Finance has a reputation for being difficult, and for good reason. Even apparently simple concepts become complicated once we look closely at the real financial world. A bond involves an issuer, a security, identifiers, contractual obligations, payments, prices and lifecycle events. A derivative can bring in multiple parties, economic terms, rights, obligations, amendments, novations and … Continue reading Financial Ontology Modelling for Everyone (5): Finance Is Hard. Ontology Should Not Be. →

For a long time, financial technology supported a fairly clear division of labour. Business people understood the financial problem, analysts translated it into requirements, architects designed the system, and developers implemented it. That model was never as clean as the organisation chart suggested, but it worked well enough. A developer could spend years building trading … Continue reading Financial Ontology Modelling for Everyone (4): The End of the Technology-Only Financial Technologist →

In the previous article, we looked at a problem that sits underneath many disappointing enterprise AI applications. The organisation often already has much of the knowledge the AI needs, but that knowledge is scattered across people, systems, code, policies and operating practices. For years, financial institutions have been able to live with this arrangement. Different … Continue reading Financial Ontology Modelling for Everyone (3): AI Makes Shared Meaning Everyone’s Problem →

In the previous article, we looked at a strange feature of modern financial AI. Large language models can know an extraordinary amount about finance. They can explain products, markets, settlement, corporate actions, valuation and risk in impressive detail. Yet once we ask them to solve a real problem inside a financial institution, that knowledge often … Continue reading Financial Ontology Modelling for Everyone (2): Your Organisation Knows More Than Its AI Does →

For a while, the story of enterprise AI was mostly about the model. Get access to a stronger large language model, give it more context, connect it to your documents and systems, and the quality of the application should improve. That story is now changing. More people have realised that a powerful model is not … Continue reading Financial Ontology Modelling for Everyone (1): Your AI May Know Finance Better Than You Think — and Still Be Useless →