Cyber Fraud Fusion: Improving Security & Reducing ATO

Is account takeover (ATO) fraud hurting your bottom line? This form of cybercrime resulted in nearly $13 billion in losses in 2023. ATO attacks and other fraudulent activity pose a growing threat to any company doing business online. However, companies trying to protect themselves face an uphill battle.

Highly qualified security experts are in short supply, and 59% of cybersecurity teams are understaffed. What’s more, fraud departments often lack the technology and data they need to do their jobs effectively. 

With a cyber-fraud fusion approach, businesses combine teams and create a security center that brings together all security data. This empowers multiple departments to combat fraud and build a unified front against cyberattacks.

Gartner is tracking the increasing popularity of cyber-fraud fusion and predicts that the number of large companies leveraging this strategy will increase from today’s less than one in 20 to reach one in five by 2028.

Read on to learn why cyber fraud fusion is gaining traction and discover what taking a collaborative and interconnected approach to threat mitigation can do for your business. 

What is Cyber Fraud Fusion?

Cyber fraud fusion is a holistic security methodology that involves combining diverse data sources, advanced analytics, and multiple teams to more effectively detect and prevent fraud. By fusing fraud teams with software solutions and cybersecurity departments, organizations can build a stronger security posture that enables a proactive, instead of reactive, approach to fraud. At the heart of this approach are “fusion centers,” where data from various domains is brought together to create a comprehensive view of potential threats. This combined sourcing of data is especially valuable for mitigating advanced cyber fraud, such as account takeover attacks. 

What are Account Takeover (ATO) Attacks?

Account takeover attacks are a form of identity theft where cybercriminals gain unauthorized access to user accounts, often for financial gain or to steal sensitive information. These attacks can be relatively simple, such as buying stolen credentials on the dark web and using them to log in, or more complex, such as using OTP bots to intercept SMS messages and break two-factor authentication. These attacks succeed more often than they should because they take advantage of certain weaknesses in fraud departments, such as a lack of real-time analysis, limited behavior tracking, or a generally reactive approach to security. The epidemic of password reuse has also made acquiring compromised credentials relatively easy and affordable for fraudsters. Plus, with the power of advanced generative AI and deepfake technology, attackers are developing increasingly sophisticated attacks that legacy approaches struggle to address. 

How Does Cyber Fraud Fusion Address ATO Attacks?

Cyber fraud fusion helps combats ATO attacks by taking a multi-layered approach to threats. This involves comprehensive data analysis, machine learning, and cross-channel monitoring to identify suspicious activities and prevent unauthorized access. Here’s how it works:  

• Real-time data analysis: Cyber fraud fusion centers process vast amounts of user data instantaneously to detect anomalies indicative of ATO attempts. This includes monitoring login attempts, transaction patterns, IP addresses, and device information. Anomaly detection enables the identification and prevention of ATO attempts in real time. 
• Cross-channel monitoring: ATO attacks often mimic legitimate user behavior, making them difficult to detect. To counter this, cyber fraud fusion centers track user activity across multiple channels and devices. These teams look at web platforms, mobile apps, and customer service interactions to build a complete picture of typical user behavior. Deviations from this pattern suggest a potential ATO attack, enabling teams to take preemptive measures. 
• Machine learning algorithms: Cyber fraud fusion also employs adaptive AI models to recognize evolving ATO techniques and improve detection accuracy over time. These algorithms analyze patterns and events, such as transactions and login attempts, to refine their detection criteria. This leads to increased accuracy over time as the system “learns” and improves itself. 
• Behavioral analysis: By combining data from multiple sources, teams are empowered to monitor behavior on a deeper level. This sophisticated approach examines user patterns and habits to detect anomalies that may indicate fraud. Factors like transaction history, geographical location, device information, and time of day are considered to establish a baseline of normal behavior. Deviations from this baseline, such as unusual transaction frequency or login patterns, are flagged for further investigation.
• Collaborative intelligence sharing: The term “fusion” is a reference to the collaborative exchange of ATO threat information between security and fraud prevention teams to enhance overall protection. This collective knowledge enhances the overall protective measures across the network. 
• Adaptive authentication measures: Finally, cyber fraud fusion also combats ATOs by supporting adaptive authentication measures. These are dynamic security protocols based on real-time risk assessments that prevent unauthorized account access. 

