Critical Analysis of Artificiall intelligence in Financial Services Articles

Hi there,I want someone write analysis around two pages about these two articles. Analysis should include:What is the central issue dealt with in the paper? Provide a critique of the research. What is good or bad about the manuscript? Are the findings useful? Is the claim of the research question or hypotheses justified? What assumptions have been made (e.g. about the generalisability of the results)? To what extent are the central insights grounded in evidence? What is the evidence supporting these assumptions? What suggestions would you make to enhance the study or would you design it differently? Is there any related research or current event that helps to explain or refute the findings in the manuscript? (with proper citations and bibliography) In what ways is this article similar or different from others you might have read? Article 1:http://www.thehindubusinessline.com/opinion/exit-a…
rise_of_the_robots.pdf

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Rise of the
robots
Robotic process automation can
cut costs for financial services
firms by up to 75 percent.
kpmg.com
About the contributors
Bill Cline: Bill was recently named KPMG’s Strategic Capabilities and Alliances leader to
drive innovation across the Financial Services Advisory practice. With more than 30 years
working in the world’s financial markets, he has designed and introduced some of the
most impactful tools in capital markets, including the first digital trading systems, the first
commercial ticker plants, new methods of market data delivery and services, and the
growth of global sourcing and asset-driven capabilities in professional services.
Michael Henry: Mike is a principal in KPMG’s Advisory practice based in New York
City. In his 25-year career, he has helped financial services organizations transform to
improve performance. He has lived and worked abroad for more than 15 years, including
6 years in Europe and 9 years in Asia, delivering value to local and global clients in
banking, capital markets, and insurance.
Cliff Justice: Cliff is a principal in KPMG’s Innovation & Enterprise Solutions team,
leading the firm’s Cognitive Automation initiatives. He is a leading authority on global
service delivery model design and sourcing, with more than 25 years of experience
in operations, technology, outsourcing, offshoring, and business transformation.
Cliff has been an early leader in applying intelligent automation, robotics, and cognitive
technologies to business operations and services.
Contents
Introduction
2
Embracing technology and transformation
3
–– New disruptors and their high-tech capabilities
4
“Offshoring” no longer a solution
6
Benefits of ‘bots
7
–– Case study: Upping the bet on ‘bots
8
So what’s the holdup?
9
Nine steps for RPA innovation
10
–– Presenting to senior management or the board
11
–– Case study: Integrating RPA gradually
11
Using RPA in the client onboarding process
12
Impact on employees – and getting their buy-in
14
What lies ahead?
16
About KPMG
17
Contact us
18
Introduction
“In the next 15 years, it’s likely that 45 percent, and
maybe up to 75 percent, of existing offshore jobs in the
financial services sector will be performed by robots,1
or more precisely, robotic process automation (RPA),”
stated Cliff Justice, KPMG LLP (KPMG) Advisory principal.
“That should translate into enormous costs savings of
up to 75 percent2 for firms
that get on board.”
into their operations will not only find themselves at a
huge disadvantage, they likely will be as obsolete as the
employees that the robots have replaced,” said Justice.
Powerful words… provocative predictions…
In this paper, we take a look at what’s behind these bold
forecasts. We also explore
some of the benefits that
robots and AI/cognitive
automation technology
holds, including the ability
to digest and analyze huge
amounts of data. Finally,
we present nine factors
you should consider before
implementing an RPA
strategy.
“Success in today’s…financial
markets requires unprecedented
levels of speed, accuracy, and
cost efficiency beyond what a
human workforce can provide.”
And the potential benefits
don’t stop there. ”Success
in today’s complex global
financial markets requires
unprecedented levels of
speed, accuracy, and cost
efficiency beyond what
a human workforce can
provide,” observed Bill Cline,
We strongly believe that
KPMG Advisory principal.
—Bill Cline, KPMG Advisory principal robotic and cognitive
“That’s why firms in the
automation is the wave of
financial services markets
are increasingly turning to RPA and artificial intelligence
the future for global capital markets and financial services
(AI)-driven cognitive automation to transform their
firms. It’s crucial that you explore what you can do today to
businesses.”
position yourself for success tomorrow.
As technology improves, robots will able to do more
sophisticated tasks faster and more efficiently than
human workers. “Businesses that don’t start taking
steps now to integrate robotics and cognitive automation
We welcome your feedback on this topic and invite you to
contact our specialists for further discussion.
1
e are defining a robot as a technology or technology-enabled process that can perform functions
W
previously only performed by humans.
