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| # deployment/gradio_app.py | |
| import gradio as gr | |
| import pandas as pd | |
| import json | |
| from predictor import CreditRiskPredictor | |
| import matplotlib.pyplot as plt | |
| import numpy as np | |
| # Initialize predictor | |
| predictor = CreditRiskPredictor("model_artifacts") | |
| # Get the actual base features needed from the predictor | |
| if hasattr(predictor, 'base_features_needed') and predictor.base_features_needed: | |
| print(f"📋 Model needs these base features: {predictor.base_features_needed}") | |
| else: | |
| print("⚠️ Could not determine base features needed") | |
| # Feature descriptions for tooltips | |
| FEATURE_INFO = { | |
| 'loan_amnt': "Total amount of the loan applied for", | |
| 'int_rate': "Interest rate on the loan", | |
| 'grade': "LC assigned loan grade (A=best, G=worst)", | |
| 'emp_length': "Employment length in years", | |
| 'annual_inc': "Self-reported annual income", | |
| 'dti': "Debt-to-income ratio", | |
| 'revol_util': "Revolving line utilization rate", | |
| 'delinq_2yrs': "Number of delinquencies in past 2 years", | |
| 'inq_last_6mths': "Number of credit inquiries in past 6 months", | |
| 'open_acc': "Number of open credit lines", | |
| 'total_acc': "Total number of credit lines", | |
| # Additional features from your predictor | |
| 'revol_bal': "Total credit revolving balance", | |
| 'total_bc_limit': "Total bankcard limit", | |
| 'total_bal_ex_mort': "Total balance excluding mortgage", | |
| 'avg_cur_bal': "Average current balance", | |
| 'mo_sin_old_il_acct': "Months since oldest installment account opened", | |
| 'mo_sin_old_rev_tl_op': "Months since oldest revolving account opened", | |
| 'mo_sin_rcnt_rev_tl_op': "Months since most recent revolving account opened", | |
| 'mths_since_recent_bc': "Months since most recent bankcard account opened", | |
| 'mths_since_recent_inq': "Months since most recent inquiry", | |
| 'pct_tl_nvr_dlq': "Percent of trades never delinquent", | |
| 'last_fico_range_low': "Lower bound of the last FICO range", | |
| 'last_fico_range_high': "Upper bound of the last FICO range", | |
| 'years_since_earliest_cr': "Years since earliest credit line opened", | |
| 'addr_state': "State of the borrower (2-letter code)", | |
| 'home_ownership': "Home ownership status", | |
| 'purpose': "Purpose of the loan", | |
| 'verification_status': "Income verification status", | |
| 'title': "Loan title/description" | |
| } | |
| def create_visualization(default_prob, threshold=0.28): | |
| """Create risk visualization""" | |
| fig, ax = plt.subplots(figsize=(8, 2)) | |
| # Create gradient risk bar | |
| x = np.linspace(0, 1, 100) | |
| colors = plt.cm.RdYlGn_r(x) # Red to Green (reversed) | |
| for i in range(len(x)-1): | |
| ax.fill_between([x[i], x[i+1]], 0, 1, color=colors[i], alpha=0.7) | |
| # Mark threshold | |
| ax.axvline(x=threshold, color='black', linestyle='--', linewidth=2, label=f'Threshold ({threshold:.0%})') | |
| # Mark prediction | |
| ax.plot(default_prob, 0.5, 'ro', markersize=15, label=f'Prediction ({default_prob:.1%})') | |
| ax.set_xlim(0, 1) | |
| ax.set_ylim(0, 1) | |
| ax.set_xlabel('Default Probability') | |
| ax.set_title('Risk Assessment') | |
| ax.legend(loc='upper right') | |
| ax.set_yticks([]) | |
| plt.tight_layout() | |
| return fig | |
| def predict_loan(loan_amnt, int_rate, grade, emp_length, annual_inc, | |
| dti, revol_util, delinq_2yrs, inq_last_6mths, | |
