Sold by: ElectrifAi LLCÂ
Deployed on AWS
Detect fraudulent ACH wire transfers with a fraud risk score to ensure transfers are only initiated by the account owner.
Overview
Machine learning based solution used to monitor ACH wire transfers, determine fraudulent transactions and provide reasons to flag transactions. A fraud risk score is calculated to ensure transfers are only initiated by the account owner. 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: APPFR-PS-LOA-AWS-001
Highlights
- Ensure transfers are only initiated by the account owner by detecting fraudulent usage of ACH wire transfers.
Details
Sold by
Delivery method
Latest version
Deployed on AWS
Unlock automation with AI agent solutions
Fast-track AI initiatives with agents, tools, and solutions from AWS Partners.
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
Pricing is based on actual usage, with charges varying according to how much you consume. 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.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.p2.16xlarge Inference (Real-Time) Recommended | Model inference on the ml.p2.16xlarge instance type, real-time mode | $0.00 |
ml.m5.2xlarge Inference (Batch) Recommended | Model inference on the ml.m5.2xlarge 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 |
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 |
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)Â .
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
Vulnerabilities CVE-2021-3177 (i.e. https://nvd.nist.gov/vuln/detail/CVE-2021-3177Â ) and CVE-2021-3449 (i.e. https://ubuntu.com/security/CVE-2021-3449Â ) has been resolved in version 1.0.1.
Additional details
Inputs
- Summary
Usage Instructions
Input/Output
- Input MIME type
- application/json
https://github.com/ElectrifAi/model-aws-ach-wire-fraud-detection/blob/main/sample.zip
https://github.com/ElectrifAi/model-aws-ach-wire-fraud-detection/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 |
|---|---|---|---|
scoring_date.csv | A zip file containing 4 comma separated csv files. Reference file in zip | Type: FreeText
Allowed values: scoring_date.csv, profiles_senders.csv, profiles_receivers.csv,transactions.csv | Yes |
profiles_senders.csv | A zip file containing 4 comma separated csv files. Reference file in zip | Type: FreeText
Allowed values: scoring_date.csv, profiles_senders.csv, profiles_receivers.csv,transactions.csv | Yes |
profiles_receivers.csv | A zip file containing 4 comma separated csv files. Reference file in zip | Type: FreeText
Allowed values: scoring_date.csv, profiles_senders.csv, profiles_receivers.csv,transactions.csv | Yes |
transactions.csv | A zip file containing 4 comma separated csv files. Reference file in zip | Type: FreeText
Allowed values: scoring_date.csv, profiles_senders.csv, profiles_receivers.csv,transactions.csv | 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
The Lower Lumbar Model detects bending, twisting, acceleration duration, degrees, and counts.
In-Memory Distributed Store for .NET and Java. Extremely fast and scalable.
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.