Sold by: Mphasis
Deployed on AWS
Ensemble Machine Leaning algorithm-based solution that predicts the probability of fraud for auto insurance claims.
Overview
Fraudulent claims are a major challenge faced by insurance providers. This solution helps insurance providers predict whether a claim is fraudulent or not to support the decision-making process. This solution considers various policy, demographic, and incident details related to the claim to return a probability score.
Highlights
- This solution provides a cost-efficient way to predict fraudulent auto insurance claims.
- This solution uses various policy, demographic, and incident details related to the claim to return a probability score.
- Mphasis HyperGraf is an omni-channel customer 360 analytics solution. Need customized Deep Learning/NLP solutions? Get in touch!
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.m5.large Inference (Batch) Recommended | Model inference on the ml.m5.large instance type, batch mode | $20.00 |
ml.m5.large Inference (Real-Time) Recommended | Model inference on the ml.m5.large instance type, real-time mode | $10.00 |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $20.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $20.00 |
ml.m4.16xlarge Inference (Batch) | Model inference on the ml.m4.16xlarge instance type, batch mode | $20.00 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $20.00 |
ml.p3.16xlarge Inference (Batch) | Model inference on the ml.p3.16xlarge instance type, batch mode | $20.00 |
ml.m4.2xlarge Inference (Batch) | Model inference on the ml.m4.2xlarge instance type, batch mode | $20.00 |
ml.c5.2xlarge Inference (Batch) | Model inference on the ml.c5.2xlarge instance type, batch mode | $20.00 |
ml.p3.2xlarge Inference (Batch) | Model inference on the ml.p3.2xlarge instance type, batch mode | $20.00 |
Vendor refund policy
Currently we do not support refunds, but you can cancel your subscription to the service at any time.
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
Updated with new features
Additional details
Inputs
- Summary
The model takes a .csv file which contains inurance claims information.
- Input MIME type
- text/csv
https://github.com/Mphasis-ML-Marketplace/Auto-Insurance-Claims-Fraud-Prediction
https://github.com/Mphasis-ML-Marketplace/Auto-Insurance-Claims-Fraud-Prediction
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
policy_number | A unique number or ID for every claim | Type: Integer | Yes |
months_as_customer | A number to indicate the number of months as customer | Type: Integer | Yes |
age | Age of the insured person | Type: Integer | Yes |
policy_bind_year | The year when the policy was started | Type: Integer | Yes |
split_limit_person | The maximum amount an insurer will pay to a single person for medical bodily injury in an accident. For example, if the amount is $200K, enter 200 | Type: Integer | Yes |
split_limit_accident | The maximum amount a company will pay to all parties injured in a single accident. For example, if the amount is $ 200K, enter 200 | Type: Integer | Yes |
policy_deductable | Amount ($) that the insurer is responsible for paying towards an insured loss | Type: Integer | Yes |
policy_annual_premium | Premium amount of the policy in dollars | Type: Continuous | Yes |
umbrella_limit | Top up amount to the policy in dollars | Type: Integer | Yes |
insured_sex | The values are ‘MALE’ or ‘FEMALE’ | Type: FreeText | Yes |
Resources
Vendor resources
Support
Vendor support
For any assistance, please reach out at:
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
One-click AI masks PII, PHI & PCI in docs, images or data streams—directly inside your AWS account. Unlimited usage, audit-ready HIPAA/PCI/NAIC templates
The Insurtech Market is surging with digital innovations in insurance, projected to reach USD 254.64 billion by 2030 at a 53.1 percent CAGR, fueled by AI, open finance, and real-time payments, enhancing customer-centric solutions.
Sophos Cloud UTM9 is nearing end-of-life and will not be supported after 30 June 2026. Sophos recommends using Sophos Firewall on AWS.
Nimbal MAC Auto is a Test Automation Development Machine designed for organizations who want to test their Android and iOS apps from a dedicated MAC environment. Organizations may use their framework or use the Nimbal Auto Framework to build their tests. This cloud-based environment enables testers to write and run tests as efficiently as in the local environment.
Get the foundational Data Quality rules you MUST have to validate data in any table given to you in plain English. EigenRules will accelerate SMEs work and reduce time to market for onboarding new data sources or apps.
WordPress powered by AMIMOTO with Auto Scaling provides on-demand memory, CPU, and storage. This 1-Click AMI was developed by our expert engineers to be the highest performing AMI for WordPress on Amazon Web Services. Completely preconfigured with WordPress, PHP 7, MySQL (Percona Server), and NGINX.
Propensity model that determines the probability that a consumer is an Auto DIYer if they regularly work on their car.
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.