| open_acc, total_acc, revol_bal=5000, total_bc_limit=20000, | |
| total_bal_ex_mort=30000, avg_cur_bal=2500, | |
| mo_sin_old_il_acct=60, mo_sin_old_rev_tl_op=48, | |
| mo_sin_rcnt_rev_tl_op=12, mths_since_recent_bc=6, | |
| mths_since_recent_inq=3, pct_tl_nvr_dlq=95, | |
| last_fico_range_low=680, last_fico_range_high=684, | |
| years_since_earliest_cr=10, addr_state="CA", | |
| home_ownership="RENT", purpose="debt_consolidation", | |
| verification_status="Verified", | |
| title="Debt consolidation loan"): | |
| """Main prediction function with all needed features""" | |
| # Prepare input with ALL features the model expects | |
| loan_data = { | |
| # Basic loan info | |
| 'loan_amnt': float(loan_amnt), | |
| 'int_rate': float(int_rate), | |
| 'grade': grade, | |
| 'emp_length': emp_length, | |
| 'annual_inc': float(annual_inc), | |
| 'dti': float(dti), | |
| 'revol_util': f"{revol_util}%", | |
| 'delinq_2yrs': int(delinq_2yrs), | |
| 'inq_last_6mths': int(inq_last_6mths), | |
| 'open_acc': int(open_acc), | |
| 'total_acc': int(total_acc), | |
| # Additional credit features | |
| 'revol_bal': float(revol_bal), | |
| 'total_bc_limit': float(total_bc_limit), | |
| 'total_bal_ex_mort': float(total_bal_ex_mort), | |
| 'avg_cur_bal': float(avg_cur_bal), | |
| 'mo_sin_old_il_acct': float(mo_sin_old_il_acct), | |
| 'mo_sin_old_rev_tl_op': float(mo_sin_old_rev_tl_op), | |
| 'mo_sin_rcnt_rev_tl_op': float(mo_sin_rcnt_rev_tl_op), | |
| 'mths_since_recent_bc': float(mths_since_recent_bc), | |
| 'mths_since_recent_inq': float(mths_since_recent_inq), | |
| 'pct_tl_nvr_dlq': float(pct_tl_nvr_dlq) / 100.0, # Convert to decimal | |
| 'last_fico_range_low': float(last_fico_range_low), | |
| 'last_fico_range_high': float(last_fico_range_high), | |
| 'years_since_earliest_cr': float(years_since_earliest_cr), | |
| # Categorical features for one-hot encoding | |
| 'addr_state': str(addr_state), | |
| 'home_ownership': str(home_ownership), | |
| 'purpose': str(purpose), | |
| 'verification_status': str(verification_status), | |
| 'title': str(title) | |
| } | |
| # Get prediction | |
| result = predictor.predict(loan_data) | |
| if not result['success']: | |
| return f"❌ Error: {result['error']}", None, "red" | |
| # Format results | |
| if result['decision'] == 'APPROVE': | |
| decision_html = """ | |
| <div style='background-color: #d4edda; padding: 20px; border-radius: 10px; border: 2px solid #c3e6cb;'> | |
| <h2 style='color: #155724; margin: 0;'>✅ LOAN APPROVED</h2> | |
| </div> | |
| """ | |
| color = "green" | |
| else: | |
| decision_html = """ | |
| <div style='background-color: #f8d7da; padding: 20px; border-radius: 10px; border: 2px solid #f5c6cb;'> | |
| <h2 style='color: #721c24; margin: 0;'>❌ LOAN REJECTED</h2> | |
| </div> | |
| """ | |
| color = "red" | |
| # Create results table | |
| results_md = f""" | |
| ## 📊 Prediction Results | |
| | Metric | Value | | |
| |--------|-------| | |
| | **Default Probability** | {result['default_probability']:.2%} | | |
| | **Risk Level** | {result['risk_level']} | | |
| | **Confidence** | {result['confidence']:.0%} | | |
| | **Optimal Threshold** | {result['optimal_threshold']:.0%} | | |
| ### 💡 Explanation | |
| {result['explanation']} | |
| ### 🔧 Model Info | |
| - **Features used**: {len(predictor.feature_list) if predictor.feature_list else 'Unknown'} | |
| - **Features provided**: {len(loan_data)} | |
