A guide to fraud monitoring

In this article, we explain how fraud monitoring works, why it’s so important for online merchants, and how to choose the right system for your needs. 

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October 25, 2023
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A guide to fraud monitoring

We often talk about the importance of fraud detection and monitoring, and with good reason: ecommerce losses to online payment fraud are expected to total $48bn in 2023, staggering growth on the $17.5bn lost in 2020, according to figures from Statista.

In order to avoid becoming a victim, you need to implement a fraud monitoring system. These systems continually analyze the vast amounts of data generated by online commercial activity, from logins to payments, to look for anomalies. 

In this article, we explain how fraud monitoring works, why it’s so important for online merchants, and how to choose the right system for your needs. 

What is fraud monitoring?

Fraud monitoring systems continually observe and analyze various events, transactions, and behaviors in real-time to detect and prevent online fraud. Mostly, this activity happens in the background, but when the system detects something unusual, it can block the event and route it for manual review. You can customize your fraud monitoring system to your requirements and your business’s risk appetite. 

Fraud monitoring is essential for online merchants, as it can help you to avoid serious consequences associated with falling victim to fraud, including financial losses, reputational damage, and legal repercussions.

How does fraud monitoring work?

Fraud monitoring encompasses several different stages:

  • Real-time data collection and analysis - fraud monitoring begins with real-time analysis of relevant data and information, including transactions, customer profiles, login attempts, network traffic, and more. This monitoring can be broken down into two types: continuous transaction monitoring and continuous session monitoring. Operating in real-time or near-real-time allows for immediate detection and prevention of suspicious activities. When predefined thresholds or patterns that could imply fraud are identified, automated systems trigger alerts
  • Anomaly detection - advanced algorithms and machine learning models are used to analyze all this data. When combined with your customized rules, these algorithms can detect patterns and anomalies that could indicate fraudulent behavior. For example, they might identify unusual a high frequency of identical transactions, multiple failed login attempts, or inconsistencies in personal customer information
  • Alerts and investigations - if potential fraud is detected, the system generates an alert and routes the activity or event for further investigation. Fraud analysts or automated systems can then review these alerts to determine whether they are indeed fraudulent or false positives
  • Prevention - if fraud is confirmed, you can take appropriate action to prevent further damage. This might involve blocking a transaction, suspending an account, or, in the most serious cases, notifying law enforcement or regulatory authorities. Additionally, the data and insights gathered from fraud monitoring activity help the fraud monitoring system learn to more accurately prevent fraudulent activities in the future

Learn more: Fraud rules engines

Why is fraud monitoring important?

Fraud monitoring isn’t just about protecting your business and your customers. It’s a collaborative effort by all online merchants and regulatory authorities to guarantee the integrity and security of the entire global payments network. 

Without fraud monitoring, consumer trust in online transactions would break down, and businesses would be too cautious to engage in the domestic and international trade that helps communities and countries prosper. 

Benefits of fraud monitoring for business

The key benefits of fraud monitoring for online businesses are:

  • Protection from financial loss - it helps protect both you and your customers from theft perpetrated by cybercriminals by enabling early detection and prevention of unauthorized transactions or account takeovers
  • Reputation management - fraud can severely damage the reputation of your business with customers, business partners, and regulators. Proactive detection and response insulates you from reputational harm by demonstrating that you take security and customer protection seriously
  • Compliance - many industries and regions have regulations that require you to implement fraud monitoring as part of your security and compliance measures, including Anti Money Laundering (AML), Know Your Customer (KYC), and Customer Due Diligence (CDD). Non-compliance with these regulations can lead to fines and legal consequences
  • Customer experience - as well as improving customer trust, implementing fraud monitoring can improve customer experience by routing only higher-risk customers or transactions for further authentication. Meanwhile, lower-risk customers can enjoy a more frictionless purchasing experience, which limits frustration and delays
  • Cost savings - detecting fraud early can reduce the overall cost of fraud prevention. Not only does it help you to avoid the immediate costs of financial loss, but also the cost of recovering and securing your systems and reputation in the event of a major breach
  • Adaptation to evolving threats - fraudsters constantly adapt their tactics to keep up with changing payments technology. Continuous fraud monitoring learns from across the entire payment network to stay ahead of new fraud schemes and vulnerabilities 

Machine learning in online fraud monitoring 

Machine learning is at the heart of successful fraud monitoring. A type of artificial intelligence (AI), machine learning has the ability to continually analyze the masses of data generated by online transactions and customer behavior. 

Based on this analysis, it learns what typical behavior and activity looks like and then detects when events occur that deviate from those norms. As fraud threats are evolving all the time, this learning is a perpetual process that keeps you safe by identifying new and emerging risks.

Machine learning is most effective when used in combination with flexible, customized rules. You can define these rules depending on your risk appetite and the specific threats you face. For example, you could set your monitoring system to trigger an alert if a transaction occurs that surpasses a specific financial threshold. 

How to choose and set up a Fraud Monitoring system

Because the consequences of an attack can be so severe, it’s worth spending some time comparing different fraud monitoring systems to find the most suitable one for your needs. 

The key features you should be looking for are:

  • Real-time monitoring - fraud monitoring has to happen in real or near real-time in order to be effective. Your system should monitor both financial activity and customer behavior continually so that it can implement automated defensive actions immediately if it spots an anomaly. This also allows you to act quickly to secure your systems if required  
  • Machine learning - as discussed above, machine learning is integral to fraud monitoring. It’s the only effective way to assess huge volumes of data and to learn about emerging fraud threats 
  • Custom rules - custom rules allow you to tailor your fraud monitoring activities to your needs. For example, you can ensure your system doesn’t become overzealous in blocking legitimate transactions, which could be frustrating and damage customer relationships 
  • Fraud scoring - you can give specific customers and actions risk scores depending on the level of threat they pose to your business. These can be useful for both machines and human agents in deciding how to act in certain scenarios 
  • Alerts - alerts are your system’s way of letting you know that something has been blocked or that it needs manual review based on you fraud scores and rules  
  • Data visualization - part of your reporting function, visualization transforms the mountains of data you receive into a digestible, visual format, which makes it much easier to draw out meaningful insights that can be shared across your organization  

How Checkout.com helps with fraud monitoring

Checkout.com’s Fraud Detection Pro has all the tools you need to keep your business and your customers safe, while minimizing false positives. 

Using a hybrid of rules and machine learning - that’s been trained on billions of transactions from across our entire network - our system routes only the riskiest transactions for further authentication but minimizes friction for your legitimate customers. 

What’s more, Fraud Detection Pro is highly flexible, allowing you to create advanced velocity and custom that you can test before pushing live.

Find out more about Fraud Detection with Checkout.com or get in touch with our experts.

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October 25, 2023 10:50
October 25, 2023 10:50