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Industries & Areas of Application

Financial Institutions

Application Scoring

Financial institutions have to analyse customer application data in order to estimate the creditworthiness of their new and/or potential customers and predict the Probability of Default (PD), Loss Given Default (LGD) and Recovery Rates (RR) related to a certain kind of financial products and customer types. In Application Scoring Models along with personal and financial data of the customer also demographic and social data is analysed.

In addition to the Application Scoring very often banks and financial institutions in general also do the so called Fraud Analysis trying to estimate the probability of Fraud related to certain customers (please see below for more information).

Application Scoring Models are also quite often combined with the so called Cross Selling Scoring Models and Revenue Scoring Models (for more information please see below) in order to be able to focus on customers with high potential and maximize profits and efficiency of the Financial Institution.

Application data is consequently enriched with behavioural data in order to enhance the predictability of the scoring model. For this purpose so called Behavioural Scoring Models are used along with the Application Scoring Models.