Wagner Associates has extensive experience in the development
and review of credit scoring models. A scoring model assigns a
score to borrowers (either an individual or a company) based on
available information about the borrower (such as credit history).
The score corresponds to the riskiness of the loan, that is, to the
likelihood that the loan will have a specified bad outcome such as
default or significant delinquency.
Scoring models are developed by statistical analysis of historical
data sets. Wagner Associates has broad knowledge of the
statistical methods that are used to develop scoring models. Our
knowledge extends from the standard methods, notably logistic
regression, to more exotic techniques such as classification trees,
neural networks, and expert systems. Wagner Associates has the
computing hardware and software tools to analyze large data sets
and to develop or review scoring models. We have particular
expertise with the S-Plus software system, a comprehensive
statistical package for data analysis.
We have worked on scoring models for standard retail credit
applications including models for mortgages, for credit cards, and
for home equity loans. We have also applied scoring model
methods in non-standard circumstances. In fact, the statistical
methodology of scoring models applies to any circumstance where
one wishes to predict the probability of a particular outcome (good
or bad) from any available information source. Currently, we are
developing a scoring model for an accounting firm to evaluate the
engagement risk of new clients. For example, such risk includes
the possibility that a client will draw the firm into detrimental
In addition, Wagner Associates has developed patent-pending methods of automated
statistical data mining that can run as client-side or server-side generators of credit scoring models.
to inquire about our consulting services in credit risk.