The Financial Services Industry Leveraging AI
to Help in Fraud Management
What is AI?
Artificial Intelligence or machine learning is a simulation of human
intelligence and an application of technology that learns and works
on problem-solving issues just like humans. It is used to enhance
efficiency, effectiveness, and outcomes of any process or operation.
AI is simply the machine intelligence that mimics human intelligence
to understand and resolve problems arising in the operations of
different industries.
How AI is being used in the Financial Services Industry?
The financial services industry is a vulnerable industry with much to put
at the highest security possible. With a lot of data and money to secure
from the sophisticated frauds and hackers, it is challenging for the
financial services sector to not cope up with the upcoming trends in
technology when the frauds are using it to disrupt their business.
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For a better interface and to protect not just the banks and the whole sector but also the customers, it is crucial for the
financial services industry to adopt technology and digital platform such as AI to avoid fraudulent behavior.
Let’s see what’s causing the fraudulent behavior in the first place
There are smart people who do wish to break into the security of such sectors. How do they do it is simply something
that is for another time but what is making them do it is simply the availability of such high technology standards
which are helping them to be better at it.
With overseas frauds, it is quite clear how fraudulent behavior has become easy for them with the help of technology
adopted by everyone. Also, the increasing usage of digital platforms for transactions by people is making it a strong
point for the frauds to take advantage of it.
But what we need here is to find such a tool/application that can break their level of technology and keep the data
and money secure and safe.
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This is where AI comes into view. AI is capable of expanding the existing models based on rules simultaneously
strengthen the human fraud analysts significantly. This helps in enhancing the accuracy of the derived results while
simultaneously offering efficiency and cost reduction.
AI helping in fraud management
AI helps in fraud management with the help of use cases that
are, however, a technical requirement for AI algorithms. Every
use case prioritizes the technical requirements includingmonitoring the transactions with the highest level of response
rate, error rates, precision explicability, training data availability,
quality, and ease of model building as compared to the other
uses cases such as the fraud investigation and reporting
With a standard and high-quality data analytics, AI tracks and provides the ones present with errors or the ones found
in an awkward position as per the AI algorithms.
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Using the right Use Case for each Fraud Case
There are different kinds of frauds attempted and carried out which demands different algorithms from AI to detect
and track them. So, AI uses different algorithms including knowledge graphics, supervised, and unsupervised learning,
etc. What the financial services do is, they use and match the AI algorithm to common use cases, for example, the
supervised learning algorithm dominates in the use case of transaction monitoring that demands exceptional
performance and accuracy. Similarly, the use case of reporting demands the visualization tools, and the clustering
algorithms are based on unsupervised learning.
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A peek into the financial services frauds
AI and machine learning (ML) is saving the day with better tools to
lead fraud management solutions in financial services.
Helping in high security and risk management, AI technologies
majorly provides a huge aid in the assessment and protection of
data, services, and transactions.
As cyber security is the prime requirement and demand for
customers due to the widespread use of digital platforms and
technology, online transactions require better protection and data
security from hackers and smart fraudsters.
The frauds have definitely taken a rise since digitization became a
normal and new way of transactions. With this increasing fraud, it is
quite challenging and difficult for the financial services sector to
protect itself and its customers.
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Moreover, as per a Juniper Research report, cybercrime currently costs the global economy approximately USD $600
billion (i.e. 0.8% of global GDP) annually, out of which online transaction fraud accounts for the biggest chunk – this
is expected to hit $25.6 billion by 2020.
Also, Ravi Shankar Prasad, India’s minister for information technology, mentioned that there were more than 25,800
cases of digital fraud in the country in 2017, resulting in the theft of nearly ₹1.8 billion rupees.
The financial services sector now aims not only on the financial risks mitigation but also aims at detecting fraud in
real-time.
The fraud strategists are seeking to attain more of a holistic view of the landscape of threat and risks in the financial
services sector for effective detection and deterrence. They are also moving forward to adopting a multi-layered
defense system for balancing the strategy. AI is helping the sector to work and gain a balance between robust
measures to counter the fraudulent behavior and offer a secure and positive customer experience
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How ML & AI Prevent Fraudulent Behavior
With a majority of cases coming up of fraud behavior, the majority
of financial institutions and banks are turning to advanced solutions
technology such as ML (machine learning) and AI (artificial
intelligence).
ML is the reason for the stir that occurred in the fraud detection
domain due to its high quality.
Learn how ML helps in fraud detection:
It has the ability to deal with a huge amount/large volume of data
present or collected from numerous sources.
It is capable of identifying and spotting the abnormal patterns and
links in the data, unlike humans.
It acts as the most viable tool for fraud detection due to its highquality outcomes that have high validity too.
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Fraud Detection Methods
The fraud detection methods are getting better with each passing
day and with more and more technology and digital adoption by the
financial services sector.
ML, if trained correctly has the ability to identify patterns and
consumer behavior.
ML is used as a method to protect companies from the frauds
happening at the internal level by studying and accessing data
present within the organization.
ML has the ability to even read and mark any kind of irregularity in
an individual's system or data differing from the day-to-day work
and the exposure of data to unauthorized people.
When ML collaborates with AI, it gets the ability to run over the
algorithms study or the only method of detecting fraud to the smart
methods one.
AI helps the machines to be programmed to learn on their own
without any supervision to track the transaction patterns and filter
out the ones which do not match the regular or normal pattern in
such a way that they can be provided support in real-time.
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AI & ML as the aiding factor for the BFSI
With the help of AI along with ML, the BFSI industry has gained a lot
of profit not just in preventing fraudulent behavior but also
protecting its customers and gaining their respect and value.
Now, both the advanced solutions technology not only helps in the
prevention of frauds and protection of data and money of the
people, but it has also led it towards growth in the market with a
boosting revenue along with valuable insights into the customer
behavior, their reference, and expectation from the companies.
Understanding customers and fulfilling their expectations is the
prime need of every business and with this, the BFSI sector is going
towards greater success.
Also, as per a National Business Research Institute survey, over
32% of financial institutions globally use AI for predictive
analysis.
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Also, as per a National Business Research Institute survey, over 32% of financial institutions globally use AI for
predictive analysis.
PwC’s Global Economic Crime and Fraud Survey states that 49% of global organizations have experienced financial
crime in the past two years. As global transactions over digital channels are increasing, the possibility of electronic
fraud is also increasing with it.
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