sidhellman/clean_data.txt · Datasets at Hugging Face

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developments [the growing use of generative AI], it is
critical we do not lose sight of our duty to protect the
most vulnerable and to safeguard financial inclusion
and access.
41 A month earlier, the U.S. Consumer
Financial Protection Bureau warned that, with the
applications already being put in place, financial
institutions risk violating legal obligations, eroding
customer trust, and causing consumer harm when
deploying chatbot [sic] technology.
42 Meanwhile, the
U.S. Securities and Exchange Commission has invited
discussion on proposed new regulations regarding
AI-enabled tools.43
Accordingly, financial services companies are looking
to regulators for guidance on how they can use the
technology. We have to start the AI project with a
view toward being regulatorily compliant, says Chia.
There will be growing regulatory content so it is
imperative for financial services to be able to engage
regulators effectively on what kind of rules and
standards there should be. Mileham adds, Its going
to be helpful to see regulators looking at this seriously
and ensuring that all of the actors in these fields with
fiduciary responsibilities understand the depth of
those responsibilities.
0
21
MIT Technology Review Insights
07
07
T
he arrival of generative AI as a viable
technology is important news for the financial
services industry. Its application, however, will
for now be limited to specific uses where
other, cheaper technologies are not already
sufficient for requirements and where the weaknesses of
the technology do not put off executives and regulators.
The difficulty in providing a more detailed forecast is the
uncertainty in how todays failings might be overcome.
The strengths of generative AI shape its current
application. In particular, with the capacity to learn
from large amounts of unstructured data and to create
output of various kinds, it is already beginning to play
an important role in customer service support, fraud
prevention, risk management, code generation, and
unstructured data analysis. Its impact in these use
cases should not be underestimated simply because
the technology is not being deployed more widely.
As generative AI is rolled out further in these areas,
substantial cost savingsup to $340 billion annually
across the financial services industryare likely from
the shift in human employment away from repetitive,
low-value tasks toward more creative and profitable
ones. In that sense, it is no exaggeration to say, in
Milehams words, This is a big moment.
Compared to what might eventually be possible,
however, we are only scratching the surface at the
moment, says Briest. The use of generative AI in more
sensitive tasks closer to the core of financial service
business modelssuch as making decisions on, or
executing, investment strategy for clients or companies
themselvesremains some way off. Too many questions
hang over the technology itself for companies or
regulators to give it free rein any time soon. Villaneuva
also urges caution. As exciting as this technology is, we
must be wary before fully realizing the benefits, he says.
Conclusion: Valuable
tool, but yet to be fully
disruptive
Nevertheless, generative AI continues to evolve quickly,
and solutions to its drawbacks may rapidly emerge.
It is very likely, for example, that ways will be found
to reduce the number and extent of hallucinations,
although some errors appear to be inevitable.44 If such
problems do persist, the technology might still find
new uses in financial services, as long as the potential
drawbacks are fully understood by all parties. Well
have to figure out as a culture, and within the regulatory
regime, what that should mean, says Mileham. It might
be that people just get comfortable with the constraints
of AI and youre able to, with a straight face, disclose
to a customer that this thing is useful, but it is also
potentially flawed, so take it with a grain of salt.
As generative AI and societal attitudes inter-evolve,
financial services companies should reap the substantial,
if constrained, benefits of the new technology while
keeping an eye on where it might head.
The use of generative AI in
more sensitive tasks closer
to the core of financial
service business models
such as making decisions
on, or executing, investment
strategy for clients or
companies themselves
remains some way off.
22 MIT Technology Review Insights
1.

developments [the growing use of generative AI], it is

critical we do not lose sight of our duty to protect the

most vulnerable and to safeguard financial inclusion

and access.

41 A month earlier, the U.S. Consumer

Financial Protection Bureau warned that, with the

applications already being put in place, financial

institutions risk violating legal obligations, eroding

customer trust, and causing consumer harm when

deploying chatbot [sic] technology.

42 Meanwhile, the

U.S. Securities and Exchange Commission has invited

discussion on proposed new regulations regarding

AI-enabled tools.43

Accordingly, financial services companies are looking

to regulators for guidance on how they can use the

technology. We have to start the AI project with a

view toward being regulatorily compliant, says Chia.

There will be growing regulatory content so it is

imperative for financial services to be able to engage

regulators effectively on what kind of rules and

standards there should be. Mileham adds, Its going

to be helpful to see regulators looking at this seriously

and ensuring that all of the actors in these fields with

fiduciary responsibilities understand the depth of

those responsibilities.

0

21

MIT Technology Review Insights

07

T

he arrival of generative AI as a viable

technology is important news for the financial

services industry. Its application, however, will

for now be limited to specific uses where

other, cheaper technologies are not already

sufficient for requirements and where the weaknesses of

the technology do not put off executives and regulators.

The difficulty in providing a more detailed forecast is the

uncertainty in how todays failings might be overcome.

The strengths of generative AI shape its current

application. In particular, with the capacity to learn

from large amounts of unstructured data and to create

output of various kinds, it is already beginning to play

an important role in customer service support, fraud

prevention, risk management, code generation, and

unstructured data analysis. Its impact in these use

cases should not be underestimated simply because

the technology is not being deployed more widely.

As generative AI is rolled out further in these areas,

substantial cost savingsup to $340 billion annually

across the financial services industryare likely from

the shift in human employment away from repetitive,

low-value tasks toward more creative and profitable

ones. In that sense, it is no exaggeration to say, in

Milehams words, This is a big moment.

Compared to what might eventually be possible,

however, we are only scratching the surface at the

moment, says Briest. The use of generative AI in more

sensitive tasks closer to the core of financial service

business modelssuch as making decisions on, or

executing, investment strategy for clients or companies

themselvesremains some way off. Too many questions

hang over the technology itself for companies or

regulators to give it free rein any time soon. Villaneuva

also urges caution. As exciting as this technology is, we

must be wary before fully realizing the benefits, he says.

Conclusion: Valuable

tool, but yet to be fully

disruptive

Nevertheless, generative AI continues to evolve quickly,

and solutions to its drawbacks may rapidly emerge.

It is very likely, for example, that ways will be found

to reduce the number and extent of hallucinations,

although some errors appear to be inevitable.44 If such

problems do persist, the technology might still find

new uses in financial services, as long as the potential

drawbacks are fully understood by all parties. Well

have to figure out as a culture, and within the regulatory

regime, what that should mean, says Mileham. It might

be that people just get comfortable with the constraints

of AI and youre able to, with a straight face, disclose

to a customer that this thing is useful, but it is also

potentially flawed, so take it with a grain of salt.

As generative AI and societal attitudes inter-evolve,

financial services companies should reap the substantial,

if constrained, benefits of the new technology while

keeping an eye on where it might head.

The use of generative AI in

more sensitive tasks closer

to the core of financial

service business models

such as making decisions

on, or executing, investment

strategy for clients or

companies themselves

remains some way off.

22 MIT Technology Review Insights

1.