Rick Sunzeri
When navigating today's digital marketplace, online retailers face escalating threats from sophisticated cybercriminals. This makes effective fraud prevention strategies more crucial than ever before to protect your business's bottom line and maintain customer trust. The good news? You have a lot of options. The not-so-good news? The right option for your unique business needs isn't always obvious — and it can vary wildly.
As a result, merchants are left questioning when they should rely on technology-based machine learning and when a human-focused manual review is more appropriate. There's also the question of what else is available.
Let's look at the options, their advantages and their potential flaws.
Using Machine Learning Technology as a Fraud Protection Solution
The machine learning approach to fraud protection taps into computer algorithms to analyze current and historical data, fraud statistics across industries, and transactional information. Many e-commerce retailers are turning to the power of technology and artificial intelligence (AI) to evaluate a transaction's fraud risk and flag potentially fraudulent transactions.
How Machine Learning Can Improve Fraud Protection
Machine learning is a powerful tool for detecting fraud because of its ability to "learn" as new data is processed and incorporate those learnings into decision-making algorithms.
We know that fraudsters are continuously evolving their strategies for perpetrating fraud. AI can pick up on those new strategies and subtleties quickly and integrate them, improving its risk-scoring algorithms.
Machine learning solutions offer a number of other advantages:
- Analyze a wide array of data, such as information about a merchant's unique segments and geographic markets, fraud patterns specific to those segments and markets, and unique customer and credit card data.
- Minimize losses due to fraudulent transactions and chargebacks. LexisNexis reports that every $1 of fraud loss translates to $3 lost in chargebacks, fees and merchandise replacement.
- Evaluate and process higher volumes of transactions much more quickly than human analysts can.
The rapid, real-time analysis inherent to machine learning algorithms lends itself to quickly identifying obvious fraud and flagging potential fraud. This is incredibly useful when processing real-time transactions that require an instant assessment of potential fraud. Not only does it aid in chargeback prevention, but it also allows businesses to address potential issues before they escalate, thereby protecting revenue and customer relationships.
Drawbacks of Relying Exclusively on AI for Fraud Prevention
Despite the benefits, machine learning as your only fraud prevention tactic has its flaws. For example, it may not be able to discern suspected fraud from a customer who is doing all their holiday shopping online at one time. It also may miss special circumstances, such as a customer making purchases while traveling overseas.
Both of those situations may look like fraud but clearly aren't. Relying solely on machine learning would result in false declines (i.e., lower approval rates and reduced sales), which often results in long-term loss of customer loyalty.
Machine learning can also hamper fraud detection during the period between when fraudsters develop a new tactic and the AI learns how to recognize it, leading to windows of opportunity for fraud to occur.
Using Manual Review as a Fraud Protection Solution
In contrast, manual reviews rely exclusively on in-house or outsourced teams of trained analysts to identify and prevent fraud. Again, there are pros and cons with this tactic.
How Human Reviews Can Improve Fraud Protection
Let's take the situations described in the last section: making purchases while traveling and making several high-value purchases in a short time span. The advantage of a manual review of these transactions is the ability for trained staff to consider whether other purchases were made recently that indicate the customer is out of town. Or looking at historical patterns to see that the customer makes these types of purchases as a yearly ritual to take advantage of sales. A manual review allows for assessment and inquiry that reduces the risk of both false declines and fraudulent transactions. Specifically, manual review involves:
- Using the problem-solving knowledge and unique skills of the staff to develop and apply new rules that guide transactional decisions.
- Letting staff identify fraud patterns specific to a merchant and implement personalized fraud screening at the client level, giving staff the opportunity to flag more suspicious transactions.
- Giving reviewers the opportunity to immediately contact clients with flagged transactions.
- Having experienced staff on hand who can detect subtle fraud patterns as they develop.
While automation is powerful, human analysts bring critical thinking and contextual understanding to fraud detection. Their ability to assess nuanced situations ensures that legitimate transactions aren't mistakenly declined, which is vital for maintaining customer satisfaction and safeguarding the business's financial health.
Drawbacks of Relying Exclusively on Manual Reviews
So now let's talk about the disadvantages of manual review as a standalone fraud prevention tactic. Having a dedicated team for catching fraud isn't necessarily a good fit for merchants for several reasons:
- Business owners have to hire either in-house or outsourced staff to screen every transaction, which can be expensive.
- Having the right staffing level at all times is challenging. Merchants must ensure they have enough staff on hand during sales spikes, while still being able to reduce staffing levels when sales slow.
- It can be more time-consuming and difficult to scale a manual review solution as a business grows and the number of transactions increases dramatically.
- Time-consuming reviews can delay order processing, frustrating customers.
- The effectiveness of manual reviews is only as good as the knowledge and expertise of the staff. That means extra training to ensure staff is knowledgeable about the latest cyberattacks and creating incentives to retain quality staff.
What's the Best Fraud Protection Solution?
Both machine learning and manual review have their benefits, but neither is the ideal solution for fraud protection. So, what's the best option for online businesses looking to protect themselves from fraud?
Consider a Hybrid Fraud Protection Solution
Businesses need a sophisticated fraud prevention solution that combines the benefits of machine learning algorithms and the discernment of experienced staff who are experts in transaction investigation. In other words, businesses need a hybrid model that leverages the best of both. This combination enhances fraud prevention by quickly flagging suspicious activities and allowing for expert evaluation, reducing false positives and improving chargeback prevention efforts.
How ClearSale's Hybrid Fraud Prevention Solution Is Different
At ClearSale, our hybrid fraud prevention solution involves four essential components that results in the highest approval rates and lowest chargeback rates in the industry.
Detect Obvious Fraud Using AI
Our solution starts with an AI-enabled algorithm that analyzes transactions against our massive fraud database. Because we've been fighting fraud since the very first online purchase was made, our global transaction database is unmatched. Using machine learning, we're able to quickly detect fraud with certainty, while suspicious transactions (about 2%) are flagged for manual review.
Increase Approval Rates Through Manual Review
Transactions identified as potentially fraudulent are analyzed by our fraud analysts who possess the experience that comes from decades of fighting fraud around the world. The goal is to clear as many transactions for approval as possible, as quickly as possible, without compromising on chargeback prevention. In some cases, our analysis may mean contacting the customer to confirm their purchase. This "white glove" level of service is something our clients value as part of their efforts to protect their customers from being victims of fraud.
Improve Fraud Detection Accuracy Through Data Sharing
Once our fraud analysts complete their assessment, they feed the insights into our algorithm so it can "learn" about new fraud patterns and trends. This further improves the accuracy of our solution and increases the speed at which we can detect fraud.
One Speed Does Not Fit All
We understand that businesses have a variety of unique needs when it comes to fraud detection and prevention. For example, an online business that sells digital products needs fraud detection at a faster speed than a business that offers online sales and 24-hour delivery or pickup.
That's why we've diversified our products to account for the needs of businesses across the fraud detection spectrum. You can find out what decision speed is right for your business by exploring our ClearSale Decision Speed Tool. You're also welcome to reach out at any time to have a custom assessment from one of our experts.
