# Project export: Credit Score Predictor
This document was generated by HackStack to give an AI agent context about a hackathon project. Sections are labeled with their provenance; content marked as truncated was cut to keep this document small.
## Project metadata
- Hackathon: Cal Hacks 11.0
- Tagline: This project forecasts future credit scores using AI, helping lenders and insurers offer better rates and assess risks while allowing clients to access more competitive financial products.
- Devpost: https://devpost.com/software/credit-score-predictor
- GitHub: https://github.com/alanrodgz/credit-score-estimator
- Team: 3 GitHub contributor(s) — 17wolfgwang (3 commits), Alan Rodriguez (2 commits), davidrlzzz (1 commits)
## Devpost submission (written by the team)
### Inspiration
Wanting to access higher financial products as a responsible young professional.
### What it does
Generates a projection of a person's future creditworthiness based on past and current financial habits.
## README (from the GitHub repository)
# Credit Score Estimator
## Overview
The Credit Score Estimator is a web application that allows users to estimate their credit score based on key financial factors. This project uses Java with Spring Boot to create a simple, user-friendly interface for credit score estimation.
## Features
- Web-based interface for inputting financial data
- Server-side processing of credit score estimation
- Responsive design for use on various devices
## Prerequisites
Before you begin, ensure you have met the following requirements:
- Java Development Kit (JDK) 11 or higher
- Maven 3.6 or higher
- Git (for version control)
## Installation
To install the Credit Score Estimator, follow these steps:
1. Clone the repository:
```
git clone https://github.com/yourusername/credit-score-estimator.git
```
2. Navigate to the project directory:
```
cd credit-score-estimator
```
3. Build the project using Maven:
```
mvn clean package
```
## Usage
To run the Credit Score Estimator:
1. Start the application:
```
java -jar target/credit-score-estimator-1.0-SNAPSHOT.jar
```
2. Open a web browser and go to `http://localhost:8080`
3. Fill in the required information:
- Annual Income
- Monthly Debt
- Credit History (in years)
4. Click "Calculate" to see your estimated credit score
## Project Structure
## Detected evidence (automated analysis)
Indexed codebase: 6 recognized source files, 5 KB.
- CSS (language) — detected in the code
- Express (technology) — detected in the code
- HTML (language) — detected in the code
- JavaScript (language) — detected in the code
- OpenAI (technology) — claimed on Devpost, not found in the code
## Codebase structure (from repository index)
### Files (10 of 10)
```
.env
.gitignore
.vscode/settings.json
app.js
index.js
package.json
public/ai.js
public/index.html
public/styles.css
README.md
```
### Dependencies
- package.json: express@^4.21.1
### Recent commits (newest first)
- Create README.md
- ADD:ai.js, app.js
- ADD:ai.js,app,js
- ADD:app.js, ai.js
- we got postgress, New DB in this B
- first commit
## Key source files (fetched from GitHub, selected and truncated for size)
### package.json
```
{
"name": "calhacks",
"version": "1.0.0",
"main": "index.js",
"scripts": {
"start": "node index.js",
"test": "echo \"Error: no test specified\" && exit 1"
},
"keywords": [],
"author": "",
"license": "ISC",
"description": "",
"dependencies": {
"express": "^4.21.1"
}
}
```
### index.js
```javascript
const express = require('express');
const path = require('path');
const app = express();
const port = 3000;
app.use(express.static('public'));
app.get('/', (req, res) => {
res.sendFile(path.join(__dirname, 'public', 'index.html'));
});
app.listen(port, () => {
console.log(`Server running at http://localhost:${port}`);
});
```
### app.js
```javascript
import express from 'express';
import fetch from 'node-fetch';
import 'dotenv/config';
const app = express();
app.use(express.json());
app.use(express.static('public'));
// OpenAI API 호출하는 엔드포인트
app.post('/api/credit-check', async (req, res) => {
const { userInput } = req.body;
try {
const response = await fetch('https://api.openai.com/v1/chat/completions', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'Authorization': `Bearer ${process.env.OPENAI_API_KEY}`
},
body: JSON.stringify({
model: 'gpt-3.5-turbo',
messages: [
{
role: 'system', content: `
You are a credit evaluation assistant. You only respond to questions related to credit assessments.
Use the following criteria to evaluate creditworthiness:
1. Payment history: If payments are on time for the last 12 months, increase the credit score.
2. Debt ratio: If the debt ratio is below 30%, increase the credit score.
3. Credit history length: Longer than 5 years increases the credit score.
4. New credit inquiries: More than 2 new inquiries in the last 6 months decreases the credit score.
Only respond with a creditworthiness score and short explanation.
`
},
{ role: 'user', content: userInput }
],
max_tokens: 150
})
});
const data = await response.json();
res.json({ result: data.choices[0].message.content }); // 결과를 클라이언트로 반환
} catch (error) {
console.error('Error fetching data from OpenAI API:', error);
res.status(500).json({ error: 'Failed to fetch data from OpenAI API' });
}
});
// 서버 실행
const PORT = process.env.PORT || 3000;
app.listen(PORT, () => {
console.log(`Server running on port ${PORT}`);
});
```
### public/styles.css
```css
body {
font-family: Arial, sans-serif;
line-height: 1.6;
margin: 0;
padding: 20px;
background-color: #f4f4f4;
}
h1 {
color: #333;
}
```
### public/index.html
```html
Credit Evaluation