As fraud grows in both volume and sophistication, previous-version security point solutions quickly become obsolete. Advanced fraud techniques are leaving financial institutions, e-commerce companies, and even governments struggling to keep up.

Fortunately, real-time fraud detection tools can help enterprises repel threats across a range of intrusion points and types. Real-time fraud detection can stop a threat within moments, preventing wide-scale damage and loss.

What is real-time fraud detection?

Real-time fraud detection is a strategy to monitor, isolate, and prevent a suspected threat to an organization within moments of detected suspicious activity. 

Speed is essential to protect an organization’s assets from misuse and compromise. The faster an organization finds a fraud risk, the faster they can address it, and the safer their data, assets, and reputation will be.

How is machine learning used in fraud prevention and detection?

In fraud prevention and detection, machine learning algorithms lean on historical datasets — both fraud-related and legitimate. For example, legitimate transaction data gives the algorithm a baseline from which it can spot fraud patterns and classify new data that enters the system.

Users can then put rules in place to spot anomalies or suspicious behavior and use automation to address that behavior (e.g., stopping a transaction). As the system consumes more data, the machine learning models become smarter, and the real-time fraud detection platform becomes optimized.

Benefits of real-time fraud detection

Real-time fraud detection holds multiple benefits, and not just for banking, fintech, or financial services providers. The ability to halt potential fraud in its tracks within a few milliseconds saves customers, retailers, shippers, and others from losses. 

As a foundational technique in real-time fraud detection, device intelligence identifies users through device fingerprinting. Additional methods like VPN detection, virtual machine detection, incognito mode detection, and IP geolocation deliver a strong defense against unauthorized access.

Reduced revenue losses

Cumulative merchant losses due to online payment fraud between 2023 and 2027 will exceed $343 billion globally, according to Juniper Research. Stopping a fraudulent payment before or while it is happening is the first line of defense in preventing fraud losses.

Because real-time fraud detection stops malicious activity before it can occur, it protects organizations from revenue losses. For example, if the system recognizes suspicious activity for a new account holder taking out a loan or credit card, real-time tools can prevent the firm from disbursing and then losing the funds. 

Increased customer trust and loyalty

Real-time fraud detection — even when it’s working in the background — can earn trust and loyalty from customers. After all, it’s not just the retailer or service provider that fraudsters are after — customers also benefit from stopgaps for protection. This peace of mind is part of the overall digital user and customer experience.

Enhanced security for online transactions

While terminating valid transactions can cause friction in rapid e-commerce transactions, consumers expect a certain level of security. These security measures deliver a level of user trust with financial service providers and websites or apps where they make purchases.

Rapid response to emerging threats

By continuously monitoring transactions and behaviors, a real-time fraud detection platform can help IT and security professionals better understand and respond quickly to emerging or evolving threats.

 It takes only a single point of intrusion to serve as the vector that leads to a data breach. As the threat landscape increases in both size and complexity, a fraud detection platform can provide support when human-controlled monitoring cannot keep up.

The use-cases of real-time fraud detection

There are several use cases for real-time fraud detection. Some of these are standalone situations, but some can combine. For example, a fraudster engaged in an account takeover of a victim’s airline frequent flyer mile account will most likely later commit payment fraud by stealing the credit card details on file with the airline and making a purchase.  

Because of the speed demanded by consumers when making an online purchase or app-based transaction, anything less than a real-time confirmation of a transaction would have customers abandoning a shopping cart or exiting an app. 

With abbreviated transaction time windows, retailers and banks need a system in place to confirm identities, accounts, and intentions within seconds. As such, real-time fraud detection is the best solution to protect both parties. 

Payment fraud

Identity theft, stolen account credentials, access to victims’ accounts, and fraudulent payments are the key behaviors that a real-time fraud detection platform aims to prevent. 

To determine whether payment fraud is about to occur, a real-time payment system would access the bank or retailer’s accounts and corresponding customer credentials, and immediately determine when there isn’t a match, or when there might be suspicious behavior. 

For example, a credit card used for an unusually large transaction in a country thousands of miles away from where every other transaction has occurred will signal an anomaly to the system and generate an alert for the true account holder to either authorize or decline the transaction.

Account takeover

Gaining access to a bank account isn’t the only type of fraudulent account takeover. Sophisticated criminals realize the value of taking over other types of personal accounts that might also hold value. Accounts for things like airline frequent flier miles, government benefits, and social media (that may have a credit card on file for online shopping) are all at risk. 

Real-time fraud detection helps here, especially when particular transactions are expected to occur. For example, social security and other benefits are typically dispersed on the first of each month. A bank’s fraud detection system will be on guard to spot an unusual number of accounts changing their passwords just before midnight on the night before the benefits are set to hit recipients’ accounts. 

This scenario occurred last year with California's CalWorks public assistance program, where fraudsters were “skimming” an average of $10 million per month from victims’ EBT cards at midnight before the first day of a new month. 

