Top data science use cases in banking - Phil Supinski
Top Data Science Use
Cases in Banking
P R E S E N T E D B Y P H I L S U P I N S K I
Using data science in the banking industry is more
than a trend, it has become a necessity to keep up
with the competition. Banks have to realize that big
data technologies can help them focus their resources
efficiently, make smarter decisions, and improve
Machine learning is crucial for effective detection and prevention and
fraud involving credit cards, accounting, insurance, and more.
Proactive fraud detection in banking is essential for providing security
to consumers and employees. The sooner a bank detects fraud, the
faster it can restrict account activity to minimize loses. By
implementing a series of fraud detection schemes banks can achieve
necessary protection and avoid significant loses.
Managing customer data
Banks are obligated to collect, analyze and store massive amounts of data.
But rather than viewing this as just a compliance exercise, machine learning
and data science tools can transform this into a possibility to learn more
about their clients to drive new revenue opportunities.
Nowadays, digital banking is becoming more popular and widely used. This
creates terabytes of customer data, thus the first step of data scientists team
is to isolate truly relevant data, thus the first step of data scientist tea is to
isolate truly relevant data. After that, being armed with information about
customer behaviors, interactions, and preferences, data specialists with the
help of accurate machine learning models can unlock new revenue
opportunities for banks by isolating and processing only this most relevant
clients’ information to improve business decision-making.
Risk modeling for
Risk modeling is a high priority for
investment banks, as it helps to regulate
financial activities and plays the most
important role when pricing financial
instruments. Investment banking evaluates
the worth of companies to create capital in
corporate financing, facilitate mergers and
acquisitions, conduct corporate restructuring
or reorganizations, and for investment
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