Why Choose a Rules-Based Fraud Prevention Solution

Financial institutions have reported a spike in attempted credit card fraud since the pandemic shut down the global economy.

The Federal Trade Commission registered 2.2 million fraud cases involving U.S. consumers in 2020. They lost more than $3.3 billion due to fraud in this period.

However, it's not only consumers who are falling victim to fraud. According to a recent PWC survey, almost 50% of companies around the world have experienced fraud in the past two years. The estimated cost amounted to $42 billion!

Fraud rates are still at an all-time high. Ignoring fraud prevention is a risk that companies can't afford. So, what options are available?

Rules-Based Fraud Management Solution

Rules are a proven method of providing protection from fraud and mitigating risk. A rule can consist of conditions that, when satisfied, flag a transaction as fraudulent.

Fraud detection systems that use rules analyze a set of unusual factors— including timestamps, account numbers, transaction amounts, and locations —to detect patterns of fraudulent behavior.

Fraud Prevention Solution

When these elements are identified, the anti-fraud platform labels them as possibly fraudulent.  

Rules-based fraud detection solutions are easy to understand because they're just a set of conditions, which significantly speeds up the development cycle.  

They are also much faster to implement, which is especially important when overseeing a large number of transactions in real-time.

The Benefits of a Rules-Based Fraud Prevention Solution

There are three key reasons why businesses choose to protect themselves using a rules-based anti-fraud technology.

Efficiency

Rules-based fraud detection platforms are both easy to set up and extremely fast. Solutions like Hyperon can scan through all the transactions in real-time and flag potential fraud.

Simplicity

Rules-based solutions are easy to interpret. The transparency of these systems is perfect for diagnosing and identifying issues. For example,  uncovering why a particular rule produced false positives.  

In this case, a team member can quickly fix the issue with no business disruption.

Instant Response to Threats

Rules-based fraud detection solutions quickly insert rules once new fraud trends emerge.

For instance, if a company traces an attack to an exact location, then they can immediately blacklist the location to prevent transactions from that area.

Rules-Based Fraud Protection in Action

Let's go over some potentially fraudulent behavior that a rules-based fraud management solution can flag with ease.

Physical and Online Location

When transactions take place far from a customer's residence. For example, a charge from a convenience store in another state from the card’s billing address at midnight.

Or if a user with the same IP address opens several accounts and makes large payments using newly issued credit cards.

Frequency

If a typically inactive account all of a sudden starts buzzing with transactions. Another case might be if a customer receives large payments from several newly created accounts.

Suspicious Use

When a customer seems to be using a card to make payments within an extremely brief period of time. It's apparent that these fast transactions are impossible for a customer who's physically shopping around with their credit card.

The Issue with Rules-Based Fraud Detection Systems

There is one important thing to keep in mind when implementing rules-based systems.

A rules-based fraud protection system is only as good as its rules. Poorly defined rules result in weaker fraud detection and false positives.

Therefore, organizations need to keep track of emerging risks and make updates accordingly.

Rules-Based Fraud Prevention: Common Misconception

One of the critiques leveled against rules-based prevention platforms is that they get too complicated the more rules you add. However, Hyperon's domain configuration feature is designed to help users easily navigate countless rules to find the ones they need to modify. Fraud analysts can drill down and target the right fraudulent behavior.

So, you can make your anti-fraud platform as complex as you need it to be.

Fraud Protection with Machine Learning

Machine learning solutions are more advanced than their rules-based counterparts.

The ability of machine learning to identify hidden links between variables is unrivaled. It's able to detect sophisticated correlations that would be virtually impossible for a person to notice.

However, a great deal of data is required to spot these intricate patterns. This is especially true for fraud detection because on average only 1 in 1,000 transactions is fraudulent. Without going over a large number of fraud cases, an algorithm can't learn to spot fraudulent behavior.

However, this means lengthy development cycles, slower deployment, and costly maintenance.

The Black Box Problem

Organizations need to know why a particular transaction was flagged. However, complex AI systems don't provide clarity or transparency. In other words, it's difficult for humans to understand why AI labeled an event as fraudulent.

Why Choose a Rules-Based Fraud Prevention Solution

The main problem with machine learning systems is that they rely on data that's around 90 days old. Obviously, this makes it difficult to spot the latest threats. An organization might be aware of a new kind of fraud, but artificial intelligence hasn't yet come across this behavior.

Therefore, machine learning isn't well suited for situations that demand immediate reactions.

On the other hand, when fraud managers learn about new fraudulent incidents, a rules-based management platform allows businesses to easily add the necessary protections. In these cases, rules can block a new type of fraud before it hurts the business.

Why Our Customers Use Hyperon

A single poorly constructed rule has the ability to allow all transactions, including all the fraudulent ones. Similarly, a rule that blocks all transactions is equally detrimental to a business.

That's why every anti-fraud management solution should allow fraud analysts to safely experiment without having to risk affecting the organization.

Hyperon has a built-in tester that allows fraud analysts to see the exact effects of rules before they go live. This way businesses can test out different rules and find out which combination is best for what they need to accomplish.

The Proven Fraud Detection Solution

Hyperon is an advanced fraud detection solution that empowers organizations to respond to immediate threats. As soon as a new threat has been discovered, your fraud managers have the necessary tools to react.

Ready to see how Hyperon can protect your business? Get in touch with our team today.