As global technology has evolved over the years, we have switched from television to the Internet, and today we are slowly and gradually adopting artificial intelligence.

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5 Ways AI is Transforming the Finance
Industry
Usm systems
Oct 23 · 7 min read
As global technology has evolved over the years, we have switched from television to the
Internet, and today we are slowly and gradually adopting artificial intelligence. The term
AI was first coined in 1956 by John McCarthy. It covers a lot of key issues, from the
process automation of robotics to the actual process of robotics. Because of the amount
of data these companies are dealing with, it is very popular among large companies
today. Increasing demand for understanding data models has led to an increase in
demand for AI. AI processes are more efficient at identifying data models than humans,
which can be beneficial for companies to understand and gain insight into their target
audiences. Thousands of companies around the world see AI as the next big thing for the
finance industry.
https://www.gatewaytechnolabs.se
There are basically two types of AI -
Weak AI
Weak AI can also be described as narrow AI, a system that is only set up to fulfill or fulfill
a specific task. It is designed to help solve specific problems. Weak AI acts according to

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the stipulated rules and adheres to it. It does not exceed the stipulated rules. It focuses
only on narrow tasks and does its best. Weak AI, like humans, is capable of all cognitive
functions and is no different from the human mind. Although it is not defined as general
intelligence, it is designed to act wisely towards the fulfillment of narrow tasks assigned
to it.
The best example of weak AI is Apple’s Siri, which is managed by a substantial database
of the Internet. It looks very intelligent, mainly because of the interactions it can hold
with humans. Siri is also known for witty remarks, but in reality, it works in a predefined
manner. When the system engages in conversations, “narrowness” is witnessed, it is not
designed to respond properly.
The same is true of robots used in manufacturing companies. When customers and
clients ask questions they respond very appropriately. The responses are accurate and
sometimes very witty. AI is capable of handling very complex situations in nature. But
their intelligence level system is limited to providing solutions to programmed problems,
something beyond that.
Strong AI
A strong AI, also known as a full AI, has a much bigger potential than a weak AI. It has
artificial intelligence, huge capabilities, and functionality. It mimics the human brain
extensively. It is so powerful that the actions of the system are exactly equal to the
actions and decisions of man. It also has an awareness of power and consciousness.
Strong AI is actually a process very similar to the human mind. Artificial intelligence
operates in every aspect with extraordinary ability, as the human mind. Beliefs,
cognitive states, and perceptions found only in humans are programmed in robust AI.
However, there is difficulty in defining intelligence accurately. As far as strong AI is
concerned, determining success or setting boundaries for intelligence is nearly
impossible or difficult. This is why weaker AI is better, mainly because of its ability to
perform assigned tasks with optimum efficiency. Weak AI does not have to be full of
intelligence that focuses on completing a specific task assigned to it. Therefore, it can be
divided into smaller processes.

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Artificial intelligence is the intelligence shown by machines, not by humans. Devices that
use their cognitive functions detect or solve problems similar to humans, or in most
cases, better. It was able to create a significant impact by doing what is deemed
impossible.
5 Ways to Look at the Finance Industry
1. Risk assessment:
Since the basis of AI is learning from past data; It is natural for AI to succeed in the
financial services domain, where bookkeeping and records are second nature to the
business. Let’s take the example of credit cards. Today, we use a credit score as a way to
determine who is and isn’t entitled to a credit card. However, categorizing people as the
haves and the have-nots is not always effective for business. Instead, data about each
person’s debt repayment habits, the number of loans currently active, the number of
existing credit cards, etc. can be used to customize the interest rate on a card, which
makes more sense to the financial institution offering it. Now, take a minute to think
about what system is capable of bringing the solution through thousands of personal
financial records- a machine that has learned! This is where the AI comes in. Because it
is data-driven and data-driven, scanning through these records gives AI the ability to
recommend historical loan and credit offerings.
AI and ML are taking the place of the human analyst very fast because bugs involved in
human selection can cost millions. AI is built on machine learning, which learns over
time, with little chance of error and extensive analysis of data; AI has set up an
automation where needed, intelligent analytical and clear thinking. Chatbots have
proven themselves to be a powerful tool for customer satisfaction and help companies
save unparalleled resources, time and money. Now, returning to Facebook’s efforts in
designing and developing bots to negotiate the way humans do, let’s explore the
possibilities of making this research a success. This new technology will not only change
the way we do business, but also non-commercial activities. Fixing meeting time in the
example of non-commercial activity. Bots can fix meetings by focusing on the availability
of everyone involved.
2. Fraud detection and management:

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Every business aims to minimize the risks around it. The same applies to a financial
institution. The loan that the bank gives you is basically someone else’s money, which is
why you get dividends on interest and investments on deposits. Banks and financial
institutions take fraud very seriously. AI is on top when it comes to security and fraud
detection. It can use past cost behavior on different transaction tools to highlight odd
behavior, such as using the card from another country only a few hours after using it or
attempting to withdraw unusual money into the account. It contains the question.
Another striking feature of fraud detection using AI is that the system has no desires
about learning. If it raises the red flag for a simple transaction and the human corrects it,
the system can learn from experience and make more sophisticated decisions about
what is considered fraud and what cannot.
3. Financial Advisory Services:
According to the PWC report, we can look forward to more robot-advisors. As pressure
on financial institutions to reduce their commission rates on personal investments,
machines and humans can work for a single down payment. Another field that is
emerging is Bionic Advisory, which combines machine calculations and human insight
and offers far more efficient options than their individual components offer.
Collaboration is key. It is not enough to see a machine as an accessory, or at the other
end, to be ignorant. A wonderful balance and the ability to see AI as a component in
decision-making is as important as the human perspective, the future of financial
decision-making.
4. Trading:
Investment companies rely on computers and data scientists to determine future models
in the market. As a domain, business and investment depend on the ability to accurately
predict the future. Machines are great at this because they can crunch huge amounts of
data in a short time. Machines can also be taught to observe patterns in past data and
how to replicate these patterns in the future. Although data such as the financial crisis of
2008 may be in the data, it can teach a machine to study data to find ‘triggers’ for these
disorders, and also plan for the future. What’s more, depending on personal risk
appetite, AI can suggest portfolio solutions meet individual demand. So a person with a
high-risk appetite can calculate AI for decisions about when to buy, hold and sell the

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stock. Those with low-risk appetites can receive warnings when the market is about to
fall and when to invest or move in the market.
5. Managing Finance:
In a well-connected and physical world, financial management is a challenging task for
many of us, and if we look further into the future, we can see AI services helping us
manage our finances. PFM (Personal Financial Management) is one of the recent
developments on the AI-based wallet. WalletStart, a San Francisco-based startup, uses AI
to create algorithms to help users make better decisions about themselves while
spending money. The idea behind the wallet is simple, it collects all the data from your
web footprint and creates your cost graph. Advocates of privacy breaches on the Internet
may find this offensive, but, in the future, the same may be the case. Therefore, it should
be the preferred personal financial management to save time from making long
spreadsheets or writing on paper. From a small-scale investment to a large-scale
investment AI can be the watchdog of the future for financial management.
Without a doubt, AI is the future of the finance industry. As it takes progressive steps
towards simplifying the financial processes for customers, it is going to replace human
beings very soon and provide faster and more efficient solutions. Bots are gradually
evolving as innovations are taking place in the field of AI. Companies that see this as a
long-term cost-cutting investment are making huge investments. This helps companies
save money on hiring and preventing human error in the process.
Although the pace at which it is progressing to develop the finance sector is still in the
early stages, it can be well anticipated that the opportunities will lead to small risks,
smart trading and top-tier customer experience.
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