Using Predictive Analytics to Transform the Banking Industry - PowerPoint PPT Presentation

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Using Predictive Analytics to Transform the Banking Industry

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If you would like to understand how predictive analytics in banking can help grow your business, get in touch. – PowerPoint PPT presentation

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Title: Using Predictive Analytics to Transform the Banking Industry


1
5 Areas Predictive Analytics in Banking Can
Bring Change
2
In todays competitive world, growing customer
base and satisfying them is considered the most
challenging task. To get over this, banks have
been implementing various tools over time.
But Important Issues like
Retaining and attracting different types of
customers
Cross-selling of which products exactly to whom
Fraud Detection
Application Screening
Ensuring long-term loyalty from high-valued
customers
Credit And Collections
Predictive Analytics comes into the picture here.
3
Predictive Analytics Helps Banks To
Here are the 5 areas in which predictive
analytics in banking will bring change
4
Fraud Detection
Here are few tools that help in catching these
frauds
Fraud is becoming an area of big concern for
every sector and for banking and financial firms,
it can cost a lot to them.
Banks need intelligent systems and tools to deal
with them.
5
Application Screening
Predictive analysis in banking can help
The results are very much accurate and authentic
to be used.
6
Customer Acquisition Retention
Here are few tools that help in catching these
frauds
Keeps the right customers longer.
Predicts which actions will earn their loyalty.
Identifies the customers most likely to defect
before they end their relationship.
7
Cross-Selling
Predictive analytics helps examine customers
usage, spending, and other behavior and leads to
effective cross-selling of the right product at
the right time.
Efficient cross-selling of products can happen by
analyzing the existing customer behavior at
places where multiple products are offered.
8
Collections
Banks have a mix of customers who always pay on
time and those who lag.
Analytics helps to identify the customers who
would be at risk in the future and what actions
banks should take to achieve positive results.
It is a tricky task to keep a track and maintain
records of all individuals and differentiate who
to focus more.
9
CRIF has been providing Credit Risk Analytics and
other data science services to various banking
financial institutions. If you would like to
understand how predictive analytics in banking
can help grow your business, get in touch.
CONTACT US
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