It’s a tough world out there for investment banks.
Tougher capital and market transparency regulations are hitting trading revenues, while weak global growth is putting at risk entire banking business models.
One way to adapt is to cut costs by automating as many of the repetitive processes as you can.
The challenge is balancing the automation with reliable fail safes that work when no human is about to check every trade.
At Goldman Sachs, that task falls to Damian Sutcliffe, the bank’s EMEA tech head and global chief of operations technology.
He sat down with Business Insider to discuss how the bank is using tech to navigate an uncertain financial world.
Business Insider: What’s the main project you’re working on?
Damian Sutcliffe: Probably the predominant thing we’re focused on is providing scale and automation for the firm more broadly. That goes into the way trades are processed, the way they’re priced — that’s increasingly being done algorithmically — all the way through to the client interactions, from the way we collect their allocations, to moving money and assets, to how we report to regulators.
In the current market conditions, there have been fewer and fewer banks that have been able to fund loss-leading businesses. So at some point you get to a moment where the pressure is too much for some places that haven’t been able to achieve the critical mass and that scale and then they pull out of that business and then that does open up market share.
But then market share is only attractive if every unit transaction you’re processing is done at a profit. So we see it as a huge opportunity. You can’t apply the old business model to the new environment and hope to be successful. And where it gets interesting for us in tech is that our division is central to the success or failure of our transformation in the new market conditions.
All of what we’re doing needs to be straight-through-processing to achieve the cost-per-trade on the expense side. Fewer human touch points, fewer errors that need humans to resolve, and more of the firm’s business being activated through computer code rather than human brains. The human brain is not operating the plant, it’s designing the plant that operates itself.
So there’s a huge focus on ourselves, all of the processing we do, what are the humans doing, how can we automate that, how can we remove the friction from the system.
BI: With fewer humans there’s greater efficiency, but doesn’t the system become more fragile with fewer checks and balances?
DS: There shouldn’t be fewer checks and balances and they may be automated themselves.
But computers are great at being told what to do, they do them very quickly, repeatedly with high precision. The challenge comes though that they’re not very good at noticing when something’s not right. And because they do it so quickly, it’s not one trade that might go wrong, it’s 100,000 processed in the 10 minutes that went wrong. What comes with that high level of automation is a huge increase in the inherent operational risk that lives in technology.
The human brain is not operating the plant, it’s designing the plant that operates itself.
Before it was “is the person in operations doing the right thing?” Now, it’s “is the computer being programmed correctly?” So we have to get ahead of that, we don’t want to fly ahead with automation and realise the world’s blown up. So in parallel we’re focused on the control side.
If you think about a nuclear power plant, you have very few people in the plant making sure everything is fine, that’s because the checks and balances are all automated probes that sit on the pipes and rely data back to the control room. So we’ve got to have automated kill switches because it’s not like you present the data to someone to and they can research it and take action. So you have to have something that says “this looks sufficiently bad, let’s pull the plug.” And then have people that can research it and make a decision later on what happened and take action if it’s a big problem.
The other thing we do is complying with the large amount of rule changes and expectations of perfection around the data we supply to regulators, which is continuing to accelerate. That has literally 1,000s of people on the firm working on it. Now it’s clear the regulators are looking.
BI: Is it tough to hire people in tech? It’s a competitive area.
DS: Technology skills are in huge demand across all industries. While our brand is extremely well recognised for investment banking and trading jobs, we’re not as well known for tech and engineering opportunities.
If you ask someone in the street “what is Goldman Sachs known for,” they will say investment banking, or even quite a lot of other things these days. But very few will say “that’s the place I want to go to because I’m a great engineer.”
If you say Google, naturally the engineers want to go there. Once we find people, we get extremely high acceptance rates. People like what they see once they have seen it. The challenge is getting people to come in and take a look.
BI: Finance doesn’t appeal to everyone. Is it tough to spark people’s imagination when Google engineers are working on things like driverless cars?
DS: That’s a fair point. If you ask me to compete on the driverless car front I may struggle. To me one of the pluses of the financial markets is that it’s fast-paced and that technology is central to it. The complexity of the problems we’re trying to solve and the nature of change of those problems, on a purely intellectual level, it’s incredibly appealing to smart people.
If you solve them, you will see the impact in people you’re sitting right next to. We don’t sit apart from the rest of the business. Maybe in some of the tech companies, you write some code, you through it out there and you don’t know if you’ve made a difference.
People like what they see once they have seen it. The challenge is getting people to come in and take a look.
BI: How do you compete on pay with the big tech companies?
DS: It’s a constant challenge. There are a number of tech firms that have strong revenues and high margins, while others have high valuations.
Out of campus, in the US the tech firms definitely bid up and are driving the market upwards. We haven’t seen that to the same extent in the UK. In the US, they’re outpaying us at the entry level.
But it’s interesting when you look at people we hire with four or five years experience from a Google or an Amazon, and you often don’t find there’s much difference there. We have a focus on onward progression of pay, while in other places you might stay on your entry salary, or thereabouts. At senior levels, I wouldn’t have said we were un-competitive, maybe even more on the upside.
BI: And what about attracting millennials?
DS: I think it’s important we adapt to the characteristics of the generation we’re hiring from. There are a number of things, such as getting access to mentors and respected people to help them. I think there’s a big focus on giving back and citizenship. In terms in work/life balance, we’re having to adapt around that. We’re about to launch a work from home initiative, which will have some jobs almost fully from home, and others two to three days in the office.
With the right equipment from home, people are starting to be more productive, with no commute time. People are taking about half of that commute time as extra work time, and the other half as time to balance out their lives. Money is one aspect of what drives people contentment, and I think with millennials it’s a smaller piece of the way they make their decisions.