The financial services industry has consistently led the way in adopting new technologies from automated teller machines (ATMs) to digital banking platforms. Now, it’s embracing artificial intelligence (Adversarial AI) at an accelerated pace. According to a joint survey conducted by the Bank of England and the Financial Conduct Authority, 75% of financial institutions are already utilizing AI, with another 10% expected to follow suit within the next three years.
AI is being deployed across multiple domains such as fraud detection, data analytics, and customer service. However, despite the widespread adoption, less than one-third of institutions surveyed believe they fully understand the technology. This gap in comprehension raises concerns, particularly as financial entities confront a rising and unfamiliar threat: adversarial AI.
Experts emphasize the importance of developing a deeper institutional understanding of AI’s inner workings. As financial institutions integrate AI into their operations, malicious actors are simultaneously mastering how to exploit these systems for their own advantage.
Understanding the Threat of Adversarial AI
Adversarial AI represents a significant shift in the cybersecurity threat landscape. Unlike traditional cyberattacks that rely on malware or hacking techniques, adversarial AI manipulates the AI algorithms themselves or the data that trains them. These subtle alterations can skew predictive models, obscure fraudulent activities, or even provide false financial forecasts that adversaries can exploit for gain.
Such attacks do not fall within the scope of conventional cybersecurity defenses like firewalls or antivirus software. Instead, they require an advanced, adaptive approach to risk management. Financial institutions must begin to familiarize themselves with complex concepts such as data poisoning (the manipulation of training data), inference-time attacks (disruptions during algorithm execution), model contamination, and vulnerabilities in the AI supply chain.
Regulatory bodies are also working to keep pace with these emerging threats. While compliance frameworks are still evolving, future regulations are expected to address the intricacies of adversarial AI. Financial institutions must prepare now to meet these expanded expectations.
Training and Preparedness-The Way Forward
As the financial sector navigates this new terrain, organizations like QA, a leader in AI education and advocacy, are stepping in to bridge the knowledge gap. With years of experience monitoring AI developments across industries, QA is offering specialized training to help financial institutions tackle the challenges posed by adversarial AI.
The organization is also engaging with policymakers to promote the development of regulatory frameworks that reflect the complex risks associated with AI, ensuring that both institutions and their customers remain protected.
While not all financial entities fully grasp the intricacies of AI, they are well-versed in risk management. Recognizing that threat actors are rapidly mastering AI tools, these institutions understand the urgency of acting now. A robust training and security strategy can enable firms to harness the full potential of AI while safeguarding against its darker applications.
AI is no longer a future technology it’s already reshaping financial services. The next imperative is clear- secure it before adversaries exploit it.
