From JPMorgan to Goldman Sachs, Lloyd’s of London and more, banks are making serious bets on technology innovation while bracing for the impact of the growing fintech sector. Now billing themselves as technology groups, rather than banks, they’re hiring more AI talent and diving deep into data offerings.
"Technology is going to fundamentally transform the banking industry over the coming years." Antony Jenkins former Barclays CEO via CNBC
Do you want to be an investment banker today? Learn to code. Want to be an analyst? Learn to code. A marketer? Sales executive? Product manager? Market researcher? Learn to code.
Having a solid degree and field experience alone are no longer enough to compete for spots at some of the world’s top institutions.
Specifically in the finance sector, firms globally are making moves to embrace the impact of AI and data-driven technologies. Today when you interact with the likes of Goldman Sachs and JPMorgan, you’re no longer entrusting your cash to banks. Instead, both now bill themselves as ‘technology groups.’ According to the Financial Times, “JPMorgan spends $10.8bn a year on tech, more than any other Wall Street group, and technologists account for about a fifth of the company’s 252,000-strong workforce.”
“Coding is not for just tech people, it is for anyone who wants to run a competitive company in the 21st century,” said Mary Callahan Erdoes, head of JPMorgan Asset Management. “These are skillsets of the future . . . By better understanding coding, our business teams can speak the same language as our technology teams, which ultimately drives better tools and solutions for our clients.”
In a move to better position itself on the tech ladder, for instance, Lloyd’s announced last month a global search for technology talent to fuel their new “Lloyd’s Lab,” designed to “help the insurance giant become even more competitive by securing partnerships with innovative global tech start-ups.”
“This is all about taking us into a technology-driven future,” Inga Beale, Lloyd’s CEO, told CNBC’s Squawk Box Europe. “There is huge demand from the market saying, ‘Come on, let’s get talking about innovation.’”
For traditional banks, the threat of innovative and agile startups feels increasingly real. Last year, $58B was raised globally in the fintech space. As well, those fintech companies “don’t suffer from legacy IT systems and can provide banking services 50% cheaper than big banks.” These banks are recognizing they need to transform themselves or risk being left in the dust.
JPMorgan makes coding classes mandatory
According to the Financial Times, JPMorgan is putting hundreds of new investment bankers and asset managers through mandatory coding lessons, including all 300 new recruits in its asset management division. Overall, a third of the bank’s analysts and associates have taken a coding program.
The team will begin with Python, which will enable them to effectively analyze and interpret large sets of data, with plans of incorporating data science, machine learning and cloud computing in the next year.
The importance of data analysis in the financial industry cannot be understated, as the alternative data industry continues to grow, and the ability to remain competitive lies increasingly in information and insights advantages.
Top financial institutions continue to hire for tech, data science and engineering talent to help them better mine the incredible amount of data they have available, while working to bring their current staff up to speed.
Goldman Sachs prioritizes tech innovation
Over at Goldman Sachs, ‘strats’ have been alive and well for years, working to develop technologies that make the Goldman team more productive.
According to a report on HBR.org, Goldman has repurposed the role of its Strats team (previously known as financial engineers or data scientists) to create a unified engineering front that works with bankers and clients directly, with 2 key goals in mind:
- to digitize bankers’ workflows through tools that improve productivity and quality of life
- to use technology that is to engage clients in a more modern, data-driven way
The team has also been leveraging external data insights to build apps for specific purposes, like those that “use machine learning algorithms to sift through SEC mutual fund filings to better understand how shareholders relate to each other. In addition, machine learning has been used to analyze the factors that make some companies more vulnerable to activist investors than others.”
Earlier this year, Goldman Sachs Group Inc. Chief Executive Officer Lloyd Blankfein presented on the firm’s future strategy at the Credit Suisse Financial Services Conference. Technology and innovation was a major part of what he discussed.
“Engineering underpins our growth initiatives,” Blankfein said, reiterating his comments from 2016 that positioned Goldman squarely in the tech space, competing with the likes of Google and Facebook." - Lloyd Blankfien
Back in 2016, the New York Times wrote on then-CIO R. Martin Chavez, who has been spearheading many of these efforts. Their vision was that Goldman will still have the chief product of a bank, but “the ways in which customers get access to that money will rely more on software and less on the bankers who traditionally delivered Goldman’s services.”
Today, the firm’s flagship loan and savings app, Marcus, has received significant traction as a prime example of the innovative technology they are working to develop in order to remain competitive in the face of the fintech revolution.
Driving real change
According to a recent report by EY, advancements in new technologies are driving change that will enable banks to:
- Better serve customers and increase access
- Provide enhanced insights both from a risk management and customer service perspective
- Increase agility and speed to market
- Strengthen operations and controls
- Transform institutional cost structures
These innovations are coming both from internal capabilities and external partnerships, driven by the need to derive insights from the vast amount of data we have available. Today, data scientists and programmers are proving just as valuable as traditional analysts. Is a swift and successful digital transformation of the banking industry the answer to their successful navigation of the coming AI revolution?
