfed by the fact that 39% of customers will not return to a store if their initial payment was rejected. Furthermore, 28% of customers stated they would post complaints on social media, highlighting any issues in play to your online business.

Another interesting data point was noted: only 14% of customer revealed they would never go back to a store where they experienced fraud. This figure suggests just how personally consumers take rejection as oppose to incidences of fraud.

Setting aside both the time and resources to manually pull and review random batches of holiday orders enables calculation of holiday false declines and give incite to changes that should be made to limit those instances.

Address Problems Now for a Smoother 2021 Season

Tuning automated rules for fraud patterns in your store reduces chargebacks. These adjustments can be set for year-round implementation or used only for the holiday season, depending on fraud trends and yearly timelines.

To fix false declines, manually review flagged orders brought up by your automated system. Creating the infrastructure to handle these issues now means higher order approval rates, larger volumes, and more profit with less customer turnover.

Reducing false declines help build a greater base of repeat customers that you can market to, especially around holiday season. Your brand image is helped by fewer customer complaints on social media and as manual approvals teach the system’s algorithm to get smarter about fraud orders, there is faster turnaround time for order fulfillment.

Taking your fraud data into account can give you a leg up in 2021 while offering better customer experiences. Consider it a key task for the new year. 

The Payment’s Journal has this and other great information available here.

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