Sold by: ElectrifAi LLC
Deployed on AWS
Predict loss severities for residential mortgages based on macroeconomics and the individual's risk of defaulting.
Overview
Predict loss severities for residential mortgages based on macroeconomics and the individual's risk of defaulting. Includes type of residence (single-family, multi-family, residential, rural). Technical highlights include estimating Loss Severity (principal loss upon loan default and liquidation) via regression analysis on historical data. Inputting data of residential mortgage-backed securities and the underlying data we receive every month, the model output the scoring likelihood to pay, default or prepay the mortgage. To preview our machine learning models, please Continue to Subscribe. To preview our sample Output Data, you will be prompted to add suggested Input Data. 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: ESTLS-PS-RMG-AWS-001
Highlights
- Predict loss severities for residential mortgages based on macroeconomics and the individual's risk of defaulting.
Details
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Delivery method
Latest version
Deployed on AWS
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Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.2xlarge Inference (Batch) Recommended | Model inference on the ml.m5.2xlarge instance type, batch mode | $0.00 |
ml.p2.16xlarge Inference (Real-Time) Recommended | Model inference on the ml.p2.16xlarge instance type, real-time mode | $0.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $0.00 |
ml.m5.large Inference (Batch) | Model inference on the ml.m5.large instance type, batch mode | $0.00 |
ml.p2.xlarge Inference (Real-Time) | Model inference on the ml.p2.xlarge instance type, real-time mode | $0.00 |
ml.p3.16xlarge Inference (Real-Time) | Model inference on the ml.p3.16xlarge instance type, real-time mode | $0.00 |
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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
Initial Release
Additional details
Inputs
- Summary
Input: A zip file containing 4 comma separated (csv) files. Reference file: sample.zip loan.csv (required) loan_periodic.csv (required) macroeconomics.csv (required) macroeconomics_zip.csv (required)
- Input MIME type
- application/zip
https://github.com/ElectrifAi/model-aws-estimate-loss-severity/blob/main/sample.zip
https://github.com/ElectrifAi/model-aws-estimate-loss-severity/blob/main/sample.zip
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
Input: A zip file containing 4 comma separated (csv) files. Reference file: sample.zip | loan.csv (required)
loan_periodic.csv (required)
macroeconomics.csv (required)
macroeconomics_zip.csv (required) | Type: FreeText | Yes |
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Vendor resources
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