A leading commercial bank has sought to aggressively expand
its presence in the small business lending segment. In its
efforts, it has used a number of techniques from “retail
lending”, combined with some of the wisdom deriving
from large project lending. The most important efforts have
included the use of clustering of small businesses into “similar
groups” with common lending norms.
Our team of consultants was asked to find an
alternative model of credit assessment which would enable
each of its credit officers to benefit from the wisdom and
experience inherent in the system, while combining it with
the aggression needed in an increasingly competitive marketplace.
Our team began with the hypothesis that there
are embedded in the system some ways of thinking and doing
which have proved effective in the past. Some of this can
be called “tacit knowledge” while other elements
of this could be called “methods of knowledge”
(i.e. the models of analysis and conclusion-making that is
a product of both individual and cultural upbringing).
As we went deeper, we found that this narrow
definition of “expertise” was insufficient in
describing what seemed to differentiate effective lending
from ineffective lending. The difference was seen not just
in the way the bankers knew things but also in the way they
acted and responded to clients. The two broad categories of
bankers, our team called “responsive bankers”
and “reactive bankers”.
Illumine’s approach to the challenge was to see responsive
bankers as superior ‘Credit Solution Designers’
who were willing to configure new ways of using credit to
enable clients leverage their own businesses.
The solution involved
- Specifying the specific differences
in the way successful bankers responded to a situation.
- Leveraging this insight into creating
a set of “design enablers” that allowed these
responses to be generalized and scaled.
- Providing local tools that integrate
fresh contextual knowledge into generic insight.
- Using this new knowledge to support
new credit configurations for each customer.