Business Analytics in Banking sector.

1. Business Analytics in Banking
Sector.
Vikhil S - 2037021

2. • The role of Business Analytics in Banking sector has become
prominent these days.
• The banking sector is largely data-intensive and has a lot of user data
for encryption.
• Banking sector has become very competitive and keep up to the
desires of consumers’, adopting to various changes has become
inevitable.
• By extracting the data from the consumers’ it may obtain insights that
cover all the aspects of the consumer behaviour.

3. Use of Business Analytics in Banking.
• It help the banks to meet their strategic needs, which must be done
beyond standard business operating and sales forecasting.
• It draws up organizational strategic insights and tangible goals.
• It has added social media to the mix of banking.

4. Why Business Analytics for Banking Sector?
• Issuance of credit ranking, can be identified through multivariate
descriptive analyses and predictive analytics.
• Improved risk management, understanding of clients, risk, and fraud
allows banks to maintain and grow a rentable client base.

5. Application of Business Analytics in Banking
• Analyzing Fraud: bank-related fraud identification is a vital task and
may protect all bank staff and clients with a range of fraud schemes
and suspicious practices.
• Calculating statistical parameters for recognizing outliers that might
indicate fraud (for example, percentages, norm deviations, high/low
levels).
• Classification – correlations between data elements can be identified.
• Digit stratification-to distinguish odd (i.e. too large or too low) entries.

6. • Analyzing Customer Data: Banks and credit unions fear losing
consumers or affiliates continuously and to reduce their turnover,
they should offer cheaper pricing, eliminate annual fees, and assign
services to their best customers. These repair approaches also have
related expenses, so these deals can not be managed for each
particular client. The effectiveness and viability of these tactics rely on
the right consumer to behave.

7. Recent application of Business Analytics by
different banks:
• HDFC Bank- Using Analytics to Get a Complete Picture of the
Customer
With the analytics engine in place, HDFC Bank can track every aspect
of a typical customer’s financial habits. “For example, we can
determine whether the customer has an active account or he’s just
having a salary credited to his account. Am I the primary bank
account for this customer or am I just another account?”
The analytics tools also gives the bank insights into personal habits of
its customers, allowing it to promote offers accordingly.

8. • Axis Bank – Analytics for Customer Intelligence & Risk Management.
Amit Sethi, CIO, Axis Bank, in an article published in CIO & LEADER
says, “…if we talk about Axis Bank, we have been using analytics in
almost every sphere. For example, when our sales guys are pitching to
a client for some loan, we try and find out what the background of
the customer is and what the likelihood of him taking a particular
loan is.” Axis Bank has seen the productivity of the sales staffs
increase by five times in the last financial year.

9. • State Bank of India-Adding Social Media to the Mix
Though private sector banks are leading the charge in using data analytics
for effective decision-making, public sector banks are not far behind.
SBI’s data warehouse has over 120 TB of data and receives an additional 4
TB of banking data a day. They are applying their data models to education
loans, automotive loans, housing loans, SME loans to try and reduce the
percentage of them going bad.
They are running studies on which colleges in which cities show the most
delinquencies in student loans and how to adjust for the increased risk.
They also use analytics to determine where ATM branches should be
positioned and how much cash should be placed in them.