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Regression Analysis for credit scoring and bad debt prediction

Integrated solution with data modeling, visualization, reporting

Manage big data with clustering, in-memory cache and NoSQL based OLAP

Process

CRISIL’s data science and modeling solution involves three steps:

Step 1: Feature Engineering

This involves

Deep domain expertise results in creation of relevant derived attributes
Enhanced variable selection using statistical modelling techniques
Model selection, verification & validation for balanced fitment

Step 3: Parameterization & Scalability

This involves

User defined parameters for consideration in the analytical framework
Data quality monitoring
Ability to support large volumes of data on both traditional and big data stacks

Step 2: Creating Integrated Solution

This involves

Results of the data modelling are integrated with the workflow/reporting/visualization framework
Superior visualization for ease of interpretation and decisioning
Automated email of training and prediction results with complete details including error curves

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Questions?

For any risk solution related queries, please contact:
+91 22 33428266
Sales.Birs@crisil.com