README.md

metadata

license: gpl-3.0
task_categories:
  - tabular-classification
  - tabular-regression
tags:
  - payments
  - fintech
  - payment-routing
  - payment-intelligence
  - tabular
  - synthetic-data
  - machine-learning
  - catboost
  - open-source
pretty_name: PayMind Reference Dataset

PayMind Reference Dataset

Synthetic/reference payment-routing data for PayMind, an open-source payment route intelligence engine.

This dataset is designed to demonstrate PayMind's training, evaluation, and routing workflow across route selection, transaction reliability, and expected settlement time.

Important: This dataset contains synthetic/reference data only. It does not contain real customers, real transactions, payment credentials, personally identifiable information, or production payment-provider performance data.

Dataset Files

The dataset contains three primary CSV files:

payment_method.csv

Reference data for training the payment-method candidate model.

The model learns which payment routes are most relevant for a given transaction context.

success.csv

Reference data for training the transaction-success model.

The model estimates the probability of a transaction succeeding for an eligible payment route.

arrival.csv

Reference data for training the settlement model.

The model estimates expected transaction arrival/settlement times, including typical and more conservative settlement estimates.

Tasks

PayMind uses the dataset across multiple tabular machine-learning tasks:

• Payment route selection — identify relevant payment methods for a transaction.
• Transaction reliability — estimate the probability of successful processing.
• Settlement estimation — estimate expected transaction arrival time.
• Route intelligence — combine model outputs with eligibility rules and estimated fees to rank available payment routes.

Intended Use

This dataset is intended for:

• Demonstrating the PayMind architecture
• Training the PayMind reference models
• Testing the PayMind training pipeline
• Software development and integration testing
• Machine-learning experimentation
• Educational and research use

Users deploying PayMind in a real payment environment should train models using appropriately governed data from their own environment.

Data Source

The data provided in this repository is synthetic/reference data created for the PayMind open-source project.

It should not be interpreted as observed behaviour of any real payment provider, financial institution, customer, or payment network.

Privacy

The reference dataset is designed to contain no real:

• Customer identities
• Names or email addresses
• Account or card details
• Payment credentials
• Authentication tokens or API keys
• Production transaction records
• Personally identifiable information (PII)
• Proprietary payment-provider performance data

Reference Models

The PayMind reference models are trained using synthetic/reference data and are intended to demonstrate the architecture rather than provide production payment-routing benchmarks.

Models:
https://huggingface.co/navk8690/paymind-reference-models

Live Demo

Try PayMind through the interactive Hugging Face Space:

https://huggingface.co/spaces/navk8690/paymind

The demo evaluates transaction context, eligible payment routes, predicted reliability, settlement expectations, and estimated cost to produce a ranked route recommendation.

Source Code

PayMind is open source.

GitHub:
https://github.com/navjotk8690/paymind

The repository includes the SDK, API, model implementations, training pipeline, data contracts, reference configuration, tests, and Gradio demo.

Training

The PayMind project provides a training pipeline for rebuilding the reference models or training models using your own compatible datasets.

The expected datasets are:

payment_method.csv
success.csv
arrival.csv

Refer to the PayMind repository documentation for the exact schemas and training instructions.

Limitations

This dataset is provided as a reference implementation dataset.

Results obtained from models trained on this data:

• Do not represent actual payment-provider performance
• Should not be treated as production routing benchmarks
• Do not guarantee transaction success or settlement time
• Should not be used as a substitute for production-specific model validation
• May not reflect the distributions, constraints, or behaviour of a real payment environment

Production users should validate their own data, models, eligibility rules, fee configuration, and ranking strategy before deployment.

License

This dataset is released under the GNU General Public License v3.0 (GPL-3.0) as part of the PayMind open-source project.

See the repository license for full terms.