Use of LLMs for Network Security within Fintech Companies

Sammanfattning

Artificial intelligence has developed rapidly in recent years, and one important development within this area is the rise of Large Language Models (LLMs). Previous research shows that LLMs may be useful in several cybersecurity and network security tasks, such as threat detection, anomaly detection, incident response, malware analysis, and vulnerability assessment. However, much of the existing research focuses on specific model performance, technical capabilities or general cybersecurity use cases, while less attention has been given to how LLMs may be understood and used in specific company settings such as fintech companies.The aim of this study was to explore how professionals in fintech companies perceive and describe the use of LLM technology for network security, including current use, potential benefits, opportunities, challenges and risks. The study used a qualitative method based on semi-structured interviews with five professionals working in fintech environments. The collected data was analyzed using thematic analysis.The results show that current use of LLMs for network security within the studied fintech companies is limited and not yet fully established. The majority of participants described no direct use but they also described early testing or using them in other ways to help with cybersecurity related work. The main potential use cases identified were code review, threat modelling, information search, monitoring, and analyzing logs or processing large amounts of data. The findings also show that LLMs are mainly viewed as support tools that can help reduce manual work in complex security environments. At the same time, several challenges were identified, including hallucinations, false positives, incorrect actions, data protection concerns, regulatory requirements, and the risk of giving AI systems too much decision making power. Human controls like human in the loop, review and trust but verify, and accountability were therefore identified as important conditions for using LLMs in network security work. Overall, the study concludes that LLMs have potential to support network security within fintech companies, but that potential implementation is shaped by practical, legal, organizational, and security requirements.