---
title: synthetic_credit_card_default
canonical_url: "https://www.modelscope.cn/datasets/syncora/synthetic_credit_card_default"
md_url: "https://www.modelscope.cn/datasets/syncora/synthetic_credit_card_default.md"
repository: syncora/synthetic_credit_card_default
last_updated: 2025-08-30
license: apache-2.0
storage_size: "13 MB"
downloads: 149
stars: 0
---

# synthetic_credit_card_default

> synthetic_credit_card_default - syncora 在 ModelScope 开源的数据集。Synthetic Credit Card Default Dataset

syncora/synthetic_credit_card_default 是 ModelScope 魔搭社区上的数据集，存储大小 13 MB，采用 apache-2.0 许可。

- **Repository**: syncora/synthetic_credit_card_default
- **License**: apache-2.0
- **Storage size**: 13 MB
- **Downloads**: 149
- **Stars**: 0
- **Last updated**: 2025-08-30

Source: https://www.modelscope.cn/datasets/syncora/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](https://huggingface.co/datasets/syncora/synthetic_credit_card_default/blob/main/UCI_Syncora_Synthetic.csv)
- ✅ **Jupyter Notebook for Analysis & Modeling** → [Open Notebook](https://huggingface.co/datasets/syncora/synthetic_credit_card_default/blob/main/UCI_Syncora_Synthetic.ipynb)
- ✅ **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

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## 🔍 Features

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

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## 📓 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](https://huggingface.co/datasets/syncora/synthetic_credit_card_default/blob/main/UCI_Syncora_Synthetic.ipynb)

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## 🚀 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](https://app.syncora.ai)

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## ⚡ Quick Start

```python
from datasets import load_dataset

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