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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 |