SMS fraud

Short Message Service (SMS) fraud involves sending text messages to victims in order to gain unauthorized access to the victim’s accounts. A phishing technique to exploit users and gain their trust, SMS fraud has grown in popularity thanks to an increase in SMS marketing. 

Real-time fraud detection is perhaps most needed with SMS messaging because of the speed at which people receive and respond to texts. Real-time fraud detection can spot larger than normal or suspicious volumes of SMS messages because it can identify the patterns of traffic coming to a website or app via SMS. The system would have been trained on historical data to understand what the organization considers an acceptable volume of SMS messages, along with other data like location, and test that against any incoming, suspicious activity. 

Reducing chargebacks

Customers may file a chargeback or request for a refund for several reasons, such as unauthorized charges, billing errors, or dissatisfaction with goods or services. 

However, chargebacks have become a problem impacting both banks and retailers alike and cost merchants over $100 billion in 2023. A real-time fraud detection platform helps in the fight against suspicious chargebacks and other credit card fraud.

Real-time fraud detection could be used here to quickly access shopping or transaction history for the customer, to determine whether the customer has requested multiple chargebacks and currently poses a risk for the bank or retailer. 

E-commerce fraud

As e-commerce frauds increase in complexity — and even creativity — real-time fraud detection solutions can help both banks and retailers prevent loss. 

For example, the system might flag a credit card used for multiple, rapid transactions across several websites or apps for disparate products. Combined with different shipping addresses all in far-off, never-used-before locations, this would trigger an alert for suspicious activity. 

The system would halt transactions, keeping the bank from having to reimburse a defrauded cardholder and the retailer from shipping products that were not paid for properly.

Promo abuse

Aside from access to bank accounts, fraudsters have also sought to steal promotions, coupons, rewards, and other benefits associated with a retailer or service provider’s app. In fact, a study by TransUnion found that promotion abuse is the number one type of retail fraud.

Cybercriminals are well aware that promotions nowadays are often highly personalized and tied to an individual customer. These customers’ accounts may also include bank account and credit card information. 

Fraud detection tools can spot anomalies in promo or reward redemptions, which can uncover and stop additional malicious behavior. This needs to be in real-time because promotions or rewards are typically redeemed as part of a transaction. Preventing a suspicious redemption also serves as a means to stop a suspicious transaction right before it occurs.

New account fraud

Digital customer onboarding and new account openings, especially with fintechs and new digital banks, are attractive access points for criminal behavior. Fraudsters simply open new accounts, take out personal loans and credit cards, and then shut the accounts down with no intent of paying the loans or lines of credit back. 

However, through robust authentication methods, real-time fraud detection tools can stop suspicious behaviors at the moment of new account creation. For example, by accessing multiple databases at once, all in real-time, a bank’s anti-fraud platform might notice that the name, photo, photo of an ID card, and address of a new customer don’t match.

How to implement a real-time fraud detection system for online transactions

To implement an effective, tactical approach to stopping fraud in its tracks, there are a few considerations organizations should make during the process.

First, your organization needs the resources in place to access, organize, process, and analyze large volumes of data rapidly and at scale. The data might arrive in the system from multiple sources in real time, and the system must be able to unify and standardize transaction details and customer identities, along with IP address, location, device information, and other data.

With the volume and speed of the session or transaction data entering the system, your business must also be able to develop algorithms that can identify anomalies or suspicious behaviors. Algorithms and models must be built and trained using historical data (both typical and fraudulent) before they can be applied to the new data entering the system.

Companies with strong security systems already in place are most likely familiar with network monitoring, security event monitoring, application security, and other intrusion detection measures. Real-time fraud detection is similar in that monitoring is in place but the organization must decide on the right mix of actions to take should suspicious behaviors be uncovered, and then assess whether those actions successfully stopped fraud.

With all of these considerations in place, a bank or retailer can consider implementing a real-time fraud detection system with confidence. When selecting a fraud prevention solution, organizations can weigh the ROI by considering the potential financial losses and reputational damages of not implementing the program.

Fingerprint’s efficient, real-time device intelligence helps companies when they are considering implementing real-time fraud detection. Fingerprint helps in evaluating large volumes of data, especially as it relates to determining the true intentions of every user, even when they are anonymous. 

Because detecting fraud is nothing new for banks and retailers, Fingerprint’s Smart Signals helps them add to the signals they’re already collecting for more informed decisions in the ever-evolving complex threat landscape. 

Fingerprint delivers 99.5% accuracy and clarity into every user touchpoint, and it integrates seamlessly with cloud providers.

Guard your transactions against fraud with Fingerprint

Standalone, previous-version solutions are powerless to stop today’s increasingly advanced cyberattacks. As banking and e-commerce transactions continue across millions of mobile devices, criminals also have millions of entry points through which to carry out fraudulent activities.

Fingerprint is a key part of a comprehensive real-time fraud detection model, offering highly accurate visitor identification instantly. With Fingerprint, you can guard both your business and your customers from fraudulent transactions — without adding unnecessary friction to the user experience.

Want to learn more about how Fingerprint can help your business strengthen its defense across the entire threat landscape? Contact our team today.