Portfolio Analytics Dashboard
Project Overview
An interactive dashboard for real-time portfolio performance analysis in the London specialty insurance market, providing actionable insights for portfolio managers and underwriters.
Features
1. Real-time Analytics
- Live portfolio performance metrics
- Dynamic risk exposure analysis
- Automated data updates
- Customizable views
2. Interactive Visualizations
# Example dashboard component
import streamlit as st
import plotly.express as px
def create_portfolio_heatmap(data):
fig = px.imshow(
data,
labels=dict(x="Risk Category", y="Portfolio Segment"),
title="Portfolio Risk Heatmap"
)
return fig
def render_dashboard():
st.title("Portfolio Analytics Dashboard")
# Portfolio Overview
st.header("Portfolio Overview")
portfolio_metrics = calculate_portfolio_metrics()
display_metrics(portfolio_metrics)
# Risk Analysis
st.header("Risk Analysis")
risk_data = get_risk_data()
st.plotly_chart(create_portfolio_heatmap(risk_data))
3. Key Metrics
- Loss ratio trends
- Premium analysis
- Risk concentration
- Portfolio diversification
Technical Stack
Frontend
- Streamlit
- Plotly
- Altair
- Custom CSS
Backend
- Python
- Pandas
- NumPy
- SQLAlchemy
Data Sources
- Internal databases
- Market data feeds
- Claims systems
- External APIs
Implementation Details
Data Pipeline
- Data Collection
- Automated ETL processes
- Real-time data streaming
- Data validation
- Processing
- Risk calculations
- Performance metrics
- Trend analysis
- Visualization
- Interactive charts
- Custom reports
- Export capabilities
Security Features
- Role-based access control
- Data encryption
- Audit logging
- Secure API endpoints
Business Impact
- 60% reduction in report generation time
- 45% improvement in decision-making speed
- 30% increase in portfolio efficiency
- Enhanced risk management capabilities
Future Roadmap
- Machine learning integration
- Predictive analytics
- Mobile optimization
- API development