Sold by: MphasisÂ
Deployed on AWS
This solution identify mortgage consumer complaints which may require a monetary compensation based on the narrative provided.
Overview
This is a Natural Language Processing (NLP) based text classification solution that helps identify whether a given consumer complaint requires monetary compensation based on the complaint narrative. A complaint is classified as either requiring monetary relief or can be resolved through explanations or non-monetary relief. This classification can be used to decide with what priority should a complaint be attended to.
Highlights
- This solution is trained on a large publicly available dataset of customer complaints about mortgage-related complaints and their resolution. It uses text analysis, natural language processing, machine learning techniques to predict if a complaint would require monetary compensation.
- This model allows companies to prioritize and manage their customer complaints efficiently to enhance the quality of customer service provided by them.
- Mphasis HyperGraf is an Omni-channel customer 360 analytics solution. Mphasis HyperGraf is an omnichannel customer 360 analytics solution. Need customized Deep Learning/NLP solutions? Get in touch!
Details
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Delivery method
Latest version
Deployed on AWS
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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.
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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.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
Initial relase
Additional details
Inputs
- Summary
- The input dataset should be in CSV format.
- The CSV file must have a single column, with different rows containing different customer complaint narratives.
- Each row must contain exactly one consumer narrative
- Limitations for input type
- A file can have maximum of 10 records and each record should not have more than 1000 words
- Input MIME type
- text/csv, application/json, text/plain
https://github.com/Mphasis-ML-Marketplace/Mortgage-Complaint-Severity-Predictor/tree/main/Input
https://github.com/Mphasis-ML-Marketplace/Mortgage-Complaint-Severity-Predictor/tree/main/Input
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
Consumer complaint narrative | Mortgage Specific Customer Complaints narrative | Type: FreeText | Yes |
Resources
Vendor resources
Support
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