AI’s ability to quickly and accurately analyze large data sets makes it a powerful cybersecurity tool for financial institutions, helping to predict and mitigate threats while maintaining trust.
Financial institutions are built on trust, sometimes for centuries. In today’s digital world, cybersecurity plays a critical role in building and maintaining that trust.
As it has been since the beginning, cybersecurity is an arms race: emerging technologies don’t distinguish between good and evil; the bad guys have the same tools as the good guys, and each side is always trying to stay one step ahead of the other.
It is impossible to talk about new technologies without mentioning the rapid rise of artificial intelligence, which is constantly demonstrating its applicability in real life. Large language models (LLM) are almost commoditized and easily accessible to the general public and AI has certainly gone beyond the status of a “buzzword”.
Emerging technologies Financial institutions must take a cautious approach to building the trust they have earned from their customers, but their criminal adversaries have no such limits. Now is the time for financial players to understand and adopt what AI can do for them in security and fight fire with fire.
When AI is viewed as a hammer, everything starts to look like a nail. Despite the rise of AI and other emerging technologies, effective cyber defense still relies on proven methods of prevention and detection; attackers, even artificial ones, have habits.
What’s different today is the scale of the landscape and the volume of data. Non-human malicious actors will likely be more precise and leave a much smaller footprint compared to their human counterparts, making these patterns harder for the human eye to detect.
AI stands out for its ability to quickly and accurately analyze vast amounts of data and find patterns in the smallest data gaps that humans would take much longer to spot, if at all. Additionally, effectively implemented AI systems can learn over time, adapt to new threats, and even become proactive by predicting attacks before they happen based on indicators of compromise, making it one of the most powerful tools in modern cybersecurity.
THE to go out AI is a compelling proposition for risk-averse businesses because it can quantify and manage risk in a way that humans can’t. When AI has historical data, it can be trained to predict potential security issues and even suggest ways to mitigate them before they happen, helping to guide resource allocation to avoid costly incidents.
Given AI’s pattern recognition capabilities, it can be applied to other areas of security beyond cyber threats. For example, AI-powered biometric systems and user behavior analytics can detect indicators of fraud with fewer false positives than ever before. AI can also be trained to maintain regulatory compliance by analyzing transactions for suspicious activity and flagging anything that might require more judgment to help prevent financial crime and reputational damage.
The benefits of AI are many, but introducing this technology into a financial institution is not without its challenges. In many cases, AI is an opaque system that does not offer transparency in its decision-making, which is in stark contrast to the needs of these institutions, which poses challenges in terms of accountability and compliance.
Data Privacy AI is also a concern because an AI system requires access to a large amount of data that must be taken into account. Each institution will have to decide for itself where the balance lies between security and privacy. Furthermore, while AI is very effective at analysis, human judgment is often still required, meaning that AI-based tools need to be refined and staff trained to get the most out of them.
AI is definitely here to stay. It’s a real technology that solves real problems and it delivers maximum value when well defined and optimized. For now, AI is not replacing cybersecurity professionals.
In early 2024, the US government flew real military fighter jets in a dogfight scenario, where one of the planes was piloted by a highly experienced aviator and the other by an artificial intelligence trained in dogfighting, but the AI-piloted plane always had a human pilot in the cockpit to take over if necessary. It should be noted that the pilot reportedly did not take control of the plane at any point in the scenario, nor did it reveal the winner.
Financial institutions should seriously consider how to add AI to their security toolbox to help their already skilled and trained leaders identify threats more quickly and accurately, because it is not a one-size-fits-all implementation. AI, while it does carry some risks, can be implemented safely and its risks mitigated if it is applied methodically using the proven methods on which these institutions have built their foundations.
Brian Wagner is a seasoned cloud technology and security expert with over 20 years of experience, particularly in the global financial services industry. He has held senior roles including Head of Security and Compliance at AWS Financial Services EMEA, Director of Cloud and Security at a Silicon Valley analytics firm, and CTO of a UK-based cybersecurity provider. As CTO at To come backBrian uses his expertise to develop innovative products tailored to the unique needs of the financial services industry, ensuring security, scalability and reliability.
