How to Build a Dynamic Credit Analyst Dashboard

Simple Summary

A customizable dashboard for credit analysts that streamlines data visualization and decision-making processes, enhancing efficiency and accuracy in credit risk assessment.

Product Requirements Document (PRD)

Goals:

• Develop a customizable dashboard for credit analysts
• Improve efficiency and accuracy in credit risk assessment
• Provide real-time data visualization and analysis tools

Target Audience:

• Credit analysts in financial institutions
• Risk management teams
• Financial decision-makers

Key Features:

1. Customizable widgets for different credit metrics
2. Real-time data integration from multiple sources
3. Risk scoring and assessment tools
4. Historical data trends and comparisons
5. Collaborative features for team analysis
6. Customizable alerts and notifications
7. Export and reporting capabilities

User Requirements:

• Intuitive interface for easy customization
• Fast loading and real-time updates
• Secure access to sensitive financial data
• Mobile responsiveness for on-the-go analysis
• Integration with existing financial systems

User Flows

1. Dashboard Customization:

   • User logs in
   • Selects "Customize Dashboard" option
   • Chooses widgets from available options
   • Arranges widgets on the dashboard
   • Saves custom layout

2. Risk Assessment:

   • User selects a specific credit application
   • Views relevant metrics and scores
   • Analyzes historical trends
   • Adds notes and recommendations
   • Submits assessment for review

3. Collaborative Analysis:

   • User identifies a complex case
   • Initiates a team collaboration session
   • Shares dashboard view with colleagues
   • Discusses findings in real-time chat
   • Finalizes joint decision

Technical Specifications

Frontend:

• React for building user interface
• Redux for state management
• D3.js for advanced data visualizations
• Material-UI for consistent design components

Backend:

• Node.js with Express for API server
• PostgreSQL for relational data storage
• Redis for caching and real-time features
• RabbitMQ for message queuing

APIs and Integrations:

• RESTful API for data exchange
• WebSocket for real-time updates
• Integration with credit bureaus and financial data providers

Security:

• JWT for authentication
• HTTPS for encrypted data transfer
• Role-based access control (RBAC)

API Endpoints

• POST /api/auth/login
• GET /api/dashboard/widgets
• POST /api/dashboard/layout
• GET /api/credit-applications/:id
• POST /api/risk-assessments
• GET /api/metrics/historical
• POST /api/collaborations/create
• GET /api/alerts

Database Schema

Users:

• id (PK)
• username
• email
• password_hash
• role

Dashboards:

• id (PK)
• user_id (FK)
• layout_json

CreditApplications:

• id (PK)
• applicant_name
• credit_score
• income
• debt_ratio

RiskAssessments:

• id (PK)
• application_id (FK)
• analyst_id (FK)
• score
• notes
• timestamp

Metrics:

• id (PK)
• name
• value
• timestamp

File Structure

Implementation Plan

1. Project Setup (1 week)

   • Initialize React project
   • Set up Node.js backend
   • Configure database and ORM
   • Implement basic authentication

2. Core Dashboard Development (3 weeks)

   • Create customizable dashboard layout
   • Develop reusable widget components
   • Implement drag-and-drop functionality

3. Data Integration and Visualization (2 weeks)

   • Connect to data sources and APIs
   • Implement data processing utilities
   • Create dynamic charts and graphs

4. Risk Assessment Tools (2 weeks)

   • Develop risk scoring algorithms
   • Create assessment forms and workflows
   • Implement historical data comparisons

5. Collaboration Features (1 week)

   • Add real-time collaboration capabilities
   • Implement shared dashboard views
   • Create in-app messaging system

6. Alerts and Notifications (1 week)

   • Develop customizable alert system
   • Implement email and in-app notifications
   • Create notification preferences settings

7. Testing and Refinement (2 weeks)

   • Conduct thorough unit and integration testing
   • Perform user acceptance testing
   • Refine UI/UX based on feedback

8. Deployment and Documentation (1 week)

   • Prepare deployment environment
   • Create user and technical documentation
   • Deploy application to production

Deployment Strategy

1. Set up staging and production environments on cloud platform (e.g., AWS, Google Cloud)
2. Configure CI/CD pipeline using Jenkins or GitLab CI
3. Implement blue-green deployment for zero-downtime updates
4. Use containerization (Docker) for consistent deployments
5. Set up automated database backups and recovery procedures
6. Implement logging and monitoring using ELK stack or similar
7. Configure auto-scaling for handling variable loads
8. Conduct regular security audits and penetration testing

Design Rationale

The design focuses on creating a flexible, powerful tool for credit analysts while ensuring security and efficiency. React was chosen for its component-based architecture, allowing for easy customization of the dashboard. Node.js provides a scalable backend, while PostgreSQL offers robust data management for complex financial information. The use of real-time technologies like WebSockets ensures that analysts always have the most up-to-date information. The modular file structure and implementation plan allow for agile development and easy maintenance. Security measures like JWT and HTTPS are crucial for protecting sensitive financial data. The deployment strategy emphasizes reliability and scalability, essential for a mission-critical financial tool.