sidhellman/clean_data.txt · Datasets at Hugging Face

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cost cutting, rather than on income generation. This is
true in every part of the sector, including in banking,
wealth management, insurance, and payments.
These savings, in most cases, arise from using
technology to free human employees from the need to
analyze large amounts of often unstructured data and to
produce output in response to directions given in natural
language. We will leverage on generative AI to change
the anatomy of work, including our internal processes, by
automating typically tedious tasks and workflows, says
Lito Villanueva, chief innovations officer and executive
vice president at Rizal Commercial Banking Corporation
(RCBC), a Philippines-based bank. RCBC is not alone.
According to a Fortune article published in June 2023,
so-called generative AI is already helping to speed up
mundane tasks known to crush the spirit of junior Wall
Street employees, hedge funds sayfrom reviewing
reams of market research to writing basic code and
summarizing fund performance.10
Eyeing higher-value work
These innovations are not typically designed to reduce
employment levels so much as to give time for staff to
focus on higher-value work. Mileham notes that even
the limited applications deployed at Betterment so
far represent an unmitigated boon in the day-to-day
operations of the firm. There are efficiency benefits
across the board. The value is real, and we get a lot out
of it, he says.
Figure 5: General Impact of generative AI
Overall, UBS analysts see cost savings as the most likely outcome from advances in generative AI, based on
analysis of 31 sectors.
Source: Compiled by MIT Technology Review Insights, based on data from Will Generative AI deliver a generational transformation, UBS, 2023
Wealth & asset
managers
Autos
Banks
Fintech/
payments
Support services
Building/
construction
IT services
Transport
Insurance**
Software
Media
Chemicals
Oil & gas
Stock exchanges
Staples
Aerospace/defense
Real estate
Mining
Telecoms
Semiconductors
Technology hardware
Luxury goods
Medical devices
General retail
Food retail
Capital goods
Internet*
Leisure
Pharma
Steel
Utilities
Revenue potential
Cost saving potential
Competition risk
*Internet identied an increase in costs as well as greater revenue and competition potential.
**Insurance saw a negative risk to revenues as well as cost-saving potentials and risk of increased competition
12
MIT Technology Review Insights
Another potential improvement is that generative
AI applications may sometimes outperform people
when evaluating unstructured data. A University of
Chicago business school study, for example, found
that a generative AI tool could quickly and accurately
process the implications of bloated financial disclosure
information, which might seek to hide the truth through
verbiage.
11
In contrast, academic research into the ability of a
generative AI tool to help customer service operations
found that it increased average productivity in terms of
issue resolution per hour. However, it had the greatest
impact on novice and low-skilled workers, and minimal
impact on experienced and highly skilled workers.12 In
other words, it helped new employees get up to speed,
but was less useful to those who already knew the
ropes.
Uses of generative AI in the finance sector
Financial services firms have focused generative AI
deployment on several specific tasks that share the
kind of attributes described above.
Customer service: Chia speaks for many when he
notes a very strong use case for generative AI in
customer servicegoing 24/7 for customer service,
even to the extent of providing advice for customers.
Indeed, the academic research noted above on use

cost cutting, rather than on income generation. This is

true in every part of the sector, including in banking,

wealth management, insurance, and payments.

These savings, in most cases, arise from using

technology to free human employees from the need to

analyze large amounts of often unstructured data and to

produce output in response to directions given in natural

language. We will leverage on generative AI to change

the anatomy of work, including our internal processes, by

automating typically tedious tasks and workflows, says

Lito Villanueva, chief innovations officer and executive

vice president at Rizal Commercial Banking Corporation

(RCBC), a Philippines-based bank. RCBC is not alone.

According to a Fortune article published in June 2023,

so-called generative AI is already helping to speed up

mundane tasks known to crush the spirit of junior Wall

Street employees, hedge funds sayfrom reviewing

reams of market research to writing basic code and

summarizing fund performance.10

Eyeing higher-value work

These innovations are not typically designed to reduce

employment levels so much as to give time for staff to

focus on higher-value work. Mileham notes that even

the limited applications deployed at Betterment so

far represent an unmitigated boon in the day-to-day

operations of the firm. There are efficiency benefits

across the board. The value is real, and we get a lot out

of it, he says.

Figure 5: General Impact of generative AI

Overall, UBS analysts see cost savings as the most likely outcome from advances in generative AI, based on

analysis of 31 sectors.

Source: Compiled by MIT Technology Review Insights, based on data from Will Generative AI deliver a generational transformation, UBS, 2023

Wealth & asset

managers

Autos

Banks

Fintech/

payments

Support services

Building/

construction

IT services

Transport

Insurance**

Software

Media

Chemicals

Oil & gas

Stock exchanges

Staples

Aerospace/defense

Real estate

Mining

Telecoms

Semiconductors

Technology hardware

Luxury goods

Medical devices

General retail

Food retail

Capital goods

Internet*

Leisure

Pharma

Steel

Utilities

Revenue potential

Cost saving potential

Competition risk

*Internet identied an increase in costs as well as greater revenue and competition potential.

**Insurance saw a negative risk to revenues as well as cost-saving potentials and risk of increased competition

12

MIT Technology Review Insights

Another potential improvement is that generative

AI applications may sometimes outperform people

when evaluating unstructured data. A University of

Chicago business school study, for example, found

that a generative AI tool could quickly and accurately

process the implications of bloated financial disclosure

information, which might seek to hide the truth through

verbiage.

11

In contrast, academic research into the ability of a

generative AI tool to help customer service operations

found that it increased average productivity in terms of

issue resolution per hour. However, it had the greatest

impact on novice and low-skilled workers, and minimal

impact on experienced and highly skilled workers.12 In

other words, it helped new employees get up to speed,

but was less useful to those who already knew the

ropes.

Uses of generative AI in the finance sector

Financial services firms have focused generative AI

deployment on several specific tasks that share the

kind of attributes described above.

Customer service: Chia speaks for many when he

notes a very strong use case for generative AI in

customer servicegoing 24/7 for customer service,

even to the extent of providing advice for customers.

Indeed, the academic research noted above on use