Sold by: MphasisÂ
Deployed on AWS
GenAI solution to generate MT103 SWIFT messages that mimics real SWIFT messages without compromising on privacy
Overview
"SynthStudio is a sophisticated Generative AI solution designed to produce high-quality synthetic data, reflecting the nuances of real data while ensuring privacy and overcoming the challenges of data privacy, scarcity, and imbalance. Generating data instances that mimic the distribution of real datasets is achieved through advanced ML techniques, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformer models. Synthetic data for SWIFT MT103(Single Customer Credit Transfer) creates curated synthetic data which helps users to test their systems, do simulation exercises, train employees and do compliance testing without getting exposed to actual SWIFT messages. These synthetic swift messages mimic actual transactions in their format and structure. The synthetic data is generated for both the Mandatory and Optional tags. Users can select countries, currencies and banks of their choice and enter custom banks to help generate personalized data."
Highlights
- This solution helps banks or other financial institutions to get access to synthetically generates SWIFT messages which exactly mimic actual SWIFT in terms of structure and content. The synthetically generated data conatins both Mandatory as well as optional fields.
- The solution also gives users to get information of how a swift transaction would look like between certain countries, currencies and banks of their choice. Added to it users can enter custom banks for synthetic data generation.
- Mphasis Synth Studio is an Enterprise Synthetic Data Platform for generating high-quality synthetic data that can help derive and monetize trustworthy business insights, while preserving privacy and protecting data subjects. Build reliable and high accuracy models when no or low data is available.
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.xlarge Inference (Batch) Recommended | Model inference on the ml.m5.xlarge instance type, batch mode | $0.00 |
ml.m5.large Inference (Real-Time) Recommended | Model inference on the ml.m5.large instance type, real-time mode | $0.00 |
ml.m5.xlarge Training Recommended | Algorithm training on the ml.m5.xlarge instance type | $10.00 |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $0.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $0.00 |
ml.m4.16xlarge Inference (Batch) | Model inference on the ml.m4.16xlarge instance type, batch mode | $0.00 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $0.00 |
ml.p3.16xlarge Inference (Batch) | Model inference on the ml.p3.16xlarge instance type, batch mode | $0.00 |
ml.m4.2xlarge Inference (Batch) | Model inference on the ml.m4.2xlarge instance type, batch mode | $0.00 |
ml.c5.2xlarge Inference (Batch) | Model inference on the ml.c5.2xlarge instance type, batch mode | $0.00 |
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 algorithm
An Amazon SageMaker algorithm is a machine learning model that requires your training data to make predictions. Use the included training algorithm to generate your unique model artifact. Then deploy the 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
This is the latest version
Additional details
Inputs
- Summary
The user input is a input_zip.zip, which has two files:
- user_input.json: It is a json file where keys are 'countries', 'IBAN', 'currencies', 'no_of_datapoints'. The values in the fields are the filters for the above mentioned fields.
- more_banks.csv: If user wants more banks than what is available, then the bank information could be provided in a .csv format where the fields are: 'ISO COUNTRY CODE', 'COUNTRY NAME' , 'INSTITUTION NAME', 'IBAN BIC', 'ADDRESS_BANK' , 'CURRENCY'.
- Limitations for input type
- In the user_input.json, the 'no_of_datapoints' field is mandatory, the user has to specify how much datapoints are required in the synthetic data. Rest all are optional
- Input MIME type
- application/zip, application/gzip, text/plain
https://github.com/Mphasis-ML-Marketplace/Synthetic-Data-Generation-SWIFT-MT103/blob/main/input/input_zip.zip
https://github.com/Mphasis-ML-Marketplace/Synthetic-Data-Generation-SWIFT-MT103/tree/main/input
Resources
Vendor resources
Support
Vendor support
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