strova-ai/synthetic_credit_card_default

Synthetic Credit Card Default Dataset

High-fidelity synthetic dataset for financial AI research, created with Syncora.ai

✅ What's in This Repo?

This repository includes:

• —✅ Synthetic Credit Card Default Dataset (CSV) → Download Here
• —✅ Jupyter Notebook for Analysis & Modeling → Open Notebook
• —✅ Instructions for generating your own synthetic data using Syncora API

📘 About This Dataset

This dataset contains realistic, fully synthetic credit card client records based on the UCI Credit Card Default dataset (2005). It allows developers and data scientists to perform credit risk analysis without using real customer data. Using Syncora.ai, you can also generate synthetic data tailored to different modeling scenarios, ensuring privacy and compliance.

Ideal for:

• —Credit risk modeling and analysis
• —Binary classification projects
• —Explainable AI (XAI) experiments
• —Financial ML benchmarking
• —Dataset for LLM training (e.g., financial question answering)
• —Data science education and prototyping

🔍 Features

• —Demographics: Age, sex, education, marital status
• —Credit behavior: Credit limits, bill amounts, repayment history
• —Target variable: Default status (0 = no default, 1 = default)

📓 Explore with Our Notebook

A ready-to-run Jupyter Notebook demonstrates:

• —Loading the dataset from Hugging Face
• —Performing credit risk analysis with ML models
• —Evaluating performance (accuracy, precision, recall)
• —How to generate synthetic data for custom scenarios using the Syncora API

👉 Open the Notebook

🚀 Generate Your Own Dataset

Need a dataset for a different scenario? Create your own synthetic data for financial AI or dataset for LLM training with our API:

👉 Generate synthetic data via Syncora API

⚡ Quick Start

from datasets import load_dataset

dataset = load_dataset("syncora/synthetic_credit_card_default")
df = dataset["train"].to_pandas()
print(df.head())