Bonding BI with banking
over three million customers, HDFC Bank needed a business intelligence framework
to keep up with and analyse its information stores
Business intelligence (BI) tools are the banking sectors
lifeline, helping to consolidate the vast volumes of data, and target the right
segment for the right scheme. Success helps in reducing costs tremendously.
HDFC Bank started using BI in 2001 when their customer base expanded to over
three million. Explains Munish Mittal, the banks Vice-president for Information
Technology, Once we acquired critical mass with around three to four million
customers in 2001, we had to integrate customer data into a central customer
data repository to understand and review all services the customer was subscribing
to, as well as customer profitability, to devise a customer-centric framework.
Within six to nine months after the BI implementation, HDFC felt a tremendous
- Analysing customer behaviour and interaction with the
- Devising a customer contact strategy and implementing
suitable channels such as direct banking.
- Analysing customer preferences for transaction channels.
- Identifying personalised needs based on relationship value,
and devising cross-sell strategies to arrive at the basic mission, which is
to be a one-stop shop.
- Devising a suitable product strategy.
- Refining new products.
The 360-Degree View
HDFC began implementation by first creating a 360-degree view of customer transactions,
profitability, product acquisition, product holding, loan repayment, ticket
sizing and transactional trends of usage, which helped them to offer many new
things such as electronic bill cards.
Next, HDFC did data warehousing by analysing campaign management using a modelling
engine by Unica on top for studying customer behaviour. It took around eight
to nine months for the bank to integrate data warehousing across product segments
in retail banking.
- Arrive at a suitable fee-based service for better
channel utilisation by analysing behaviour on average balances maintained
by certain customer segments.
- Upgrade customer profitability across various
profitability bands by studying cross-selling strategy through trends
from BI framework, and offering alternative fee-based business propositions
to less profitable customers.
- Judge a delinquent customer before granting
a second-class/top-up loan.
Bonding them Together
Bonding BI to customers and suppliers was another issue that HDFC had to deal
with and managed successfully. For supply chain relationship management,
we have implemented solutions in the area of corporate banking where the payment
between the automobile dealer and manufacturer as well as the supplier and the
same manufacturer can be executed in real time on the Internet, reveals
HDFC uses various Business Objects technology-based end-user reporting and personal
OLAP tools to study the behaviour of supplier, dealer and manufacturer transactions
over the Internet to generate trends, devise pricing strategy, and create innovative
use of product offerings.
For cleaning up data, HDFC has in-built health check-ups, and for Extract Transform
Load (ETL) they have database administrators. Mittal explains: For ETL
we have database administrators who work with us to optimise ETL performance.
We use innovative and state-of-the-art storage technology to derive maximum
performance of IO (input/output) processing.
For data integration, HDFC has health checks, data standardisation,
and data enrichment as a part of their daily/weekly/monthly data warehousing
processing. HDFC is currently implementing a data quality and householding solution
from SAS for enhancement of its BI infrastructure.