Credit Scoring: The complete box set!
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To complete our recent blog series about credit scoring, here is a short video introducing the WPS Data Science Module (DSM), a toolset capable of building behavioural and application scorecards. DSMWPS Data Science Module (DSM) features a collection of point-and-click tools including a Workflow Editor, Data Profiler and Machine Learning capabilities.
Please get in touch if you would like to know more about DSMWPS Data Science Module (DSM) or about credit scoring.
Credit Scoring: Part 9 – Scorecard Implementation: Deployment, Production and Monitoring
The real benefit of a scorecard or a credit strategy is only evident on implementation.
Credit Scoring: Part 8 – Credit Risk Strategies
Credit risk strategy is the process that follows after the scorecard development and before its implementation. It tells us how to interpret the customer score and what would be an adequate actionable treatment corresponding to that score.
Credit Scoring: Part 7 – Further Considerations in Credit Risk Modelling
Advanced validation framework and dealing with unbalanced data
Credit Scoring: Part 6 – Segmentation and Reject Inference
Segmentation and reject inference, or keep it simple? – That is the question!
Credit Scoring: Part 5 – Scorecard Development
Scorecard development describes how to turn data into a scorecard model
Credit Scoring: Part 4 – Variable Selection
How to achieve parsimony and what is the key information to look for?
Credit Scoring: Part 3 – Data Preparation and Exploratory Data Analysis
Data preparation is a key aspect of any data mining project including development of a credit scorecard
Credit Scoring: Part 2 – Credit Scorecard Modelling Methodology
How I make sure that other data scientists can replicate the same steps and produce similar results
Credit Scoring: The Development Process from End to End
Why do credit scoring? What is a credit score?
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