Classic examples of predictive modeling method are scoring models.  In general scoring models are the most popular applications of predictive data mining, and in many industries, they are an integral part of day-to-day operations.  One of the most successful application of scoring models is consumer credit scoring.  The last decade has seen a proliferation of the use of consumer information to develop credit scores for use by credit card issuers, banks, mortgage lenders etc.  Credit scores are used for everything from business underwriting, classify creditworthiness and pricing decisions.  Predictive scoring models are beginning to get adopted in compliance applications as well.

Predictive scoring models are powerful technique for applying knowledge learned from historical data to new cases. For example, compliance scoring models can be developed based upon historical audits. These models can then be used to “score” new cases (new tax-payers in the case of tax compliance, new claims in the case of insurance, etc). These scores would represent the chance that the new cases are non-compliant.