Datasets:
sidhellman
/
clean_data.txt

Dataset card Data Studio Files
xet
Community
1
text
stringlengths
0
182
from the technology in the near term. In particular, the
consultancy argues that generative AI can generate
personalized investment recommendations, analyze
market data, and test different scenarios to propose
new trading strategies.8 Certainly, interest exists
for applying generative AI in all these areas. The
financial sector has been very quick to understand the
usefulness of these tools, says Cont.
With limited and at most partial exceptions, however,
the industry has not gone beyond experimentation in
such areas. Jason Napier, head of European banks
research at UBS, says that while later there will be
other, probably more important, deployments, a lot of
the potential of AI appears really nascent at this stage.
Rather than generative AI revolutionizing the industry
over the short to medium term, companies are focused
on using it to address a range of specific tasks that
typically involve the automation of low value-added
jobs that previously required humans to assess
unstructured information. Interest in doing more exists,
but the still experimental state of generative AI-
powered tools and, equally important, regulatory issues
stand in the way.
While later there will be
other, probably more
important, deployments,
a lot of the potential of AI
appears really nascent at
this stage.
Jason Napier, Head of European Banks
Research, UBS
10 MIT Technology Review Insights
03
03
T
o be useful, any new technology or tool must
solve a problem. So far, generative AI is being
applied to a range of specific tasks or
problems, rather than for the wholesale
design of operating models across entire
companies. This is the case across much of the
economy. McKinsey estimates that roughly three-
quarters of the value created by generative AI overall will
arise from just four areas: customer operations,
marketing and sales, software engineering, and research
and development.9
Cost cuts for now; income generation will
have to wait
Where financial services differ from other sectors is
that generative AI is largely not being used to drive
revenue. According to UBS research, so far the real
value being seen is from cutting costs. (see Figure 4).
Reality check:
Recent deployments
of generative AI
We will leverage on
generative AI to change
the anatomy of work,
including our internal
processes, by
automating typically
tedious tasks and
workflows.
Lito Villanueva, Chief Innovations Officer
and Executive Vice President, RCBC
Figure 4: Expected impact of generative AI in the financial sector
UBS analysts say generative AIs main opportunity for the financial sector is lower costs, as staff expenses
represent a relatively high portion of total costs.
Source: Compiled by MIT Technology Review Insights, based on data from Will Generative AI deliver a generational transformation, UBS, 2023
Banks
Exchange & nancial business services
Fintech & payments
Insurance
Real estate
Wealth & asset managers
Revenues
Costs
Competition
Neutral
Increase
Neutral
Reduction
Increase
Neutral
Reduction
Reduction
Reduction
Reduction
Reduction
Reduction
Increase
Increase
Increase
Increase
Neutral
Increase
11
MIT Technology Review Insights
According to its assessments of a range of industries
(see Figure 5), the main impact of generative AI lies in