Sold by: ElectrifAi LLC
Deployed on AWS
In credit line management, this risk model evaluates risk at time of acquisition to calculate a risk score to limit loss.
Overview
Evaluate risk at the time of acquisition with this risk model to periodically calculate a risk score and intervene early to limit loss. The objective - find the RPC (Right Party Contact) for the collection agency to reach the delinquent customer. With enhanced modeling tools, an Early Intervention solution was developed for Top US credit card issuers and reduced the annual credit loss by over 15% and increased profitability by over $50 million. Additional opportunities identified, include realignment of agents to queues, additional early collections treatment strategies and scope expansion to business cards and exempt portfolios. To preview our machine learning models, please Continue to Subscribe. Sample Data is representative of the Output Data but does not actually consider the Input Data. Our machine learning models return actual Output Data and are available through a private offer. Please contact info@electrifai.net for subscription service pricing. SKU: EITVN-PS-CCC-AWS-001
Highlights
- Periodically calculate risk score and intervene early to limit loss by finding the RPC (Right Party Contact) to reach delinquent customer.
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
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Version release notes
Vulnerability CVE-2021-3177 (i.e. https://nvd.nist.gov/vuln/detail/CVE-2021-3177 ) has been resolved in version 1.0.1.
Additional details
Inputs
- Summary
Data in CSV files. The files should then be archived and zipped into a single file e.g. input.tar.gz PNL.csv (required) Bureau.csv (required) Transaction.csv (required) Authorization.csv (required)
- Input MIME type
- multipart/form-data
https://github.com/ElectrifAi/model-aws-early-intervention/blob/main/input.tar.gz
https://github.com/ElectrifAi/model-aws-early-intervention/blob/main/input.tar.gz
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
Data in CSV files. The files should then be archived and zipped into a single file e.g. input.tar.gz | PNL.csv (required)
Bureau.csv (required)
Transaction.csv (required)
Authorization.csv (required) | Type: FreeText | Yes |
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