Fraud Scoring: How Quantifying Your Risk Helps Prevent Abuse
Every eCommerce transaction is unique. At the same time, some elements of a transaction will be pretty consistent for most buyers.
Let’s say you’re looking at one, individual customer. Indicators like IP address, ZIP code, and shipping preferences should remain more or less constant from one purchase to the next. If an order comes in that completely bucks an established buying pattern, you should know to take a closer look, as it may be a case of fraud.
What about orders that straddle the fence, though? Orders that raise a few flags, but maybe not enough to reliably say it’s a case of fraud? You have to make a judgment call. But, even that can be tricky.
If you’re too lenient, you may end up accepting a fraudulent order. If you’re too careful, you end up rejecting legitimate customers. That’s where fraud scoring comes in, giving you the power to make smart, consistent choices about whether to accept or reject orders.
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What is Fraud Scoring?
- Fraud Scoring
Fraud scoring refers to the process of quantifying the level of risk involved in a transaction. Machine learning technology examines each transaction based on dozens of different indicators, then assigns a simple numeric score representing the transaction's risk level.
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In a way, you can think of fraud scoring as being like a consumer credit rating. The system assigns different values to different elements of a transaction; dollar value, product category, AVS response, and other indicators are all examined. Points are then added or subtracted according to predetermined rules, and a final score is calculated. This score helps quantify the amount of risk a transaction presents.
Many payment gateways offer built-in fraud scoring, but third-party options are also available. Make sure you look carefully at things like customization capability and cost-per-score when considering different service providers, though. It's important to have a fraud scoring system that you can set for your specific business needs and budget.
Fraud scoring is also sometimes called “transaction risk scoring.” That’s actually a more accurate term, but most people just shorten it to “fraud scoring” for brevity’s sake.
How Does Fraud Scoring Work?
So, that’s the basic idea. How does it actually work in practice, though? Basically, the software starts by running down a list of factors, including:
- Dollar value of sale
- AVS response
- Category of merchandise
- Customer IP address
- Order history
- Shipment method
- Social media presence
- Buyer’s time zone
- Time of order
- ZIP code
There can be many other elements. The main point, however, is that the final transaction score is not a random guess. It doesn’t hinge on any single piece of information. Rather, the risk is predicted based on a mathematical model.
Numeric values are assigned to each element of an eCommerce transaction. Clear fraud indicators, such as a missing CVV code, are weighted more heavily than something like a misspelling on the street name. Basic rules for creating these values may be inherent in the software or script. You can tweak the specifics, though, choosing different elements and weighting them to reflect your business or industry.
The Fraud Scoring Transaction Flow
Let’s say a customer reaches checkout. They submit their billing info and shipping information, then click to complete the purchase. That’s when fraud scoring kicks in. The technology goes through the following steps:
Again depending on your preset rules, the technology will either accept the purchase, reject it, or flag for manual review, based on the score.
To illustrate, let’s say most of the information provided by the buyer checks out. But, the buyer appears to be using a proxy server, as well as an ISP from a datacenter. Both of these are common fraud indicators.
Depending how you’ve set your rules for fraud scoring, these red flags could be weighed heavily, and might push the fraud score above the threshold for automatic approval. Then, again depending on how you’ve set the parameters, the transaction could be flagged for manual review, or rejected outright.
How is Fraud Scoring Used?
Fraud scoring is most helpful for cases that are not clearly fraudulent, but not clearly legitimate, either. Consider this example: imagine a regular customer lives in Iowa, but is staying in Singapore for business. The buyer makes a purchase using a Singapore address. Generally speaking, this would be a clear red flag for fraud.
With the benefit of fraud scoring, though, this will be weighed against other indicators. By looking at the transaction holistically, the tool determines that the purchase is valid and can go ahead.
In contrast, you may have a transaction that seems okay at first glance. However, fraud scoring parses the transaction more closely, generating a score of 75 based on factors that aren’t immediately obvious. It exposes fraud that you might not have otherwise noticed.
Here’s a typical fraud-scoring model that demonstrates how scores might be broken out:
Benefits of Using Fraud Scoring
The most obvious advantage of using fraud scoring is simple: it saves time and money. But there are other benefits to consider.
In the initial set-up process, you’ll usually decide how much risk you’re willing to accept. You set the thresholds, so you get to determine the benchmarks. When set properly, your fraud scoring tool will offer you:
What Are the Challenges of Fraud Scoring?
Fraud scoring is a useful tool, but it shouldn’t be the deciding factor in every case. Remember that no technology is foolproof, and false positives are still possible. You need to calculate what each score ends up costing, and make sure you’re saving more than you’re spending.
Here are some other fraud scoring challenges to consider:
Bad Data
"Rule Creep"
Limited Decisioning
The Human Factor
Ongoing Upkeep
Importance of Understanding & Testing Your Fraud Scoring Technology
As you can see, there are a lot of challenges and limitations to fraud scoring technology. That’s why it’s crucial that you understand your system and continuously test its effectiveness.
Here are some tips for understanding and testing your fraud scoring technology:
You can stay one step ahead of fraudsters and protect your business from financial losses. The key is understanding and continuously testing your fraud scoring technology.
Remember to stay proactive. Keep expanding your knowledge on the latest trends and techniques in fraud detection, and don't hesitate to make necessary adjustments to your system as needed.
Fraud Scoring: Crucial, but Not Enough on its Own
Fraud scoring is one of the most powerful tools you can have in your arsenal. As effective as it is, however, its use is limited to preventing fraudulent orders. That won’t help with friendly fraud.
Friendly fraud is post-transactional. There’s no reliable way to stop it from happening before the sale. And, even if you could, friendly fraud usually comes from seemingly-legitimate customers. Fraud scoring would have no effect.
For effective overall fraud and chargeback prevention, you need a multi-tiered strategy that combats fraud both before and after the transaction. Chargebacks911® offers transparent, end-to-end fraud and chargeback management, going beyond prevention to revenue recovery and future growth.
Whatever you need to combat fraud, we can help. Contact us today for a free demo.
FAQs
How is a fraud score calculated?
Fraud scores are calculated using various data points, including transaction history, customer behavior, device information, and geolocation. This score is generated through complex algorithms that weigh the risk factors, allowing businesses to make informed decisions about whether to approve or decline a transaction.
How to get fraud score to 0?
Achieving a fraud score of 0 is virtually impossible, as it requires eliminating all potential risk factors associated with a transaction. Instead, focus on implementing robust verification processes, real-time monitoring, and a layered approach to fraud detection that minimizes risk while accepting some degree of uncertainty.
Why does my IP have a high fraud score?
A high fraud score associated with your IP may be due to several factors, including previous transactions linked to fraud or unusual activity patterns originating from your location. Additionally, if your IP address is shared with other users, actions taken by those users could also contribute to an elevated risk assessment.
What is the fraud risk scoring model?
The fraud risk scoring model is a systematic approach that assigns a risk score to transactions based on various data inputs, such as user behavior and historical patterns, to assess their likelihood of being fraudulent. This model helps businesses make informed decisions by identifying transactions that may require further scrutiny or intervention before approval.
How do you evaluate fraud risk?
To evaluate fraud risk, businesses employ a comprehensive analysis of multiple data points, including transaction history, user behavior, and device information, to determine the likelihood of fraud occurring. Implementing advanced machine learning algorithms enhances this evaluation by continuously learning from new data to refine risk assessment processes.
