Language, the oldest technology humans ever deployed, has long been the silent architecture of financial power. In a wide-ranging analytical essay published on The Finanser, veteran fintech commentator Chris Skinner advances a thesis that deserves serious attention in boardrooms and central banks alike: the concentration of global economic power is inseparable from the concentration of linguistic dominance — and Britain's ascent, achieved in part by absorbing and repurposing the French language, is the most instructive case study history offers. The question he leaves hanging in the air, urgent and unresolved, is whether artificial intelligence is about to dissolve that advantage entirely.
The argument is deceptively simple on its surface. Nations and empires that control the dominant language of commerce, law, diplomacy, and technology control the terms of every transaction conducted within those frameworks. France understood this for centuries, projecting its cultural and financial influence across Europe and beyond through the supremacy of French as the language of courts, contracts, and civilised exchange. Britain, through a combination of conquest, commerce, and what Skinner pointedly frames as linguistic appropriation — absorbing the vocabulary of its Norman French rulers after 1066 — eventually displaced French as the global operating system of power.
The historical lineage Skinner traces is striking. Viking invaders reshaped the linguistic substrate of the British Isles long before the Norman Conquest formalized French aristocratic influence over English governance and trade. What emerged was not a defeat of English but a hybridization: a language capacious enough to absorb Latin legal terminology, French commercial vocabulary, and Germanic structural roots, producing a tongue uniquely suited to the demands of global empire and, later, international finance. The City of London did not become the world's preeminent financial centre by accident; it did so in a language that had already colonised the vocabulary of money itself.
American technology then extended that dominance into the digital age. The internet was built in English. The protocols, the programming languages, the foundational documentation of the global financial technology stack — all composed in a language whose intellectual geography traces directly back to those Viking longships and French aristocratic courts. When SWIFT messages traverse the globe, when Bank for International Settlements working papers circulate among central bankers, when International Monetary Fund conditionality frameworks are negotiated, the working language is English — itself a monument to centuries of calculated linguistic absorption.
For the fintech industry specifically, this dynamic has concrete competitive implications. Startups pitching to venture capital in London or San Francisco operate within an English-language framework that is not merely convenient but structurally privileging. Regulatory guidance from the Financial Conduct Authority and the European Central Bank alike is increasingly published in English first. Product documentation, application programming interfaces, developer ecosystems — the entire commercial infrastructure of modern financial services — runs on a linguistic monopoly that English-speaking markets did not so much earn as inherit through the long historical arc Skinner describes.
Which brings the argument to its most consequential and genuinely unsettling inflection point: artificial intelligence. Large language models, trained predominantly on English-language data, have until very recently reinforced the existing hierarchy — giving English-speaking developers, financial institutions, and regulators yet another structural advantage in the emerging AI-powered economy. But that dynamic may be reversing faster than most market participants appreciate. Multilingual AI models are improving rapidly, and the translation barriers that long disadvantaged non-English-speaking financial ecosystems are eroding in real time. A French neobank, a Brazilian payments startup, or a Japanese asset manager may soon be able to operate at the frontier of AI-assisted financial innovation without any meaningful linguistic penalty.
If Skinner's core thesis holds — that language concentration is the mechanism through which power concentrates — then the flattening of linguistic advantage by AI represents something far more significant than a cultural footnote. It is a potential reordering of the competitive map of global finance. The institutions, regulators, and technology firms that have long benefited from English's status as finance's native tongue would face a world in which that advantage no longer compounds automatically with each new technological cycle.
What This Means for Financial Markets and Institutions
The practical implications are worth spelling out. Financial institutions headquartered outside the anglophone world have historically faced invisible friction costs — in talent acquisition, regulatory engagement, and technology adoption — that English-language incumbents never had to price in. As AI-driven translation and multilingual interface layers mature, those friction costs decline. The competitive moats built partly on linguistic geography become shallower. At the same time, institutions that have relied on English-language dominance as a passive advantage may find themselves exposed if they mistake a structural tailwind for genuine organisational capability.
Chris Skinner has spent two decades mapping the intersection of technology, culture, and financial power. His framing of language as the original fintech — the first tool that allowed humans to coordinate economic activity at scale — is not rhetorical flourish but analytical precision. The history he sketches, from Viking raiders through Norman aristocrats to Silicon Valley engineers, is ultimately a history of who controls the terms in which money speaks. The coming years will determine whether AI writes a new chapter in that story, or simply translates the old one into every language simultaneously.
Written by the editorial team — independent journalism powered by Codego Press.