Artificial Intelligence is the buzzword. Everyone is speaking about it, irrespective of whether they are a scholar on the topic or not. But what must be considered is AI's deep-reaching implications and how it has the ability to transform the society for the better. In this article, we would look at how AI is currently being used in the banking industry to transform it for the better. It is important to note that while us commoners use the term Artificial Intelligence (AI) everywhere, in reality, it is a mixture of technologies like Machine Learning (ML), Robotic Process Automation (RPA), Predictive Analytics and not to mention, Artificial Intelligence (AI).

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The exploding use of AI in banking sector
Artificial Intelligence is the buzzword. Everyone is speaking about it, irrespective of whether
they are a scholar on the topic or not. But what must be considered is AI's deep-reaching
implications and how it has the ability to transform the society for the better. In this article,
we would look at how AI is currently being used in the banking industry to transform it for
the better. It is important to note that while us commoners use the term Artificial Intelligence
(AI) everywhere, in reality, it is a mixture of technologies like Machine Learning (ML),
Robotic Process Automation (RPA), Predictive Analytics and not to mention, Artificial
Intelligence (AI).
Before we dive into the application of AI in the banking industry, let us look into the
definition of each term related to Artificial Intelligence, to get a clearer understanding of each
term to appreciate their extensive usage in the banking industry.
A) Artificial Intelligence- In simple terms, Artificial Intelligence is the emulation of
human intelligence by computer systems. They can be broadly categorized into weak
and strong AI.
Weak Artificial Systems are those which are trained to perform a certain task and its
programming does not allow the AI to learn from its fallacies. The Strong AI or
Artificial General Intelligence (AGI), is generally associated with human intelligence
and it is responsible for the popular fear in the general population of losing out jobs to
increasingly efficient and smooth artificial intelligence.
B) Machine Learning- Machine Learning is an application of Artificial Intelligence and
as the name suggests, the algorithms enable the computers/machines to learn from its
mistakes and mold itself to solve increasingly complex scenarios and problems by
taking into account all of its previous data to provide an optimum solution. Machine
Learning largely relies on patterns in the data to identify and make better decisions, as
and when required.
C) Robotic Process Automation- To define in layman's terminologies, Robotic Process
Automation is the method of combining AI and Machine Learning to process data in
high volumes as well as automate repetitive tasks, thereby reducing the time required
and human efforts. RPA is largely divided into three categories-

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 Probots- These follow simple rules which are repeatable in nature to process high
volume data
 Knowbots- Bots that are trained to graze the internet to collate much-needed user-
specific information.
 Chatbots- These bots are interactive in nature and are being extensively used in
various industries as virtual agents to interact with customers.
Thus from the above pointers, one thing is pretty clear, banks and many other organizations
use AI and other complementary technologies to reduce time while increasing efficiency.
Source
Contrary to the global belief that AI with replacing humans, AI will work alongside humans
to make the world a better place to live in. The banking industry today has been increasingly
using AI in its day to day functions and it is only expected to rise from here on.
The Business Insider AI in banking report states that the front office and the middle office
have the largest capability of saving costs through the implementation of Artificial
Intelligence in banks.

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Source
The above facts in the images have been arrived at after analyzing the following financial
institutions/companies- Citi, JPMorgan Chase, U.S. Bank, Personetics, HSBC, Quantexa and
Capital One.
AI is benefitting all sectors of business and banking is no exception to this. Some of the
recent uses of AI in the banking industry are enumerated as follows-
i) Personal Assistants and Chatbots- In this era of digitization, companies need to not
only leverage mass digital marketing, but also customize their products and
services for each customer. AI helps in individual customization through the use
of chatbots and personal assistants. Customers can now not only choose a product
of their liking but also leverage these platforms for redressing grievances,
contacting customer support and writing reviews to name a few.
Mobile banking, another successful effect of digitization, has been integrated with
Artificial Intelligence to yield wonders for the banks.
Today's knowledgeable customer uses mobile banking a lot as it is easier, faster and
efficient. Thus, banks can get detailed information about their customers through
predictive analytics based on their mobile app usage and they can then focus their
attention on the products and services that are most liked.

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Source
ii) Backend automation using Artificial Intelligence- Customer data and critical image
documents (like Aadhar, Voter Card, Pan Card) can be processed extremely fast
using Artificial Intelligence and Machine Learning to yield valuable information
about the client(s). Robotic Process Automation can make this work easier by
extracting only the valuable lines of information from these documents and
analyzing them to create a complete profile of every customer the bank deals with,
ever.

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iii) Security- AI can be successfully implemented in the middle office to detect fraud and
money laundering. An Artificially Intelligent system can successfully detect these
anomalies and report them to the higher management in the blink of an eye. Better
fraud and money laundering activities detection will lead to better management of
financial resources within the bank thereby leading to not only greater profits but
it would also mean that more people would have access to the funds of the banks
(as loans) thus helping the economy as a whole.
iv) AI in ATMs- One of the most necessary places where Machine Learning and
Artificial Intelligence is the need of the hour. Real-time facial recognition
software supported by robust artificial intelligence and machine learning would
lead to lessening of the incidences relating to ATM vandalism. India has already
witnessed a lot of loss because of ATM thefts and vandalism and at times
surprisingly pests (rats) chewing away through wads of cash inside the ATM
storage locker!
v) Trading and Securities- Robotic Process Automation (RPA) is extremely useful in
trading and securities; an RPA could easily distinguish between the prices for the
purchase of securities between an investment manager and a broker and then
create an email message directed towards the broker on predetermined rules. RPA
can also streamline several processes where one would need to skim through rows
and columns of data to arrive at the correct financial decision.

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Source
vi) Portfolio Management- Machine Learning, equipped with years of data on the stock
market of various stock exchanges throughout the world are now able to construct
near-perfect portfolios that minimize the risk all the while aiming to maximize the
wealth over a period of time.
Challenges of implementation of AI
Any technology would have its fair share of challenges in implementation and AI is no
exception in this regard. AI without data would be akin to a human without a heart and a
brain. Also, the availability of the right data is another issue. Hence, there needs to be a
structured process for collecting customer data and later, cleaning, processing, and finally
analyzing the same to reveal the important insights that banks need so much. Then comes the
additional burden of the language barrier in India, with tens of different languages and

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hundreds of dialects spoken, the process of collecting regional data would be a herculean task
for sure. Banks from all over the country needs to come together to form a framework and a
structure so that these challenges become easier to face. AI has the potential to become a
trillion-dollar industry by the year 2035 and its explosive growth in the present times only
strengthens the statistics.
Source
In addition, government banks must also be willing to partake directly informing the
framework mentioned, so that the poorest of the poor in the economy benefit from these
technologies. After all, no development can really be termed as such if it is not inclusive.
References-
https://www.businessinsider.com/the-ai-in-banking-report-2019-6?IR=T
https://www.livemint.com/AI/v0Nd6Xkv0nINDG4wQ2JOvK/Artificial-Intelligence-in-
Indian-banking-Challenges-and-op.html