How To Make Your CA(SA) Articles Worthwhile
2 Min Read
An AI trading firm I've been quietly watching crossed a billion dollars in single-day trading volume and closed out 2025 with a 51% return.
The company is Vertus, based in the Isle of Man, and the headline numbers are impressive by any institutional benchmark.
But what makes Vertus genuinely interesting is the shape of the business, and what that shape says about our roles in finance among rapidly developing AI systems.
Fun fact: The most successful hedge fund in history, Renaissance Technologies' Medallion Fund, has been closed to outside investors since 1993. It reportedly averaged about 66% gross annual returns over three decades. Founder Jim Simons famously refused to hire from Wall Street and recruited physicists and mathematicians instead. He said that whenever they brought in finance people, the models got worse..
What Vertus Actually Does
Founded in 2022 by three entrepreneurs with backgrounds in medical robotics, space tech and quant finance, Vertus reported a 51.15% return for 2025, a Sharpe ratio of 2.13, and over a billion dollars in daily trading volume. Numbers that put them in conversation with the top tier of quantitative funds globally.
Vertus isn't a hedge fund in the traditional sense. They build the AI trading systems and license them out to regulated asset managers, who then put the strategies in front of their own clients. Their pricing makes the model explicit: $10m to white-label the tech under a partner's brand, $20m for custom builds, $50m for a Vertus-branded allocation run through a partner.
The Real Lesson Here
The hardest, most technical work in the value chain, building a system that can reason about markets in real time, has been turned into a product line. What Vertus actually monetises is the act of packaging the AI.
The technical execution layer in finance and accounting is increasingly being replaced by AI and software systems. For instance:
The Big Four have rolled out AI audit platforms (KPMG Clara, EY Helix, PwC Halo, Deloitte Omnia) which are capable of running full-population testing.
SARS uses machine learning to risk-score returns.
Equity research notes are increasingly drafted by models.
Hedge Funds are using AI algorithms to manage funds.
The layer becoming more valuable is someone who understands the mechanics and the business problem well enough to translate between them. Someone who can pick the right tool for the client's mess, configure it, sense-check what it outputs, and stand behind the answer when the regulator comes asking.
Lessons For Future CA(SA)s
Fundamentals still matter, just for a different reason. You can't validate an AI output if you don't know what the right answer roughly looks like. IFRS, the tax code, audit methodology, these become the lens you use to make sure things make sense.
Get fluent with the tools. Not at a coding bootcamp level but knowing which tool fits this problem and how to prompt it properly.
Watch the seam. The roles that compound in value sit at the seam between the technology and the client.
Roundup
Vertus has built something genuinely impressive, and the structural insight from how they've put their business together is worth even more than the headline returns. The quieter bit of their model, building an AI then renting it out to people who actually face the client, is the most honest preview of where finance careers are heading that I've seen this year. Technical work gets productised and value moves into translation, judgment, packaging and trust.
It's the same sentence the profession has been writing about itself since the spreadsheet replaced the ledger book. We're just doing it faster now, with better marketing.
Until next week,
The Journal Entry Team
If you enjoy our content we’d love it if you showed your friends and peers!
Please copy and paste this link to others:
