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Roula Khalaf, editor of the FT, picks her favorite stories on this weekly newsletter.
Shortly after moving into investment banking in 1997, I used to be sent to a hotel in Sussex with other recent recruits on a week-long financial modeling course. It was raining non-stop and our important distractions were the hotel bar and playing Snake on our Nokias.
Our lecturer, a graduate of an American business school, seemed incredulous that his profession had been limited to teaching such a boring bunch.
I didn't just like the training. Although I understood the ideas, my rudimentary Excel skills and clunky Gateway computer made the exercises extremely tedious. As the brand new “Associate Director”, who comes from a law school, I even have set myself the skilled goal of never constructing a model myself. I missed many goals over the following 25 years, but I achieved this one.
Now the routine work I desired to avoid is on the verge of mass automation. According to Bloomberg, OpenAI has done this rented More than 100 former bankers from firms like Goldman Sachs and JPMorgan paid them $150 an hour to coach their artificial intelligence to develop the models that outline junior banking.
What's surreal is that they make more per hour teaching their reps than they do working. A full-time junior banker earning $200,000 per yr earns about $50 per hour, assuming an 80-hour work week.
In recent many years, investment banking has develop into a story of “revenge of the nerds.” Hiring has shifted from the verbally fluent generalist or scratch golfer to the tech-savvy workhorse. The ideal junior is someone who can calculate discounted money flow in every way possible and cope with last-minute corrections to a pitch book by a highly insecure CEO.
In my very own London team, we found that we were hiring more graduates from continental business schools than from Oxbridge liberal arts graduates. It wasn't intentional; They simply performed higher in technical assessments. The job rewarded precision, resilience and database mastery. The aspiring archetype became a multilingual PowerPoint wizard with multiple internships.
AI now threatens to show this logic on its head. Once machines can model 1000’s of scenarios in seconds, competitive advantage will lie less in accuracy or endurance and more within the qualities which have at all times prevailed in the upper echelons of investment banking – strong judgment, credibility and the power to inform a story that offers intending to numbers. The show horses could still outshine the work horses.
This transition won’t occur overnight. Automating complex financial tasks requires years of refinement. The pressure to enter will ease progressively after which perhaps suddenly, impacting not only the banks but additionally the private equity groups and hedge funds that depend on them to coach their future talent.
The job structure has at all times been based on apprenticeships: you could have to endure years of labor and eventually rise to develop into an advisor to managing directors. Remove the underside rungs of this ladder and the structure becomes wobbly and unstable. You can't make a chatbot learn customer management or intuition. AI can model any scenario, but it might probably't read space (a minimum of not yet).
It's ironic that the traits most valued in recruits – attention to detail, 24/7 responsiveness and Stakhanov work ethic – are the very ones which might be easiest to copy by AI. Machines don't change decimal places, don't call in sick and don't fly to Italy for a friend's wedding on the weekend. You don't have any friends (a minimum of not yet).
In short, the “nerds” who displaced the graceful talkers are actually, perhaps unintentionally, training the machines which will take a few of their roles away from them.
For the junior banker, this doesn’t necessarily mean extinction, nevertheless it does require reinvention. A brand new hybrid may emerge: the lead analyst who monitors AI output, tests its assumptions, and interprets its conclusions. Modeling knowledge remains to be required for this. But the main target would shift from execution to oversight and communication.
Even experienced rainmakers aren’t immune. The traditional pyramid relies on legions of junior employees (spoons) presenting evaluation to a handful of CEOs. If a smaller, AI-powered team delivers the identical performance, why keep the old hierarchy? Customers can also be more proof against fees that end in high overhead costs. Smaller boutiques or recent entrants may benefit from this.
In the longer term, more machines will take over evaluation and number processing in investment banking advice, while humans could have to pay attention more on persuasion. Or perhaps sooner or later the machines will learn this too. Until then, it's amazing to see how a career based on perseverance and sacrifice outsources perseverance itself.
