by July 4, 2009 0 comments

On an average ICICI Bank receives 3.6 mn calls in a month in the inbound call
center from 1.4 mn customers across Liabilities, Credit Cards and Assets base.
Of this, around 80% of the calls are for seeking information on
transactions/products. Thus there was an opportunity for the bank to use this
point of contact for varied activities such as cross-sell & upsell of other
products, retention/winback programs, obtaining information for profile
building, contact updation & linking of various existing relationships, channel
migration programs, and seeking customer referrals (Customer Get Customer
Program). This was made possible by employing a robust technology architecture
powered by high end analytics which enabled quick pitch & closure on phone by
service executive (PBO).

Amit Sethi
Joint General Manager, Technology
Ashish Singhal, DGM, Business Intelligence Unit

QPlease highlight the key business and/or social benefits that this
project has delivered.
With a conservative response rate of 3% it is projected to yield 30 Mn
USD in the first year itself and with learning’s going forward this is
expected to have a quantum leap.

QWhat were the key business challenges that were faced while
implementing this project?
Business challenges included the following:
Creation of the customer product propensity models.
Training a large service workforce on selling varied products.
Design of processes so as to minimize cost and offer improved
convenience to customers.

QWhat according to you sets this project apart from any other in its
class? What’s the unique selling proposition (USP) of this project?
This is the first of its kind implementation in India where the inbound
call centre is being used for above activities using a complex set of data
analytics and technology for enhancing customer value and lifetime with the

The analytics framework works by identifying the timing and content of pitch
and the technology framework helps in generation of this information and in
aiding the delivery of the same to the PBO. The core data systems herein refer
to product host systems viz. Finacle, Finone, and Prime and the central cross
sell systems Loan on Phone. The financial and non-financial transactions
information comes through these channels and the third party data (including
Credit Bureau) is used for calculating the customer’s size of wallet which helps
in determining the profile of the customer.

The analytical applications use this data to arrive at rank order of the
pitch to be made to the customer and feed this information to the CRM, Finacle-CRM,
through a special application called as ‘Message Centre’ which is used by PBO at
the inbound call centre for knowing what to pitch to a particular customer and
also for recording the response of the customer. This information pull is done
through the Campaign Management Tool, UNICA Affinium, which is interfaced with
the CRM system. Based on the customer response, the resultant action is
reflected in either core data systems or is passed onto the field or outbound
telecalling channels for further action. For this purpose, the CRM system is
integrated with the Sales Force Automation (SFA) system which is used for lead
management. In addition to the above, on an online basis the customers who have
responded as ‘Not Interested’ are suppressed from the CRM screen and the next
pitch for that customer is shown to the PBO. For customers who have responded as
‘Remind Me Later’ this information is again stored in Data Warehouse and after
30 days a follow up call is automatically initiated to them thrugh the Campaign
Management Tool. This seamless flow of information between the core systems,
enterprise data warehouse, CRM, analytical applications, campaign management
tool and the lead management system have helped them create a robust
infrastructure which in turn has led to smooth functioning of this
project.Managing the huge technology systems integration into a data warehouse
as a ‘unified comprehensive solution’ for this project encountered range of
hurdles of different kinds – technical, people, change management and smooth
scalability. In term of technical hurdles, challenges existed in data accuracy,
completeness and cleansing to facilitate effective usage. Hurdles also posed in
the subsequent build up of specific logics, derived variables, data cross system
data marts and views. In term of people challenges, the project called for a
complete revisit of the ‘querying philosophy’- which had to be altered to be in
line with the data design aspects as per the Sybase IQ architecture and the
domain functional requirements.

Company Scenario
Before Deployment
  • Inbound call center was used just to resolve customer issues and to
    give relevant information as requested by customer
After Deployment
  • Inbound call center is now used not only to resolve customer queries
    but also to sell/upsell bank products to potential customers

This project is expected to bring Rs 135 Cr in first year even if response
rate is as low as 3%. These expected results are amazing given total expenditure
of Rs 5.85 Cr on this project.

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