Amazon Sagemaker
Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.
Credit Line Management
By:
Latest Version:
1.0.1
Balance potential to increase credit lines to encourage clients to spend more money on credit against the risk if the client cannot pay.
Product Overview
Increasing credit lines encourages clients to spend more money with their credit card. This model periodically checks the potential to increase the credit line but not to take on risk if the client cannot pay the bill. Line sensitivity model and risk guardrail policy applied to develop model-driven credit line management framework for top US credit card issuers which drove 14% profit lift compared to previous policy-based framework. 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: CLINE-PS-CCC-AWS-001
Key Data
Version
Type
Model Package
Highlights
Periodically check potential to increase credit lines to encourage clients to spend more money, but not to take on risk if the client cannot pay.
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Pricing Information
Use this tool to estimate the software and infrastructure costs based your configuration choices. Your usage and costs might be different from this estimate. They will be reflected on your monthly AWS billing reports.
Estimating your costs
Choose your region and launch option to see the pricing details. Then, modify the estimated price by choosing different instance types.
Version
Region
Software Pricing
Model Realtime Inference$0.00/hr
running on ml.p2.16xlarge
Model Batch Transform$0.00/hr
running on ml.m5.2xlarge
Infrastructure PricingWith Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
With Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
SageMaker Realtime Inference$16.56/host/hr
running on ml.p2.16xlarge
SageMaker Batch Transform$0.461/host/hr
running on ml.m5.2xlarge
Model Realtime Inference
For model deployment as Real-time endpoint in Amazon SageMaker, the software is priced based on hourly pricing that can vary by instance type. Additional infrastructure cost, taxes or fees may apply.InstanceType | Realtime Inference/hr | |
|---|---|---|
ml.p2.xlarge | $0.00 | |
ml.p2.16xlarge Vendor Recommended | $0.00 | |
ml.p3.16xlarge | $0.00 |
Usage Information
Model input and output details
Input
Summary
Input: A zip file with 6 comma separated csv files. Reference file: sample.zip target_week.csv (REQUIRED) creditcard_pnl.csv (REQUIRED) bureau_info.csv (REQUIRED) creditcard_transaction.csv (OPTIONAL) mechant_info.csv (OPTIONAL) cli_campaign.csv (not required for scoring,but required for training)
Input MIME type
application/jsonSample input data
Output
Summary
A list of JSON objects containing the fields listed below. Reference file: sample.zip.out accountID: accountID associated with the transaction credit_line_increase: credit line increase amount for credit card accounts month: month tag of the monthly report
Output MIME type
application/jsonSample output data
Sample notebook
Additional Resources
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Support Information
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