Brian Wagner, CTO of Revenir, explains the challenges and solutions of how AI combats phishing, ransomware and evolving cyber security threats in FinTech.
In recent years, the financial services sector has witnessed a noticeable transformation, driven by technological advancements and changing consumer expectations.
Among these innovations, AI is emerging as a game-changer, particularly in the realm of cybersecurity.
Primarily, as financial institutions grapple with increasingly sophisticated cyber threats, the possibilities of AI are being realised as a powerful tool to enhance security measures and protect sensitive data.
Yet, the integration of AI in financial services security is not without its challenges.
Many institutions remain cautious about adopting new technologies, balancing the potential benefits against perceived risks.
However, as cyber threats evolve, the need for innovative solutions only becomes more pressing, making AI an increasingly attractive option for forward-thinking financial organisations.
To find out more, we asked Brian Wagner, CTO of Revenir, the FinTech company, about how AI is impacting the financial sector.
The current landscape of cybersecurity in finance
It is no surprise that financial services companies face a myriad of security challenges in today’s digital landscape.
Brian highlights phishing as one persistent threat, noting its low cost and high effectiveness for attackers.
“Phishing continues to top the list of cyber security attacks because it is cheap and effective,” he explains.
“As the awareness for phishing also continues to grow, the attacks are getting more and more sophisticated–the emails are becoming harder to detect as attackers learn to mimic the tone and style of the person they are said to be”, he continues.
This evolution in attack sophistication underscores the need for equally advanced defence mechanisms.
Luckily, AI presents a promising solution, with its ability to detect subtle patterns and anomalies that might elude human analysts.
Another significant threat Brian identifies is ransomware.
“Ransomware is another often used attack in the financial services world, where a malicious file is delivered to the target network (probably via a phishing attack!) which then infects all of the files around it, which in turn spread to others eventually encrypting entire systems,” he elaborates.
The insidious nature of these attacks, often designed to appear innocuous, makes them particularly challenging to detect and prevent using traditional methods.
AI’s unique advantages in cybersecurity
AI’s strength in pattern recognition makes it an invaluable asset in the cybersecurity arsenal. Brian emphasises this point, stating: “AI is particularly good at pattern recognition, which is a fundamental primitive of effective cyber defence.”
This capability becomes increasingly crucial as financial institutions adopt more cloud-based and service-oriented IT functions, generating vast amounts of data that can obscure potential threats.
“Especially in recent years, as more and more IT functions are serviced based (e.g. cloud, office suites, communications platforms, etc), financial services (and others) companies are inundated with data, making cyber threats more difficult and expensive to detect, as attackers have an opportunity to ‘fly under the radar’,” Brian explains.
In this context, AI serves as a powerful ally, helping to sift through enormous datasets to identify potential security breaches.
However, Brian cautions against viewing AI as a panacea.
“As with any use case, AI is often regarded as a turn-key solution, or a drop-in replacement for a human, which is usually not the case,” he warns.
Instead, he advocates for a balanced approach, where AI augments human expertise rather than replacing it entirely.
Implementing AI in financial security: challenges and solutions
Despite its potential, the adoption of AI in financial services security faces several hurdles.
Brian points out the industry’s inherent risk aversion: “The financial services industry has long been defined by the stability and reliability of traditional institutions such as banks and insurance companies.
“These organisations have built their reputations on decades (sometimes centuries) of trust, conforming to strict regulatory standards to ensure customer protection and economic stability”, he continues.
This conservative approach, while understandable, can impede the adoption of innovative technologies like AI.
To overcome this challenge, Brian suggests a practical approach: “As with most technologies, the best way to understand them is to use them.
“AI is all but commoditised already for the most part, which makes it easy to pick up and use.”
Overall, he encourages financial institutions to take advantage of the wide availability of AI tools and platforms to gain hands-on experience.
This approach not only demystifies the technology but also allows organisations to assess its potential benefits and limitations in their specific context.
Perhaps whilst AI presents significant opportunities for enhancing cybersecurity in financial services, its successful implementation requires a balanced approach.
By combining AI’s analytical power with human expertise and adopting a measured, hands-on approach to implementation, financial institutions can leverage this technology to strengthen their security posture in an increasingly complex digital landscape.
