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extensive innovation |
algorithms that beat passive asset selection.26 Risk |
management is another field where generative AI is |
seeing use as an advanced research tool that goes |
beyond its current rollout. Use cases here include trying |
to better understand asset correlation27 and tail risk, |
among others.28 |
While much of the abovementioned activity has |
occurred in academia, some companies are |
interested as well, at least in principle. UBS, for |
example, is researching the use of generative AI |
for trading applications. One compelling avenue is |
using the technology to express news, in the form of |
unstructured text, as a numerical vector in order to |
assess its impact on asset prices. |
The companys preliminary results show promise in |
improving the ability to forecast volatility changes |
driven by incoming news. Meanwhile, a blue-chip Wall |
Street firm has applied for a trademark for what it |
hopes will be a tool that will advise customers on stock |
selection.29 In practice, however, Briest observes that |
the banking industrys restrained approach reflects the |
one being taken across the financial services industry |
as a whole. The sector is relatively conservative in |
adopting new technological trends, he says. |
Risk management is another field where generative AI |
is seeing use as an advanced research tool that goes |
beyond its current rollout. |
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MIT Technology Review Insights |
05 |
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hen grappling with the challenge of |
adopting new technologies, |
companies often have to tackle the |
confluence of legacy technology and |
a tight labor market. |
Legacy technology |
Financial services companies, especially banks, were |
among the early adopters of IT decades ago. Choices |
made then, though, have long resisted further change. |
The most striking example of this phenomenon is that, |
as late as 2017, 43% of banking systems relied on |
a six-decade-old computer programming language, |
COBOL, which was also behind 80% of credit card |
transactions and 85% of ATM activity. |
Typically, COBOL drove large mainframe computers |
because it was the only option decades ago. Although |
such arrangements have provided substantial stability, |
they make it difficult to add new capabilities arising |
from more recent technological developments.30 |
COBOL encapsulates the broader legacy-technology |
deficit in the financial sector. Its a problem that |
encompasses old software and siloed data storage |
arrangements that have evolved to meet challenges |
across decades but are no longer fit for purpose. |
Two general |
challenges for new |
technology adoption |
According to an Accenture survey of large banks, even |
though the respondent pool consisted of companies |
interested in cloud usage, only 31% had moved more |
than half of their previous mainframe activity to the new |
platforms.31 A lot of banks maintain old IT systems, says |
Briest. Were hearing from technology companies about |
a lot of pilot projects starting and companies moving |
quite quickly to the next step, but this is going to take |
some time. Its an observation shared by Chia. Most |
financial services organizations have a lot of data that is |
usually poorly structured or even fragmented, he says. |
Despite this enduring challenge of legacy IT for many |
companies, the problem has been diminishing across |
the industry because of extensive digitalization in recent |
years. A lot of financial services firms have invested |
heavily in digital transformation, says Chia. Most have |
gained a certain capability in data management and |
theres already a level of fundamental readiness in terms |
of technology investment. |
One of them is RCBC, which was established in 1960. |
The past three years have been pivotal for our digital |
transformation, says Villanueva. The introduction and |
expansion of generative AI solutions will be smooth |
and easy. Meanwhile, new entrants do not have a |
technological deficit to overcome. Mileham says that |
More generally, companies have a big opportunity to |
use generative AI to accelerate the shift off some |
legacy applications that maybe it was just cost- |
prohibitive to consider previously. |
Michael Briest, Head of European Technology Research, UBS |
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MIT Technology Review Insights |
Betterment, as a cloud-native company, can deploy |
generative AI as broadly as it sees a use for it relatively |
quickly. Im confident that major cloud providers are |
going to be able to productize these capabilities and |
expose them to companies very efficiently, he says. |
Cont also says that he believes that financial companies |
are, overall, pretty ready to make use of generative AI. |
Even those who currently are not in such a state may |