Cut-off, odds and risk groups
To make automatic decisions you need to define score cut-off (or threshold)
that will divide “Good” customers that display positive behavior (such
as good profit and timely re-payments) from “Bad” customers that most
probably will display negative behavior (such as default).
Those customers, whose score is less than the cut-off point are rejected, the
automatic decision for them will be “No”.
Those customers whose score is higher than the cut-off point are accepted,
the automatic decision for them will be “Yes”.
Based on customer score you also can segment your customers to risk
groups.
Risk group is defined by odds of being “Good” relatively to
odds of being “Bad” (e.g. delinquent).
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For example, a borrower that belongs to group with
odds 300:1 has very low risk of being delinquent. But if
a borrower belongs to group with odds 5:1 he/she has
unacceptable credit risk.
Cut-off point approach assumes that in any case you will have a small amount of “Bad” customers in accepted segment. For example, in the 300:1 risk group you will have 1 “Bad” customer for every 300 “Good” customers. Similarly you will reject a certain amount of “Good” customers while rejecting all applicants below cut-off point.
Scoring technologies can be used as an objective risk management
tool, which help ensure centralized, uniform, more consistent and
reliable decision management across your organization.
Scoring is the most widely used in lending for all stages of a credit
life-cycle, from borrower acquisition to customer management to debt
collection and recovery. Credit scoring examples will be used in these
materials to display scoring techniques. |
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