EFS Scoring fully covers the needs for application, behavioral, credit, collection or risk scoring in financial institutions. The results are applied to the application process for loan disbursement, CRM and marketing activities and portfolio risk segmentation to support the collection process.

In order to achieve a high structured decision process, financial institutions implement complex statistical models and advanced mathematical algorithms. EFS Scoring exposes and makes manageable the reasoning behind these structures. In order to open the scoring “black-box” EFS Scoring follows two basic principles: a) the usage of rule matrixes and b) the visualization of rule sets using a graphical representation with decision tables and diagrams to describe the risk policy.
 
Decision tables utilize a tabular view to describe and analyze decision situations. The business users can use a rule and expression editor to describe the logic and compose complex expressions. Decision diagrams are graph based views of processes. The processes incorporate policies that implement the decision functions and calculations and can take into account all data from the credit risk cycle. As an example, in the case of origination scores and requested amount can be combined to reach an approval or rejection of the application.

EFS Scoring graphical interfaces help the financial organizations to substantially reduce the implementation cycle of the scorecards. The tool is helping business users to configure, parameterize and deploy the scorecard models without any technical assistance. No coding is needed even for complicated expressions.
 
Business users can use a simple matrix-like graphical visualization to have an overview of the scorecard definition and the credit policy, empowering the user experience and the comprehension of the implemented models. Scorecards implementation and decisions are supported through decision tables and diagrams that are used as knowledge visualization schemes.
 
The business users can design, edit, publish and integrate the scorecards in the credit policy for testing (e.g. champion challenger or simulation) or operational purpose.

The process of scorecards selection and evaluation is utilizing simulations and Champion/ Challenger. Different scorecards can be deployed simultaneously, addressing the same scoring needs and sourced with different portfolios for a given time duration. At the end of the evaluation period business owners can compare the overall behavior and the actual results and choose the most appropriate scorecard to continue servicing their rating needs.
 
EFS Scoring monitors scorecard performance, account analytics and execution statistics including subject areas such as: performance, scorecards statistics and model validation reports. An extended list of reports is available, including: Lift curve, ROC, Binomial statistical testing, Chi-square stability testing, Scorecard correction, Population stability reporting.

The scores are integrated in the more general credit/risk decision environment and their risk indicative effectiveness can be evaluated in the credit risk framework.
 
The implemented scorecards can be executed in batch and real-time mode (via web service interfaces) and their outcome can be exposed and fed to other internal or external systems, such as loan origination, collection and recoveries or CRM. EFS Data Repository provides the underlying data layer, that consolidates data from various data sources, computes complex metrics, keeps data history and exposes the data library in a form usable during design mode to the business users.