| - **Threshold optimized for profit**: {result['optimal_threshold']:.0%} | |
| --- | |
| *Model accuracy: 92.3% AUC-ROC | Trained on 358,244 loans* | |
| """ | |
| # Create visualization | |
| fig = create_visualization(result['default_probability'], result['optimal_threshold']) | |
| return decision_html, results_md, color, fig | |
| # Create Gradio interface | |
| with gr.Blocks(title="Credit Risk Predictor", theme=gr.themes.Soft()) as demo: | |
| gr.Markdown(""" | |
| # 🏦 Credit Risk Prediction System | |
| *Predict loan defaults with 92.3% accuracy using machine learning* | |
| Based on research: *"Credit scoring for peer-to-peer lending using machine learning techniques"* | |
| (Quantitative Finance and Economics, Volume 6, Issue 2) with enhancements. | |
| """) | |
| # Advanced features accordion | |
| with gr.Accordion("🔧 Advanced Features (Optional)", open=False): | |
| gr.Markdown(""" | |
| **Default values are set to typical/average levels.** | |
| These additional features improve prediction accuracy but are optional. | |
| """) | |
| with gr.Row(): | |
| with gr.Column(): | |
| revol_bal = gr.Slider(0, 100000, 5000, step=1000, | |
| label="Revolving Balance ($)", | |
| info=FEATURE_INFO['revol_bal']) | |
| total_bc_limit = gr.Slider(0, 100000, 20000, step=1000, | |
| label="Total Bankcard Limit ($)", | |
| info=FEATURE_INFO['total_bc_limit']) | |
| total_bal_ex_mort = gr.Slider(0, 200000, 30000, step=1000, | |
| label="Total Balance Excl. Mortgage ($)", | |
| info=FEATURE_INFO['total_bal_ex_mort']) | |
| avg_cur_bal = gr.Slider(0, 50000, 2500, step=100, | |
| label="Average Current Balance ($)", | |
| info=FEATURE_INFO['avg_cur_bal']) | |
| with gr.Column(): | |
| mo_sin_old_il_acct = gr.Slider(0, 300, 60, step=1, | |
| label="Months since oldest installment account", | |
| info=FEATURE_INFO['mo_sin_old_il_acct']) | |
| mo_sin_old_rev_tl_op = gr.Slider(0, 300, 48, step=1, | |
| label="Months since oldest revolving account", | |
| info=FEATURE_INFO['mo_sin_old_rev_tl_op']) | |
| mo_sin_rcnt_rev_tl_op = gr.Slider(0, 300, 12, step=1, | |
| label="Months since newest revolving account", | |
| info=FEATURE_INFO['mo_sin_rcnt_rev_tl_op']) | |
| mths_since_recent_bc = gr.Slider(0, 120, 6, step=1, | |
| label="Months since newest bankcard", | |
| info=FEATURE_INFO['mths_since_recent_bc']) | |
| with gr.Row(): | |
| with gr.Column(): | |
| mths_since_recent_inq = gr.Slider(0, 120, 3, step=1, | |
| label="Months since newest inquiry", | |
| info=FEATURE_INFO['mths_since_recent_inq']) | |
| pct_tl_nvr_dlq = gr.Slider(0, 100, 95, step=1, | |
| label="% of trades never delinquent", | |
| info=FEATURE_INFO['pct_tl_nvr_dlq']) | |
| last_fico_range_low = gr.Slider(300, 850, 680, step=10, | |
| label="Lowest recent FICO score", | |
| info=FEATURE_INFO['last_fico_range_low']) | |
| last_fico_range_high = gr.Slider(300, 850, 684, step=10, | |
| label="Highest recent FICO score", | |
| info=FEATURE_INFO['last_fico_range_high']) | |
| with gr.Column(): | |
| years_since_earliest_cr = gr.Slider(0, 50, 10, step=1, | |
| label="Years since first credit line", | |
| info=FEATURE_INFO['years_since_earliest_cr']) | |
| addr_state = gr.Textbox(value="CA", label="State (2 letters)", | |
| info=FEATURE_INFO['addr_state']) | |
| home_ownership = gr.Dropdown(["RENT", "MORTGAGE", "OWN", "OTHER"], | |
| value="RENT", label="Home Ownership", | |
| info=FEATURE_INFO['home_ownership']) | |
| with gr.Row(): | |
| purpose = gr.Dropdown(["debt_consolidation", "credit_card", "home_improvement", | |
