There were over two million instances of fraud involving Americans occurred in 2020, which resulted in more than $3.3 billion in losses. Although, it’s not only consumers who are being defrauded. According to the latest reports, nearly 50% of businesses around the globe have been victims of fraud in the last couple of years. The estimated cost of the fraud? $42 billion!
Fraud Prevention Solutions Powered By Rules
Rules-based software solutions have a proven track record of protecting companies from fraud. Rules are made up of conditional statements that, when verified, flag fraudulent activity.
A fraud prevention software built on top of a business rules engine relies on rules to review a set of peculiar factors to spot patterns of fraudulent activity. For instance, a quick succession of transactions from different locations would alert the business to potential fraud being committed in real-time.
A fraud prevention solution that runs on rules is easy to use, which significantly accelerates the development cycle.
A business rules engine can easily be configured into a fraud prevention tool that can analyze extremely large numbers of transactions as they happen.
The Advantages of Fraud Prevention Solutions Based on Rules
There are a few important reasons why organizations of all sizes use rules-based fraud prevention software to secure their operations.
Great Performance
Fraud detection solutions that use rules are both very fast and very simple to deploy. They’re able to analyze countless transactions in real-time and identify suspicious activity.
Easy to Use
Anti-fraud software solutions are transparent and easy to understand, which makes them perfect for troubleshooting issues. For instance, discovering why a specific rule created false positives.
In this instance, a fraud specialist can easily fix the problem without disrupting business operations.
Real-Time Response
Staff can insert new rules into the fraud detection software as novel fraudulent activity has been identified.
For example, if an organization traces an attack to an exact location, it can instantly shut down transactions from that region.
How Do Fraud Prevention Solutions Prevent Fraud
The following are common examples of fraudulent behavior which rules-based fraud prevention solutions can immediately spot.
Suspicious Locations and Timestamps
Transactions that occur far from a client’s registered residence. For instance, a charge from a convenience store in another state or country late at night.
Frequent Transactions
Frequent transactions might indicate potentially fraudulent behavior. For example, if a client receives large payments from many newly opened accounts in a short span of time.
Suspicious Activity
This is tied to the previous example of suspicious activity, and it describes cases when a client is using their card to make numerous purchases in a very short period.
It’s obvious that these almost instant purchases couldn’t be made by a client who’s physically shopping around.
A Fraud Prevention Platform Running on Rules
Many companies are considering using machine learning technology to fight against fraud. However, for most businesses implementing machine learning doesn’t make any sense.
The biggest challenge with machine learning platforms is that they use data that’s 90 days old on average. As a result, it’s very difficult for these solutions to detect the newest threats.
Conversely, as soon as a business hears about new fraudulent activity, a rules-based prevention solution enables organizations to easily add the necessary safeguards.
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