Why Markets Need a Finance-Specific Knowledge Graph

Without explicit domain structure, even strong LLMs can miss nuance or retrieve results that look relevant but aren’t. That’s especially true in financial markets, where language is dense, overlapping, and constantly evolving.

A finance-specific Knowledge Graph helps by:

• 𝗜𝗺𝗽𝗿𝗼𝘃𝗶𝗻𝗴 𝗿𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 𝗮𝗰𝗰𝘂𝗿𝗮𝗰𝘆 through domain specific themes and well defined relationships between concepts
• 𝗣𝗿𝗲𝘀𝗲𝗿𝘃𝗶𝗻𝗴 𝗰𝗼𝗻𝘁𝗲𝘅𝘁 when the same term carries different meanings across markets
• 𝗥𝗲𝗱𝘂𝗰𝗶𝗻𝗴 𝗳𝗮𝗹𝘀𝗲 𝗽𝗼𝘀𝗶𝘁𝗶𝘃𝗲𝘀, supported by paragraph level atomisation and precise disambiguation
• 𝗔𝘂𝗱𝗶𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗯𝘆 𝗱𝗲𝘀𝗶𝗴𝗻, enabling transparent tracing of how concepts link, evolve, and inform outputs
• 𝗘𝗻𝗮𝗯𝗹𝗶𝗻𝗴 𝗚𝗿𝗮𝗽𝗵𝗥𝗔𝗚, providing the structured domain backbone that makes RAG reliable, it’s how you win with RAG

Our knowledge graph of more than 𝟮𝟬𝟬,𝟬𝟬𝟬 𝗳𝗶𝗻𝗮𝗻𝗰𝗶𝗮𝗹 𝗰𝗼𝗻𝗰𝗲𝗽𝘁𝘀 is 𝗿𝗲𝗴𝘂𝗹𝗮𝗿𝗹𝘆 𝘂𝗽𝗱𝗮𝘁𝗲𝗱 𝗯𝘆 𝗼𝘂𝗿 𝘁𝗲𝗮𝗺, ensuring human oversight where it matters. This creates a clear, evolving map for models to navigate, one that reduces ambiguity, keeps pace with new themes, and provides a stable foundation for interpreting complex topics.

The takeaway is simple:

𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝗱𝗼𝗺𝗮𝗶𝗻 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲, 𝗺𝗮𝗶𝗻𝘁𝗮𝗶𝗻𝗲𝗱 𝘄𝗶𝘁𝗵 𝗵𝘂𝗺𝗮𝗻 𝗼𝘃𝗲𝗿𝘀𝗶𝗴𝗵𝘁, 𝗺𝗮𝗸𝗲𝘀 𝗳𝗶𝗻𝗮𝗻𝗰𝗶𝗮𝗹 𝗔𝗜 𝗺𝗲𝗮𝗻𝗶𝗻𝗴𝗳𝘂𝗹𝗹𝘆 𝗺𝗼𝗿𝗲 𝗮𝗰𝗰𝘂𝗿𝗮𝘁𝗲.