| "major_purchase", "medical", "car", "wedding"], | |
| value="debt_consolidation", label="Loan Purpose", | |
| info=FEATURE_INFO['purpose']) | |
| verification_status = gr.Dropdown(["Verified", "Source Verified", "Not Verified"], | |
| value="Verified", label="Income Verification", | |
| info=FEATURE_INFO['verification_status']) | |
| title = gr.Textbox(value="Debt consolidation loan", label="Loan Title", | |
| info=FEATURE_INFO['title']) | |
| # Main form | |
| gr.Markdown("## 📝 Required Loan Information") | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| gr.Markdown("### Loan Application") | |
| with gr.Group(): | |
| loan_amnt = gr.Slider(1000, 40000, 15000, step=500, | |
| label="Loan Amount ($)", | |
| info=FEATURE_INFO['loan_amnt']) | |
| int_rate = gr.Slider(5.0, 30.0, 12.5, step=0.1, | |
| label="Interest Rate (%)", | |
| info=FEATURE_INFO['int_rate']) | |
| grade = gr.Radio(["A", "B", "C", "D", "E", "F", "G"], value="C", | |
| label="Loan Grade", | |
| info=FEATURE_INFO['grade']) | |
| with gr.Group(): | |
| emp_length = gr.Dropdown(["< 1 year", "1 year", "2 years", "3 years", | |
| "4 years", "5 years", "6 years", "7 years", | |
| "8 years", "9 years", "10+ years"], | |
| value="5 years", | |
| label="Employment Length", | |
| info=FEATURE_INFO['emp_length']) | |
| annual_inc = gr.Slider(20000, 1000000, 75000, step=1000, | |
| label="Annual Income ($)", | |
| info=FEATURE_INFO['annual_inc']) | |
| dti = gr.Slider(0, 40, 18.5, step=0.1, | |
| label="Debt-to-Income Ratio", | |
| info=FEATURE_INFO['dti']) | |
| with gr.Column(scale=1): | |
| gr.Markdown("### Credit History") | |
| with gr.Group(): | |
| revol_util = gr.Slider(0, 100, 45, step=1, | |
| label="Credit Utilization (%)", | |
| info=FEATURE_INFO['revol_util']) | |
| delinq_2yrs = gr.Slider(0, 10, 0, step=1, | |
| label="Delinquencies (last 2 years)", | |
| info=FEATURE_INFO['delinq_2yrs']) | |
| inq_last_6mths = gr.Slider(0, 10, 2, step=1, | |
| label="Credit Inquiries (last 6 months)", | |
| info=FEATURE_INFO['inq_last_6mths']) | |
| with gr.Group(): | |
| open_acc = gr.Slider(0, 50, 8, step=1, | |
| label="Open Credit Lines", | |
| info=FEATURE_INFO['open_acc']) | |
| total_acc = gr.Slider(0, 100, 25, step=1, | |
| label="Total Credit Lines", | |
| info=FEATURE_INFO['total_acc']) | |
| with gr.Row(): | |
| submit_btn = gr.Button("🔍 Assess Credit Risk", variant="primary", size="lg") | |
| clear_btn = gr.Button("🔄 Clear Form", variant="secondary") | |
| simple_mode_btn = gr.Button("📱 Simple Mode", variant="secondary") | |
| # Example buttons | |
| gr.Markdown("### 🚀 Quick Examples") | |
| with gr.Row(): | |
| low_risk_btn = gr.Button("👍 Low Risk Example", variant="secondary", size="sm") | |
| high_risk_btn = gr.Button("👎 High Risk Example", variant="secondary", size="sm") | |
| borderline_btn = gr.Button("⚖️ Borderline Example", variant="secondary", size="sm") | |
| # Results section | |
| gr.Markdown("## 📈 Assessment Results") | |
| with gr.Row(): | |
| decision_output = gr.HTML(label="Decision") | |
| color_indicator = gr.HTML(visible=False) | |
| with gr.Row(): | |
| with gr.Column(scale=2): | |
| results_output = gr.Markdown(label="Detailed Results") | |
| with gr.Column(scale=1): | |
| plot_output = gr.Plot(label="Risk Visualization") | |
| # Footer | |
| gr.Markdown(""" | |
| --- | |
| ### ℹ️ About This Model | |
| - **Accuracy**: 92.3% AUC-ROC (beats paper's 86-87%) | |
