Smart(er) Cybersecurity

To combat ever-evolving threats, cyber-savvy credit unions are adopting a defense-in-depth approach complemented by AI and ML technologies to protect sensitive data and maintain member trust.

The cybersecurity landscape is in a constant state of flux, with new threats emerging almost daily. For credit unions, the stakes are particularly high. The sensitive nature of the data you handle—ranging from members’ personal information to transactional records—makes you a prime target for cybercriminals. 

According to the What’s Going On in Banking 2024 report from Cornerstone Advisors, 48% of credit union executives identified cybersecurity as a top concern, up from 35% in 2023. This growing awareness reflects the escalating risks that credit unions face.

And IBM’s 2024 Cost of a Data Breach Report highlights the severity of these threats, revealing that the average total cost of a data breach has reached an all-time high: the average incident results in losses of $4.88 million, a 10% spike from $4.45 million in 2023—and the highest increase since the pandemic. 

These figures underscore the financial implications of utilizing inadequate cybersecurity measures and reinforces the critical need for credit unions to implement a comprehensive, layered defense strategy to better protect mission-critical data and 
systems. 

The Importance of Defense-in-Depth

One of the most effective strategies in cybersecurity is defense-in-depth, which involves deploying multiple layers of security controls to protect data and systems. This approach reduces the risk of a single point of failure and ensures that if one layer is breached, others remain in place to protect the system. 

Say, for example, that a hacker manages to bypass a firewall. With multiple layers of security controls in place, the hacker would still need to get through additional security measures like intrusion detection systems, encryption, and multi-factor authentication. This layered approach complicates an attacker’s efforts to gain unauthorized access, providing more opportunities for your systems to detect and stop a breach before significant damage occurs.

A defense-in-depth approach extends beyond just technical measures. It also includes policies, procedures, and employee awareness training—since human error remains one of the most significant vulnerabilities in cybersecurity. According to the 2024 Data Breach Investigations Report from Verizon Business, the financial services industry continues to be a target for cyberattacks, with system intrusion, miscellaneous errors, and social engineering representing 78% of breaches. 

Your employees are often the first line of defense against social engineering attacks and other user-targeted threats, so you can reduce the likelihood of successful attacks and improve your overall security posture by equipping staff to recognize and respond to potential threats, thereby fostering a culture of security awareness in your organization. 

Leveraging AI and Machine Learning in Cybersecurity

The Bankers as Buyers 2024 report from the William Mills Agency notes that as cyber threats become more complex and complicated, addressing the challenge is always top of mind for financial institutions, making cybersecurity a top priority. 

But traditional defense mechanisms alone are no longer sufficient. This is where artificial intelligence (AI) and machine learning (ML) come into play to enhance a defense-in-depth strategy.

AI, which enables systems to mimic human intelligence and iteratively improve themselves based on collected data, can analyze vast amounts of data in real time and identify patterns, trends, and anomalies that might indicate a potential threat—something a human might not be able to do.

ML is a subset of AI that uses algorithms to parse data, learn from it, and make predictions. In cybersecurity, ML algorithms can predict the nature of a threat or identify unusual behavior within a network that may signal an attack. Additionally, ML algorithms can learn from past cyberattacks, improving their ability to predict and prevent future incidents.

When combined, AI and ML provide proactive threat intelligence, automate repetitive tasks for quicker threat response, and enhance the ability to predict, prevent, and mitigate cyberattacks.

Enhancing Cybersecurity with AI and ML

AI and ML can be deployed at various layers of defense to enhance threat detection and response. ML algorithms, for example, can analyze network traffic to identify unusual patterns that may indicate a cyberattack, while AI can automate responses to detected threats, reducing reaction time and potentially limiting damage. 

Credit unions that integrate AI and ML into a defense-in-depth cybersecurity strategy can gain several key benefits:

• Anomaly Detection: AI can learn what normal behavior looks like within a network and flag deviations, such as unusual data transfers or suspicious login attempts.
• Predictive Analytics: ML can analyze historical data to identify trends and patterns associated with cyberattacks, enabling you to anticipate and prevent similar threats.
• Phishing Detection: AI can scrutinize emails for signs of phishing, such as suspicious links or language, which are often precursors to more significant cyberattacks.
• Automated Response: AI can detect threats and automate a response—such as isolating a compromised system—thereby reducing the time it takes to contain an attack.
• Vulnerability Management: AI can scan and monitor systems for known vulnerabilities, allowing you to address potential weaknesses before hackers can exploit them.
• Threat Intelligence: AI can gather and analyze information about potential threats, helping you stay ahead of cybercriminals.
• User Behavior Analytics: AI can monitor user behavior for anomalies, such as login attempts at unusual times, which could indicate compromised credentials.
• AI-Powered Antivirus: Unlike traditional antivirus software that relies on virus definitions, AI-powered antivirus solutions can proactively detect and block unknown threats by analyzing file behavior.

A Comprehensive Approach to Cybersecurity

AI and ML offer significant enhancements to cybersecurity, but they are not a silver bullet. You need a comprehensive cybersecurity strategy that integrates these advanced technologies with traditional defense measures, employee training, and robust cybersecurity policies. 

No single layer of defense is perfect, but by employing a combination of these strategies, you can significantly reduce the risk of cyberattacks and better protect your credit union’s mission-critical data and systems.

Sebastian Fazzino is Head of Sales, Complementary Solutions at Jack Henry™. He is an innovative executive with over 30 years of IT, security, audit, sales, and operations management experience, and for the past 23 years, he has worked directly with financial institutions.

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