2
obotic process automation: The new IT job killer, InfoWorld, March 23, 2015; Framing a Constitution
R
for Robotistan: Racing with the Machine of Robotic Automation, Charles Sutherland, HfS Research,
October 2013
Embracing technology
and transformation
“Although capital markets have been expanding globally,”
observed Cline, “there’s been an increase in competition from
traditional competitors as well as from disruptive new entrants
into financial services. And some of these new entrants are
much more nimble and tech savvy than established firms with
legacy infrastructure to support.” (See sidebar on page 3,
“New disruptors and their high tech capabilities” ).
“This increased competition, together with the
ever-mounting pressure to reduce costs means that it’s not
just a matter of working harder any longer, it’s a matter of
working smarter,” Cline said.
He noted that huge sums of money have been spent
to make front-office trading faster through the use of
AI-generated algorithms. “These resources will now
be focused on the middle- and back-office because
sophisticated AI and cognitive automation programs will be
available to do this work,” he stated. “Trying to cut costs
in middle- and back-office operations by ‘labor arbitrage,’
that is, offshoring the work to lower cost countries, will no
longer cut it.” (See Figure 1)
Figure 1: Benefits of labor arbitrage vs labor automation
The chart below compares the characteristics and benefits of labor arbitrage and labor automation.
Labor arbitrage
characteristics
15%–30%
Labor automation
characteristics
40%–75%
cost takeout
Cost takeout for relevant
functions
Model is scalable to the extent
that you can scale labor.
Model is scalable and is largely
independent of labor growth.
Custom/complex, legacy;
“Your mess for less.”
Transformative –
new way of doing business
Access to low cost labor
necessary to provide
continuous value
Access to “rocket scientists”
who can codify manual
processes
Revenue/profit
correlated to people
Revenue/profit
correlated to people
Source: Bots in the Back Office: The Coming Wave of Digital Labor, KPMG, 2015
Rise of the robots
3
New disruptors
and their hightech capabilities
Here’s a quick look at some of
the new entrants into the fintech
field and the high-tech skills
they possess.3 This should put
financial services firms on notice
regarding the types of capabilities
they may need to develop or
acquire in the future:
Investment banks, exchanges, clearing organizations, and others
are increasingly recognizing the power of technology and the
benefits of transforming their businesses. (See Figure 2)
Accordingly, many of them have begun to incorporate highly
automated IT- and AI-driven process innovations into their
operations.
Figure 2. How capital markets firms can benefit from
technology
Digitalization
Falling cost of computing
–– Cinnobar: This 230-person
firm has developed a
sophisticated multiasset,
high volume, global trading
platform.
Areas of
fintech
–– eToro: An online social
trading and networking tool,
eToro enables individuals to
discuss investment issues,
trade, invest, learn, and share
knowledge.
–– Metamako: The firm builds
smart, super-fast (i.e., latency
sensitive) trading networks
for exchanges and the trading
community.
–– Robinhood: This zerocommission stock brokerage
platform allows traders to get the
best possible trade execution on
purchases and sales across all
stock exchanges.
–– Magna: KPMG’s proprietary
tool allows firms to
proactively monitor and detect
unauthorized trading activity
in real time, flags abnormal
or risky behavior, and helps
investigate and resolve
potential risks.
Cost reduction
Technology innovation
Ubiquitous data
Changing customer behavior
Source: The Perfect Storm of Technology and Capital
Markets: The Modern History of FinTech. KPMG, 2015
For example, Cline noted that industry spending on speed
and automation initially was focused primarily on trading
infrastructure and data; middle- and back-office functions
typically used economies of scale and offshoring as a way to
reduce costs. (See page 6, “Offshoring” no longer a solution.)
“A drastically new approach is needed,” said Justice. “We
believe that the industry as a whole must move more quickly
towards adopting RPA and AI, especially in light of the
increasingly complex regulatory intensive environment.”
–– Estimize: This open, crowdsourced, financial estimates
platform aggregates
fundamental estimates from
buy-side and sell-side analysts,
private investors, and students.
3
dapted from The 50 Best FinTech Innovators, KPMG Australia, in partnership with the
A
Financial Services Council and Australian Wealth Investments
And yet, most financial services firms have done little or nothing in the
way of integrating RPA into their business processes. A recent study
found that more than 40 percent of capital markets respondents weren’t
using RPA at all, and another 24 percent are just talking about it. Only 12
percent were using RPA, and then only sparingly. (See Figure 3)
Figure 3 – RPA has a long way to go
We and/or our
service providers
use it in production
sparingly.
