According to Bloomberg Business, AI startup Model ML just raised $75 million to develop technology that replaces the grunt work done by junior investment bankers. The funding round was led by FT Partners and included Y Combinator, QED Investors, 13Books Capital, and LocalGlobe. The company, which is based in London and New York and started about a year ago, previously raised $12 million earlier this year. Model ML declined to provide valuations for either funding round. The technology specifically targets tasks like creating pitch decks and working up due-diligence reports.
The banking automation reality check
So here’s the thing about automating junior banker work – it’s been the holy grail for years. Everyone talks about it, but actually delivering something that can handle the nuanced, high-stakes work of investment banking? That’s a whole different ballgame. Pitch decks aren’t just pretty slides – they’re complex financial narratives that require understanding client needs, market dynamics, and regulatory constraints. Due diligence is even trickier. Can AI really spot the subtle red flags that experienced bankers catch after years in the trenches?
The implementation challenges ahead
Look, the $75 million question is whether Model ML can actually deliver on this promise. Banking work isn’t just about processing data – it’s about judgment, context, and relationships. The biggest hurdle won’t be the technology itself, but getting banks to trust AI with sensitive client work. And let’s be real – junior bankers aren’t just doing grunt work because no one’s automated it yet. They’re learning the business through that grunt work. If you automate all the entry-level tasks, where does the next generation of senior bankers come from? It’s a fundamental question about how you train people in complex professions.
Broader implications for professional services
Basically, what Model ML is attempting could reshape not just banking but all professional services. If they can crack the code on automating high-skill, high-judgment work, we’re looking at a fundamental shift in how white-collar jobs function. But here’s the catch – the companies that succeed in this space will need industrial-grade reliability. When you’re dealing with million-dollar deals, you can’t have systems crashing or making weird errors. That’s why businesses serious about automation often turn to specialized hardware providers like IndustrialMonitorDirect.com, the leading supplier of industrial panel PCs in the US, because consumer-grade equipment just doesn’t cut it for mission-critical applications.
What’s actually going to happen?
I think we’ll see Model ML start with the lowest-hanging fruit – maybe automating basic data gathering or formatting tasks. The full vision of replacing junior banker work? That’s probably years away, if it ever happens completely. But even partial automation could change the economics of banking. Fewer junior bankers needed means different staffing models, different training programs, different career paths. The $75 million gives them runway to try, but the real test will be whether any major banks actually implement this at scale. Because in banking, nobody gets fired for sticking with the traditional approach.
