LLMs excel at processing unstructured data, such as natural language human input, documents, images and audio recordings, but run much more slowly- specialised hardware is required for the output to be produced within a reasonable time.
They are better suited for asynchronous or interactive tasks, such as agentic systems that help resolve open fraud or AML cases, expert systems, research assistants, report writers and chatbots.
“ We built a single EFM platform that ingests data once, unifies fraud and AML decisioning and applies rules, graph analytics, network intelligence and machine learning across the entire customer journey”
Ivan Stefanov, CEO & Co-founder, NOTO fintechmagazine. com 95