Bnco is an advanced banking web application designed specifically for business owners to manage their assets, liabilities & equity efficiently, and perform financial forecasting. It boasts a suite of powerful features:

• Asset, Liability, and Equity Management: Comprehensive tools to track and manage financial data.
• Statistical Reporting: Advanced reporting capabilities to generate insightful statistical reports.
• Credit Risk Modeling: Utilizes regression models for credit risk assessment, aiding in informed decision-making.
• Customer Support: Bnco's chatbot offers 24/7 customer support.

Continuous Integration/Continuous Deployment (CI/CD): Bnco is implemented for streamlined and automated updates.

• Bnco is developed using Django REST Framework for high interoperability.

• Crafted in React.js with TypeScript, Bnco offers a dynamic and responsive user interface. Integrated with MaterialUI for a sleek, modern design.

• Large Scale Data Handling: Developed a PostgreSQL script for efficiently populating the database with 1,000,000+ entities.

• Credit Risk Modeling: Implemented regression models for real-time analysis of PD (Probability of Default), LGD (Loss Given Default), and EAD (Exposure at Default). The models provided valuable insights into the creditworthiness of borrowers, aiding in risk assessment and decision-making processes.

• Bnco is containerized using Docker, ensuring consistency across different development and production environments.
• Utilized Kubernetes for orchestrating containerized applications, enhancing scalability and reliability.

• Implemented JWT token-based authentication, ensuring secure access control across different user roles (admin, moderator, regular user).
• Secure setup with an Nginx reverse proxy server and Gunicorn, ensuring encryption with SSL.

• Integrated a chatbot using WebSockets, allowing real-time communication within the app.

• Implemented comprehensive E2E testing to verify the integrated components of the application.
• Conducted stress tests, using JMeter, with detailed graphs illustrating the app's performance under various loads.