Fighting fraud isn’t easy. It’s time-consuming, it’s challenging, and it’s expensive. Artificial intelligence (AI) approaches seem like a better approach.
After all, AI can quickly analyze extensive amounts of customer data to identify emerging fraud patterns. By incorporating this insight into fraud risk scoring algorithms in near real-time, you can lower your risk of falling victim to fraud.
Well, maybe. For all the benefits AI-based fraud solutions can offer, the technology does have some limitations when it comes to evaluating credit card transactions.
Advantages of AI-Based E-Commerce Fraud Management
Where AI excels is its ability to quickly review incoming transactions. The algorithms can calculate fraud risk scores far faster than manual reviewers ever could, which means for businesses that must deal with a high volume of incoming orders, AI can be the difference between speedy approvals and disgruntled customers.
There’s a cost aspect to this as well. Because this initial review of incoming orders can be automated, you don’t need to spend valuable (read: expensive) man-hours reviewing each individual order. This can tremendously cut down operating costs, and it enables you to focus your analysts’ attention only on those specific orders that require further investigation.
And finally, AI can be very helpful at spotting obscure patterns in fraud that might not be readily apparent to your average reviewer. This is particularly true if you have a good amount of high-quality, validated information on past orders.
Where AI-Based Fraud Management Falls Short
That said, there are several circumstances where AI alone will not be sufficient to manage e-commerce fraud and may even prevent you from maximizing sales.
1. Auto-Declining Orders
AI does a great job of auto-approving good orders and flagging potentially fraudulent orders. But AI should never be trusted on its own to auto-decline orders. Statistics show false declines – that is, accidentally declining orders that are actually legitimate – is a very high, very real risk for e-commerce merchants.
By all means, use AI to flag orders that might be fraudulent. But always, always review those orders before declining them. False declines cost businesses 13 times more than credit card fraud. Validate every decline decision, so you are confident you’re not inadvertently ruining a relationship with a perfectly good customer simply because they’re trying to ship a gift to a different address (which is a common reason for false declines).
2. Lack of High-Quality Data
AI is only as good as the data it receives. If your product is brand new or highly unique, your AI-based fraud solution may not have the data it needs to make accurate approval decisions. In these cases, an AI solution may end up declining orders that are good – and the AI algorithm may inadvertently become more conservative as time goes one and decline more and more future orders.
For these types of products, flexibility will be key to ensuring you’re able to maximize sales without also increasing your chargebacks. This may require turning off (or loosening the standards) for your AI solution while you closely monitor actual sales and fraud trends, study your potential risk, and modify your fraud strategy based on your learnings.
3. Troubles with Fraud Filters
At the core of many AI solutions lies the ubiquitous fraud filter. Fraud filters use rules to evaluate incoming transactions; if a transaction meets certain criteria, the transaction will be either flagged for review or auto-declined.
The problem, therefore, is whether the fraud filters are set up properly. It’s tempting to think that if one fraud filter catches some fraud, more fraud filters will catch even more fraud. Unfortunately, this isn’t always the case. Layering filters incorrectly can result in some rules canceling others out, leaving you as vulnerable as if you had no fraud protection.
Moreover, smart fraudsters know how to “play” the fraud filter game. For example, it’s not terribly difficult for a fraudster to test your system with a series of orders and eventually learn that orders under $1,000 are typically approved, whereas orders over $1,000 are typically reviewed. Once they learn this, they’ll flood your system with batches of orders of $999 that enable them to fly under your fraud filters’ radar, completely undetected.
A Better Approach: AI Plus Expert Review
Perhaps the smartest approach is to combine the best of both worlds: Implement a comprehensive fraud management solution that combines AI technology with expert fraud analysis.
This multilayered approach enables you to harness all the efficiency benefits of AI, so you don’t have to slow down the order approval process – and it also safeguards your business against the risk of accidentally auto-declining orders from your best customers. In this type of approach, AI might be used to auto-approve good orders and flag orders that are suspicious. The fraud analyst team can then manually review these flagged orders and either validate the order or confirm the decline decision.
A seamless online ordering experience for customers, a more accurate approach to fraud detection, and the ability to grow sales safely.
Here at ClearSale, we use exactly such an approach: A combination of advanced fraud detection technology reinforced with a team of more than 700 experienced analysts — creating a powerful one-two punch that lets merchants stay one step ahead of fraudsters.
If you’d like to learn more about how our approach compares to other fraud solutions on the market, download our “Fraud Protection Buyers Guide.” This free guide walks you through your options and helps you ask the right questions, so you can be confident you’ll select the fraud protection solution that works best for your business.