Harnessing Large Language Models in Banking: Banking Innovation with Operational and Security Risks

The banking industry is becoming more inclined towards LLM for innovation in the services, better and more efficient operations, and customized services. I possess fantastic skills in utilizing technology in multiple areas related to customer support, fraud identification, and financial actions. Nevertheless, deploying these artificial intelligence systems has implications for operations and security, for instance, model interpretability, model bias, data privacy, and susceptibility to cyber-attacks. In addition, there are aspects of compliance with data protection laws and the fairness of AI decisions. This article describes the advances from LLMs in banking, discusses their inherent risks, and outlines sound application strategies. Thus, by following and sustaining proper data management, constant supervising, and employing the human-AI tandem working methodology, the banks can avail themselves of the opportunities LLMs offer without fearing the possible risks and avoiding ethical and legal norm violations.