We and/or our
service providers
are piloting RPA.
12%
21%
43%
I don’t think
it’s anywhere.
24%
We and/or our service
providers are talking
about RPA.
Source: “Ideals of As-a-Services” Study, HfS Research 2015
Sample: Total = 716; enterprise buyers = 178; advisers/consultants = 176;
service providers = 372
“It’s really pretty simple,” stated Justice. “We see significant
changes on the horizon in the financial services space. Firms that
either resist those changes or are too slow to adapt risk being
rendered irrelevant by disruptive forces—or traditional competitors
that have adapted more quickly—in very short order.”
“Firms that…resist those
changes or are too slow to
adapt risk being rendered
irrelevant.”
—Cliff Justice
KPMG Advisory principal
Rise of the robots
5
“Offshoring” no longer
a solution
For more than two decades, a key strategy for capital markets firms to cut costs in middle- and back-office operations
was to offshore the work to countries like China, India, and Philippines. The savings primarily resulted from the lower
wages they could pay employees there as compared to major money centers. As wages and the standards of living in
China and India rose, countries like Vietnam, Mauritius, and some Central and Latin American countries became popular
offshoring destinations.4
This so-called labor arbitrage strategy—which was more about
cost-cutting than boosting efficiency or any long-term strategic
thinking—worked for many years. But, according to Cline, the
offshoring business model is obsolete for several reasons:5,6
–– Shrinking gap in labor costs: Wages in countries outside
of the United States have risen, sometimes sharply,
while domestic wages have remained stagnant.
–– Political/social backlash against offshoring: This backlash,
along with tax factors and increased management
overhead expenses, is making offshoring a less
attractive option for U.S. companies.
–– Increasing globalization and fewer employees: U.S. firms
are competing with businesses from around the world
for a shrinking number of employees. This is leading to
higher labor costs abroad, especially for skilled workers.
–– Political instability, labor unrest, and other increased
risks: The United States remains one of the lowest risk
countries in which to operate.
»» – What’s more, as the use of RPA increases,
countries with economic dependencies on
outsourcing may start incurring significant job losses,
potentially leading to increased geopolitical risk and
unrest there.
–– Turnover: Companies are finding it increasingly difficult
to attract and retain foreign workers, especially skilled
ones. This tends to lead to higher costs for either
keeping skilled employees or retraining new ones.
»» Firms that take the option of hiring less skilled workers
typically find that a host of other problems arise (e.g.,
reduced quality, productivity).
RPA may be the final nail in the coffin for labor arbitrage.
“RPA has the potential to displace offshore clerical work
in the same way machines displaced manual work in
the 20th century,” observed Michael Henry, principal,
Advisory, KPMG. “In 1870, 70 – 80 percent of the U.S.
population was employed in agriculture; now it’s less
than 2 percent. RPA means the end of offshoring as we
know it.”
“RPA means the end of
offshoring as we know it.”
4
here in the World? Business Process Outsourcing and Shared Service Location Index,
W
Cushman & Wakefield, 2015
5
Labor Costs – Assess Costs Everywhere, State Department of Commerce, July 2015
6
U.S. Firms Eyeing Benefits of Onshoring, CFO, 11/23/2015
—Michael Henry
KPMG Advisory principal
Benefits of ‘bots
“Capital market firms that continue to employ labor
arbitrage are missing the boat in terms of the benefits
they’d derive by using RPA and AI,” Justice stated.
“What’s more, for the most part, firms that claim they’ve
‘automated’ have not really transformed their operations or
processes. Their people are still doing most of the work;
they’ve only made it marginally more efficient by using
better work flow tools.”
This approach is no longer sustainable in light of the
new RPA and “big data” technologies that are storming
the industry, and the business challenges coming from
disruptive new entrants. RPA and cognitive automation
strategies can drive cost reduction and operational
improvement well beyond anything that can
be attained with “cubicle farms,” regardless of
location.
Specifically, they can help firms:
–– Improve quality as human workers increasingly focus on
higher-value tasks and exceptions.
–– Improve speed of operations.
–– Apply data analytics to evaluate “big data.” This can be
invaluable in cleansing, standardizing, and analyzing data
across the enterprise. For example, it can include:
»» Determining P&L by enterprise, business unit, etc.
