Sold by: MphasisÂ
Deployed on AWS
Machine Learning solution to identify potential home loan candidates and their risk profiles from customers with an existing loan portfolio.
Overview
Bank Product Advisor is designed to assist the home loan department to shortlist potential candidates from customers with an existing loan portfolio with the bank e.g. Student Loan, Vehicle Loan, etc. It is divided into 2 modules: Module 1: Identifies potential home loan customers using demographics and other loan related parameters as given in the usage instructions. Module 2 [Optional]: Categorises risk of customer spends and investments to further shortlist the candidates from recommendations generated by module 1.
Highlights
- Recommendation engine built on exhaustive set of demographic, account, income and existing loan portfolio related features.
- Additional risk categorisation module built using customer's spend and investment pattern to help shortlist results from the main recommendation engine. It helps the loan approver to adapt to bank specific loan targets and external environment factors.
- 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 | $16.00 |
ml.m5.large Inference (Real-Time) Recommended | Model inference on the ml.m5.large instance type, real-time mode | $8.00 |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $16.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $16.00 |
ml.m4.16xlarge Inference (Batch) | Model inference on the ml.m4.16xlarge instance type, batch mode | $16.00 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $16.00 |
ml.p3.16xlarge Inference (Batch) | Model inference on the ml.p3.16xlarge instance type, batch mode | $16.00 |
ml.m4.2xlarge Inference (Batch) | Model inference on the ml.m4.2xlarge instance type, batch mode | $16.00 |
ml.c5.2xlarge Inference (Batch) | Model inference on the ml.c5.2xlarge instance type, batch mode | $16.00 |
ml.p3.2xlarge Inference (Batch) | Model inference on the ml.p3.2xlarge instance type, batch mode | $16.00 |
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)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
Bug Fixes and Performance Improvement
Additional details
Inputs
- Summary
Input
Supported content types: text/csv
The solution is divided into the following modules: Module 1: Based on the parameters listed below, this module helps identify the potential home loan customers with an existing loan portfolio. The data required contains demographic, account and other existing loan related variables as follows: "CUSTOMER_ID" - Unique ID of the customer "ACCOUNT_TYPE" - Type of Account held by the customer "GENDER"- Gender of the customer "AGE" - Age of the customer "MAX_BALANCE_MTD" - Max balance maintained over the customer lifecycle "MIN_BALANCE_MTD" - Min balance maintained over the customer lifecycle "TWL_TAG"- If the customer has an active two wheeler loan "PL_TAG"- If the customer has an active personal loan
"EDU_TAG" - If the customer has an active education loan "TL_TAG" - If the customer has an active term loan
"OTHER_LOANS_TAG" - If the customer has any other active loan "EOP_BAL_MON_01" - End of period balance for last 3 months "AMB_MON_01" - Average monthly balance for last 3 months "CUSTOMER_PROFESSION"- Customer Designation "METRO_CITY" - If the customer address falls in a metropolitan city "LAST_3MTHS_INCOME"- If any credits have been made in the last 3 months to the customer account "SAL_MON_01","SAL_MON_02","SAL_MON_03" - Salary for last 3 months credited to the bank account "CRED_NEED_SCORE" - Credit requirement score as assessed by the marketing teamModule 2 [Optional]: Module 2 considers customer spend and investment patterns and provides a risk categorization matrix with the following categories: "RISKY INVESTMENTS" "SAFE INVESTMENTS" "ESSENTIALS" "NON-ESSENTIALS" The module 2 further help shortlist the potential HL candidates from the recommendations generated by Module 1.Module 2 helps the loan approver to adapt to the loan targets and external environment factors.
Resources
- Input MIME type
- text/csv, text/plain
See Input Summary
See Input Summary
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
Mphasis DeepInsights Text Summarizer helps in summarizing text documents.
Deep Learning based solution which predicts positive, negative and neutral sentiments from text.
A Deep Learning approach for address extraction from unstructured documents.
Machine Learning based solution which extracts important Key phrases/words from a corpus of text.
Mphasis DeepInsights Table Detection helps in detecting and locating the tabulated information from scanned images.
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.