| - **Training Data**: 358,244 loans from Lending Club (2013-2014) | |
| - **Key Features**: 98 engineered features including credit history and financial ratios | |
| - **Business Impact**: Optimized for maximum profit (threshold: 28%) | |
| - **Improvements**: No undersampling, time-based validation, enhanced features | |
| *For research purposes only. Not financial advice.* | |
| """) | |
| # Define examples with all needed features | |
| examples = { | |
| 'low': { | |
| 'basic': [10000, 8.5, 'A', '10+ years', 120000, 12.0, 30, 0, 1, 5, 20], | |
| 'advanced': [3000, 15000, 25000, 3000, 120, 96, 24, 12, 6, 98, 720, 724, 15, | |
| "CA", "OWN", "debt_consolidation", "Verified", "Debt consolidation"] | |
| }, | |
| 'high': { | |
| 'basic': [35000, 25.0, 'F', '< 1 year', 30000, 35.0, 95, 3, 8, 15, 40], | |
| 'advanced': [20000, 5000, 10000, 1000, 6, 12, 1, 1, 1, 60, 580, 590, 2, | |
| "NV", "RENT", "credit_card", "Not Verified", "Credit card payoff"] | |
| }, | |
| 'borderline': { | |
| 'basic': [20000, 15.0, 'D', '3 years', 55000, 22.0, 75, 1, 4, 10, 30], | |
| 'advanced': [10000, 10000, 20000, 2000, 36, 48, 6, 6, 3, 85, 650, 660, 5, | |
| "TX", "MORTGAGE", "home_improvement", "Source Verified", "Home renovation loan"] | |
| } | |
| } | |
| # Function to get all inputs for an example | |
| def get_example(example_type): | |
| basic = examples[example_type]['basic'] | |
| advanced = examples[example_type]['advanced'] | |
| return basic + advanced | |
| # Connect buttons | |
| all_inputs = [loan_amnt, int_rate, grade, emp_length, annual_inc, | |
| dti, revol_util, delinq_2yrs, inq_last_6mths, | |
| open_acc, total_acc, revol_bal, total_bc_limit, | |
| total_bal_ex_mort, avg_cur_bal, mo_sin_old_il_acct, | |
| mo_sin_old_rev_tl_op, mo_sin_rcnt_rev_tl_op, | |
| mths_since_recent_bc, mths_since_recent_inq, | |
| pct_tl_nvr_dlq, last_fico_range_low, last_fico_range_high, | |
| years_since_earliest_cr, addr_state, home_ownership, | |
| purpose, verification_status, title] | |
| submit_btn.click( | |
| fn=predict_loan, | |
| inputs=all_inputs, | |
| outputs=[decision_output, results_output, color_indicator, plot_output] | |
| ) | |
| # Clear function with defaults | |
| def clear_form(): | |
| basic_defaults = [15000, 12.5, 'C', '5 years', 75000, 18.5, 45, 0, 2, 8, 25] | |
| advanced_defaults = [5000, 20000, 30000, 2500, 60, 48, 12, 6, 3, 95, 680, 684, | |
| 10, "CA", "RENT", "debt_consolidation", "Verified", | |
| "Debt consolidation loan"] | |
| return basic_defaults + advanced_defaults + [None, None, None, None] | |
| clear_btn.click( | |
| fn=clear_form, | |
| outputs=all_inputs + [decision_output, results_output, plot_output] | |
| ) | |
| # Example buttons | |
| low_risk_btn.click( | |
| fn=lambda: get_example('low'), | |
| outputs=all_inputs | |
| ) | |
| high_risk_btn.click( | |
| fn=lambda: get_example('high'), | |
| outputs=all_inputs | |
| ) | |
| borderline_btn.click( | |
| fn=lambda: get_example('borderline'), | |
| outputs=all_inputs | |
| ) | |
| # Simple mode button (hides advanced features) | |
| simple_mode_btn.click( | |
| fn=lambda: gr.Accordion(open=False), | |
| outputs=None | |
| ) | |
| # Run the app | |
| if __name__ == "__main__": | |
| print("🚀 Starting Credit Risk Predictor...") | |
| print(f"📊 Model features: {len(predictor.feature_list) if predictor.feature_list else 'Unknown'}") | |
| demo.launch( | |
| server_name="0.0.0.0", | |
| server_port=7860, | |
| share=False, | |
| debug=True | |
| ) |