»» Meeting regulatory requirements (e.g., Know Your
Customer [KYC], Anti-Money Laundering [AML], FATCA).
–– Connect the dots in analyzing global trading, accounting,
controls, and risk management in real time.
“Machines can do many tasks
better, cheaper, and faster.”
–– Improve accuracy as a result of reduced
human error.
»» Example: An automated process can factor in
thousands of validation and due diligence rules when
analyzing a single Foreign Account Tax Compliance
Act (FATCA) form far more quickly and with fewer
mistakes than a human workforce.
—Cliff Justice
To put it succinctly, “machines can do many tasks better,
cheaper, and faster,” stated Justice. “While firms have
long been aware of the uses and benefits of automation,
advancements in robot technology and programming,
combined with falling costs, have made the use of ‘bots more
practical for many businesses.”
Rise of the robots
7
Case study:
Upping the bet
on ‘bots
For one financial services firm,
robots have proven ideal in
back- and middle office centers,
performing high-volume,
rules-based work. At a recent
conference, representatives
from Australia and New Zealand
Banking Group Limited (ANZ),
Australia’s fourth largest bank,
discussed how they have been
able to successfully integrate
robots and robotic software into
their operations.
They emphasized that ANZ
started off slowly at first, placing
a single software robot into its
lending operations. But now the
bank uses ‘bots in its finance,
human resources, payments
and mortgage processing
departments as well. It was
noted that in the payments
area, the number of human
employees has decreased from
40 to 2.8
For example, it’s been estimated that a software robot can cost around a tenth
of a full-time worker in the United States, United Kingdom or Australia, and
roughly a third of a full-time worker in India. And the marginal cost of additional
software robots is minimal.7
This goes a long way in explaining the exploding growth in the number of robots
projected to be ordered in the next several years. (See Figure 4)
Figure 4 – Number of robots ordered on the rise
As the chart below illustrates, the number of industrial
robots projected to be shipped worldwide by 2018 is more
than double the number shipped in 2013.
400,000
300,000
200,000
100,000
0
2013
2014
2015
2016
Note: 2015 and later are projections,
Source: International Federation of Robotics
7
Automation versus labour arbitrage, Martin Conboy, the outsourcing-guide.com, 6/9/15
8
ise of the machines as ANZ brings in robot workers to do the ‘boring’ jobs, Financial Review,
R
8/24/2015
So what’s the holdup?
If integrating robot technology into the financial services
markets and replacing human employees makes so much
sense and offers so many benefits, why isn’t it being
utilized more often?
What’s more, few financial services firms have a “culture
of innovation” that lends itself to taking the dramatic steps
needed to compete in the future and have to overcome an
ingrained resistance to change. (See Figure 5)
One reason is that RPA has only become advanced enough
to replace humans in the capital markets sectors in the
past two years; prior to that, the technology just wasn’t
quite there.
In a study of 38 banking, insurance, and investment firms,
only 21 percent had a dedicated chief innovation officer
(CINO):9
Thanks to enhanced AI and cognitive automation—
including natural language processing, machine learning,
and machine vision—together with better designed
robots, ‘bots stand ready to take their place in the financial
markets workforce.
Another, perhaps equally important, reason for the delay is
that many businesses simply are uncertain where and how
to begin to transition to robotics and cognitive automation
systems. Replacing or overhauling legacy systems can
take time and have significant costs associated with it,
depending on the size and complexity of the enterprise.
For example, we worked with a large investment bank that
recently spent over $100 million to implement work flow
tools allowing it to reengineer processes.
That’s a huge investment in technology, and it can be a
difficult pill for senior management or shareholders to
swallow. Regardless of how you try to justify the expense
and make the argument that it’s necessary for long-term
survival, it may be difficult to get executives, the board, or
shareholders to act upon it.
In addition, specifically with respect to RPA:
–– It takes a lot of time and effort to review and document
a firm’s current procedures and processes and convert
them into “instructions” that robots and/or AI software
programs need to follow. (See page 11. “Using RPA in
the client onboarding process”.)
–– There may be cultural resistance to change from
managers who are used to having a large number of
people to supervise (i.e., protecting one’s “turf”).
9
–– 45 percent did not have a dedicated CINO.
–– 24 percent had an executive with CINO duties but who
also wears other hats.
–– 10 percent had a person in the role but in a low-profile
way or without a title.
It’s likely that these firms will need to rely on third parties
to create the tools needed for game-changing technologies
such as robotics and cognitive automation.
Figure …
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