We are all consumers of financial services more or less. We have bank accounts, possibly life insurance, some of us have credit cards, some of us have fixed deposits, some of us may be doing share trading and investment, some of us are borrowers of loans. These are all financial services. Financial Technology or FinTech is a way of delivering or improving the delivery of financial services using technology and innovation. The use of smartphones and internet to improve the services in banking, investing, lending and borrowing etc are examples of technologies aiming to make financial services more accessible to the people. The use of Artificial intelligence, Machine learning, Blockchain, Cryptocurrency etc are redefining the way we are used to receiving financial services. FinTech is an emerging industry. Startups, established financial institutions as well as technology companies are disrupting this space to replace or enhance the usage of currently existing financial services. In this video we will restrict ourselves to the usage of AI in FinTech. We will learn about different areas where FinTech is already serving a great deal. We will learn about the areas where we look forward to seeing more disruptions and innovations to make financial services more secure and accessible to the general public.

1. AI
in
FinTech
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AI
in
FinTech

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What is FinTech?
Financial Technology or FinTech is a
way of delivering or improving the
delivery of financial services using
technology and innovation.

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❖ The usage of AI in FinTech.
❖ Areas where FinTech is
already serving a great deal.
❖ Look forward
Scope of this video

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Cyber-security and FinTech
On one side we have easy and cost
effective availability of mobile internet
and smartphones. On the other hand
companies are going online
increasingly.

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Cyber-security and FinTech
In order to make the services more
convenient and reach out to more and
more customers financial companies
are adapting to technology rapidly.
What is essentially following this is the
availability of an overwhelming amount
of data personal, financial data online.

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Cyber-security and FinTech
Personal,
Financial Data
Bad-boy

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Cyber-security and FinTech
Counter bad AI with good AI.
AI algorithms may be used extensively
to predict vulnerability for users and
companies in the fintech space.
Blockchain technology may be a
solution to bring in strict security in
financial services.

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Claims management
❖ Detect fraud
❖ Discover new cases of fraud
❖ Speed up processing time and cost
❖ Speed up settlement
❖ Enhance customer experience

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Credit Risk Analysis
❖ What is credit risk?
❖ Role of AI in credit risk analysis
Classification models or Artificial Neural
Network (ANN) are trained on historical
client data to build credit risk analyser to
assess client risk profile.

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Churn prediction
Another usage of AI in Fintech (for that matter in any
customer serving company) is going to be controlling
the churn rate of customers

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Automated customer support
Customers facing systems such
as chatbots or voice systems can
deliver human-like customer
service or expert advice
experience at a low cost. With
extensive research and
development in NLP or natural
language processing, over the
time, chatbots can evolve to be
personal finance assistance.

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Insurance management
AI will help insurance
companies automate
the underwriting
process.

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Finance forecasting
With a huge amount of data
availability to take into
consideration for many
internal and external
parameters and by applying
them to train AI models, more
accurate predictions will be
possible in finance for
companies. These models will
be free from human biases
and be more realistic.

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Algorithmic trading
Who doesn’t want to get hold
of that AI algorithm that will
predict the stock market
accurately?

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Sentiment analysis
Sentiment analysis can
be used for due diligence
about companies and
managers using financial
reviews.
NLP techniques quickly
pulls out the key topics
that are of most interest
to the firm.

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Valuation model
The model can quickly
calculate the valuation of
an asset using data
points around the asset
and historical examples.
The model learns which
weights to assign to each
data point by using
historical data.

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Fighting against money laundering
Artificial neural networks (ANN) and ML algorithms consistently
outperform any traditional statistical method in detecting
suspicious events.

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Computer vision and surveillance
According to the FBI, in the
United States Federal Reserve
system banks alone are
targeted by nearly 3,000
robberies every year.
Computer vision-based
applications can be used to
enhance the security and
surveillance systems

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#HappyLearning
#BeCareerReady
There’s a great deal of work artificial intelligence is
doing in the FinTech space. There are many more
undiscovered areas where AI is going to play a key
role in the future. We look forward to more exciting
disruption happening in this space.