Top 7 Benefits of Cyber Fraud Fusion in Improving Overall Protection

The features above demonstrate how cyber fraud fusion combats ATO attacks, but this approach is not exclusive to one specific type of cyber threat. Instead, cyber fraud fusion centers can increase an organization’s overall security and thwart all kinds of fraud. A cyber fraud fusion center provides: 

1. Comprehensive Threat Visibility: By integrating data from diverse sources like network traffic, endpoint activity, behavioral analytics, and even third-party intelligence feeds, organizations can achieve a 360-degree view of their security posture. This means you can identify subtle vulnerabilities across various channels and unlock the power of advanced visualization tools to map out complex attack vectors. 
2. Rapid Threat Detection and Response: Cyber fraud fusion significantly reduces the time between attack initiation and mitigation by using real-time analytics and automated response mechanisms. Automation tools can automatically initiate countermeasures, such as blocking suspicious IP addresses or isolating compromised accounts, stopping attackers in their tracks.  
3. Reduced False Positives: According to JP Morgan, actual fraud losses represent 7% of the total cost of fraud, while false positives amount to 19%. Cyber fraud fusion improves the accuracy of fraud detection by using advanced analytics to distinguish between genuine threats and legitimate user activities, reducing alert fatigue and ensuring your teams trust your technology. 
4. Enhanced Customer Trust: Proactively protecting user accounts and data not only reduces the risk of breaches but also enhances your reputation as a trustworthy guardian of customer information. This is especially important in sectors like fintech and healthcare, where customers rely on you to safeguard their personally identifiable information (PII). Taking a holistic approach to security leads to increased customer digital trust, confidence, and loyalty.
5. Operational Efficiency: Streamline fraud management processes by automating routine tasks and centralizing threat intelligence. Cyber fraud fusion focuses on using technology to eliminate manual, repetitive tasks so security teams can focus on high-priority issues like advanced persistent threats (APTs), incident response, threat intelligence analysis, and security architecture improvement. 
6. Proactive Risk Management: Another benefit of this approach is that it enables organizations to anticipate and prepare for emerging fraud trends by analyzing historical data patterns and industry-wide threat intelligence. Cyber fraud fusion also focuses on techniques like scenario planning and red-team exercises to help prepare for potential threats through simulations that test the effectiveness of your measures. 
7. Improved Regulatory Compliance: Comprehensive monitoring and auditing capabilities are essential for meeting the evolving security and privacy standards that exist across various industries and borders. By collecting and analyzing all threat data in a single fusion center, this novel approach to organizational security simplifies compliance with regulations like the GDPR, CCPA, and PCI-DSS. Fusion centers are typically equipped with advanced reporting features that provide detailed logs and audit trails that you can use to demonstrate compliance during regulatory reviews, reducing the risk of penalties and enhancing your organization’s credibility. 

Leverage Cyber Fraud Fusion with Sift

Isolated departments and internal data silos leave you unprepared for the AI-powered threat actors of today. ATO attacks are particularly threatening because they directly target the customer. You may have strong defenses on your own network, but protecting accounts that belong to your customers is a much greater challenge.

That’s where Sift comes in. Sift’s AI-powered fraud decisioning platform embodies the principles of cyber-fraud fusion through several key advantages: 

• AI-powered risk assessment: Uses advanced machine learning to detect complex fraud patterns across multiple channels.
• Cross-platform integration: Smoothly combines data from various sources for comprehensive fraud analysis.
• Customizable rules engine: The fraud detection solution allows you to tailor fraud detection strategies to your specific needs and risk tolerance.
• Automated response workflows: Enables quick action against potential fraud attempts, reducing manual intervention.
• Continuous learning: Adapts to new fraud techniques through ongoing model updates and refinement.
• Comprehensive reporting: Offers detailed analytics and insights for informed decision-making and strategy optimization.

Learn more about why cyber-fraud fusion is the future of online fraud detection.