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Scoring Model Configuration and Calculation
Total autonomy to create and configure your own Scoring/Rating models with a flexible range of different approaches.
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Portfolio Risk Certification for Commercial Leads
Use of the scoring model as the main enabler and streamliner of marketing campaigns by scoring lists of clients in a single action.
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End-to-end Scoring Approval Process
Ownership over the overall scoring process including the assignment of scoring requests to analysts, definition of hierarchy approvals, management of overrides, among others.
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Simulation of Scoring Changes
Before making changes to the scoring module, proactively assess how the risk level distribution of your portfolio will be impacted by those changes before they are executed.
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Monitoring / Validation of the Scoring Model
Proactively identify issues or problems with the scoring model based on a comprehensive set of statistical tests focused on all scoring model dimensions, namely discriminatory power, stability, concentration, calibration & backtesting and data quality.
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Design and Configuration of Model Variables
Full autonomy and more flexibility to create new variables to be included in new versions of the scoring model based on a stored database, mitigating the usual lengthy IT process of developing and implementing changes to scoring models.
Total autonomy to create and configure your own Scoring/Rating models with a flexible range of different approaches.
Use of the scoring model as the main enabler and streamliner of marketing campaigns by scoring lists of clients in a single action.
Ownership over the overall scoring process including the assignment of scoring requests to analysts, definition of hierarchy approvals, management of overrides, among others.
Before making changes to the scoring module, proactively assess how the risk level distribution of your portfolio will be impacted by those changes before they are executed.
Proactively identify issues or problems with the scoring model based on a comprehensive set of statistical tests focused on all scoring model dimensions, namely discriminatory power, stability, concentration, calibration & backtesting and data quality.
Full autonomy and more flexibility to create new variables to be included in new versions of the scoring model based on a stored database, mitigating the usual lengthy IT process of developing and implementing changes to scoring models.
