Sold by: ElectrifAi LLC
Deployed on AWS
Behavior Scorecard monitors risk after onboarding.
Overview
Providing the foundation of lifecycle credit risk strategy, this model combines strategies to enable automated underwriting differentiating low (0%) to high (40%) risk. Using customer demographic data, credit history and payment behavior, lifecycle scorecard insights are produced. The Behavior Scorecard monitors risk after onboarding. 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: BSCOR-PS-LOA-AWS-001
Highlights
- Behavior Scorecard monitors risk after onboarding.
- Applied logistic regression to predict client's default probability.
Details
Sold by
Delivery method
Latest version
Deployed on AWS
New
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
This product is available free of charge. Free subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Vendor refund policy
This product is offered for free. If there are any questions, please contact us for further clarifications.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
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.
Deploy the model on Amazon SageMaker AI using the following options:
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
Input: A zip file containing upto 3 comma separated csv files. Reference file: sample.zip contract.csv (required) repayment.csv (required) bureau.csv (optional)
- Input MIME type
- application/json
https://github.com/ElectrifAi/model-aws-behavior-scorecard/blob/main/sample.zip
https://github.com/ElectrifAi/model-aws-behavior-scorecard/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 upto 3 comma separated csv files. Reference file: sample.zip | contract.csv (required)
repayment.csv (required)
bureau.csv (optional) | Type: FreeText | Yes |
Resources
Vendor resources
Support
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Similar products
LevelEleven is a sales performance management solution for gamification and coaching. Reinforce successful behaviors through competitions, personalized scorecards, intelligent goal management, automated recognition, and data-driven coaching natively within Salesforce.
Application Scorecard predicts customer's default probability.
Collection Scorecard determines willingness to pay back a loan after defaulting.
At Observe.AI, we help businesses and their customers unlock extraordinary outcomes by using AI to drive real impact at scale. Our Post-interaction AI suite analyzes 100% of customer interactions in the contact center to surface insights across the enterprise, and drive winning behaviors in the contact center that increase revenue, improve retention, and optimize efficiencies and compliance.
Customer reviews
No customer reviews yet
Be the first to review this product . We've partnered with PeerSpot to gather customer feedback. You can share your experience by writing or recording a review, or scheduling a call with a PeerSpot analyst.