sidhellman/clean_data.txt · Datasets at Hugging Face

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of the technology in customer service found that it
increased the number of issues solved per hour by 14%,
improved client sentiment, and reduced requests for
managerial intervention.
13
The most common customer servicerelated innovation
is the creation of chatbots for either direct use by
customers or company service agents. These tools
represent not so much a new development as an
evolution. At Betterment, for example, a chatbot based
on predictive AI has already reduced the workload on
our customer service team drastically, Mileham says,
even before the integration of generative AI. That step
is being considered carefully.
The addition of generative AI elements to chatbots
brings obvious benefits. These include interaction
in natural language and the possible integration of
potentially huge repositories of unstructured data into
the tools knowledge base. Accordingly, Villanueva says
that a generative AIbased chatbot is one of RCBCs
leading digital priorities. Thats because it enables
real-time quality customer service interactions and
contributes to a seamless customer experience by
facilitating the filing of complaints, accommodation of
client requests, and collection of relevant customer data.
RCBC is not alone. In May 2023, tech company Kasisto
launched KAI-GPT, the first banking-specific LLM,
and the initial program built to use KAI-GPT was KAI
Answers, which aids employees in replying to customer
queries.
14 Meanwhile, various banks have announced
development of generative AI-powered information
tools for the direct use of customers or customer
service agents.
15 Similarly, Cowbell Insurance has
launched MooGPT to provide answers to its customers
and agents.
16 Most of these tools appear designed
to improve customer-employee interactions rather
than replacing them, except in cases where the aim is
providing basic information.
This is intentional. Two considerations are at play.
First, notes Mileham, any integration of generative AI
into existing chatbots needs to be done safely. As of
yet, its not like youre going to be putting a generative
AI directly in front of customers and setting it free,
he says. Second, some financial services firms have
reported an increased need for human customer
service staff. Weve seen people wanting more human
interactions for retail transactions instead of fewer,
says Villanueva. As a result, the Philippines-based
As of yet, its not like youre going to be putting a
generative AI directly in front of customers and
setting it free.
John Mileham, Chief Technology Officer, Betterment
13
MIT Technology Review Insights
banks generative AI chatbots are being designed to
allow our talents to maximize their time and move
toward more highly specified customer concerns that
require more detailed and sensitive attention, he adds.
Fraud prevention and risk management: For some
years, financial services companies have been using
advanced technologies, including predictive AI, to
improve risk management and fraud prevention.
Generative AI will allow the sector to go further,
including through greater integration of unstructured
data into these efforts. Chia says that using such
information will allow companies to identify new
patterns and anomalies with associated risks at both
a micro levelsuch as the potential for an individual to
defaultand a broader onesuch as market trends.
More specifically, according to UBS research, reducing
fraud is key for the payments industry in general.
Visa and PayPal have both deployed generative AI to
prevent fraudulent transactions by blocking suspicious
ones.
17 More generally, fintechs such as Datavisor,
Feedzai, and Forter have all integrated generative AI
into their off-the-shelf solutions to reduce payment
fraud.
18 At the same time, the new technology allows
the sector to go beyond reinforcing existing anti-fraud
defences, says Villanueva. He adds that RCBC is
hoping to use it to engage customers more actively in
fraud prevention, through more targeted and effective
awareness and education campaigns.
Coding: The financial services industry is, in many
ways, a knowledge-based one. Michael Briest, head of
European technology research at UBS, notes that as a
sector, banks spend more as a percentage of revenues
on IT than any other, and a lot of banks still do software
design and maintenance in house. Accordingly, ways
to improve the efficiency of such activities will interest
companies. If properly trained, a generative AI tool can
produce requested computer code as easily as others
can answer questions or generate pictures.
A leading U.S. bank has started using generative AI
tools to help its code developers.
19 It is not alone.

of the technology in customer service found that it

increased the number of issues solved per hour by 14%,

improved client sentiment, and reduced requests for

managerial intervention.

13

The most common customer servicerelated innovation

is the creation of chatbots for either direct use by

customers or company service agents. These tools

represent not so much a new development as an

evolution. At Betterment, for example, a chatbot based

on predictive AI has already reduced the workload on

our customer service team drastically, Mileham says,

even before the integration of generative AI. That step

is being considered carefully.

The addition of generative AI elements to chatbots

brings obvious benefits. These include interaction

in natural language and the possible integration of

potentially huge repositories of unstructured data into

the tools knowledge base. Accordingly, Villanueva says

that a generative AIbased chatbot is one of RCBCs

leading digital priorities. Thats because it enables

real-time quality customer service interactions and

contributes to a seamless customer experience by

facilitating the filing of complaints, accommodation of

client requests, and collection of relevant customer data.

RCBC is not alone. In May 2023, tech company Kasisto

launched KAI-GPT, the first banking-specific LLM,

and the initial program built to use KAI-GPT was KAI

Answers, which aids employees in replying to customer

queries.

14 Meanwhile, various banks have announced

development of generative AI-powered information

tools for the direct use of customers or customer

service agents.

15 Similarly, Cowbell Insurance has

launched MooGPT to provide answers to its customers

and agents.

16 Most of these tools appear designed

to improve customer-employee interactions rather

than replacing them, except in cases where the aim is

providing basic information.

This is intentional. Two considerations are at play.

First, notes Mileham, any integration of generative AI

into existing chatbots needs to be done safely. As of

yet, its not like youre going to be putting a generative

AI directly in front of customers and setting it free,

he says. Second, some financial services firms have

reported an increased need for human customer

service staff. Weve seen people wanting more human

interactions for retail transactions instead of fewer,

says Villanueva. As a result, the Philippines-based

As of yet, its not like youre going to be putting a

generative AI directly in front of customers and

setting it free.

John Mileham, Chief Technology Officer, Betterment

13

MIT Technology Review Insights

banks generative AI chatbots are being designed to

allow our talents to maximize their time and move

toward more highly specified customer concerns that

require more detailed and sensitive attention, he adds.

Fraud prevention and risk management: For some

years, financial services companies have been using

advanced technologies, including predictive AI, to

improve risk management and fraud prevention.

Generative AI will allow the sector to go further,

including through greater integration of unstructured

data into these efforts. Chia says that using such

information will allow companies to identify new

patterns and anomalies with associated risks at both

a micro levelsuch as the potential for an individual to

defaultand a broader onesuch as market trends.

More specifically, according to UBS research, reducing

fraud is key for the payments industry in general.

Visa and PayPal have both deployed generative AI to

prevent fraudulent transactions by blocking suspicious

ones.

17 More generally, fintechs such as Datavisor,

Feedzai, and Forter have all integrated generative AI

into their off-the-shelf solutions to reduce payment

fraud.

18 At the same time, the new technology allows

the sector to go beyond reinforcing existing anti-fraud

defences, says Villanueva. He adds that RCBC is

hoping to use it to engage customers more actively in

fraud prevention, through more targeted and effective

awareness and education campaigns.

Coding: The financial services industry is, in many

ways, a knowledge-based one. Michael Briest, head of

European technology research at UBS, notes that as a

sector, banks spend more as a percentage of revenues

on IT than any other, and a lot of banks still do software

design and maintenance in house. Accordingly, ways

to improve the efficiency of such activities will interest

companies. If properly trained, a generative AI tool can

produce requested computer code as easily as others

can answer questions or generate pictures.

A leading U.S. bank has started using generative AI

tools to help its code developers.

19 It is not alone.