System Requirements Document

1. Introduction

The "Credit Lander" project aims to automate the hospital emergency lending process using AI technology. This initiative will enhance the efficiency and consistency of lending decisions by integrating an AI-assisted loan decision engine with existing CRM systems. The project is designed to reduce manual effort, improve risk assessment, and maintain human oversight for uncertain applications. Additionally, a graphical interface component will be developed to enhance user interaction and visualization.

2. System Overview

The Credit Lander system will integrate with partner hospitals' existing CRM platforms to automate the loan approval process. The system will utilize AI models to assess risk, provide loan scoring, and offer approval recommendations. It will also include modules for uncertainty detection, lending analytics, and budget control, all accessible through an admin portal.

3. Functional Requirements

• As a User, I should be able to submit emergency funding requests via a QR code.
• As an Admin, I should be able to review loan requests manually when flagged by the system.
• As an Admin, I should be able to configure approval thresholds for auto-approve, auto-reject, and manual review.
• As an Admin, I should be able to access lending analytics and performance reports.
• As an Admin, I should be able to manage daily and monthly lending limits through a dedicated budget control system.
• As a System, I should be able to integrate with existing CRM systems to retrieve and update loan applications.
• As a System, I should provide risk scores using a machine learning-based risk scoring model.
• As a System, I should detect uncertainty in loan applications and flag them for manual review.
• As a System, I should provide an interactive galaxy map for visualizing loan applications.
• As a System, I should support up to 10,000 loan applications per day.
• As a System, I should ensure the AI model provides risk scores with 95% accuracy.
• As a System, I should load the admin portal within 3 seconds on standard internet connections.
• As a Project Manager, I should be able to track the effective duration of the project to ensure timely delivery.
• As a User, I should be able to interact with a graphical interface for enhanced visualization and interaction.

4. User Personas

• User: Individuals submitting emergency funding requests.
• Admin: Hospital staff responsible for reviewing and managing loan applications and system configurations.
• Project Manager: Responsible for overseeing the project timeline and ensuring timely delivery.

5. Core User Flows

• User Flow: User scans QR code -> submits emergency funding request -> request enters CRM -> Admin reviews request manually -> Admin approves or rejects loan -> Loan is disbursed.
• Admin Flow: Admin configures approval thresholds -> System processes loan applications -> System flags uncertain applications -> Admin reviews flagged applications -> Admin updates system configurations as needed.
• Analytics Flow: Admin accesses analytics dashboard -> reviews lending performance -> adjusts budget controls.

6. Visuals Colors and Theme

• Primary: #1A73E8 (deep blue)
• Primary Light: #E8F0FE (light blue)
• Secondary: #FF6F61 (coral)
• Accent: #FFD700 (gold)
• Highlight: #FFA500 (orange)
• Background: #FFFFFF (white)
• Surface: rgba(240, 248, 255, 0.8) (light azure)
• Text: #333333 (dark gray)
• Text Muted: #777777 (medium gray)
• Border: rgba(200, 200, 200, 0.5) (light gray)

7. Signature Design Concept

Interactive Loan Decision Galaxy: The homepage will feature an interactive galaxy map where each star represents a loan application. Users can click on a star to open a detailed view of the application, including risk scores and recommendations. Dragging the galaxy will rotate the cluster, and hovering over stars will highlight connections between similar applications. This concept will be brought to life using @react-three/fiber and @react-three/drei for 3D visualization, with gsap for smooth animations and transitions.

8. Interaction Model & Motion Direction

• The landing page will utilize a "parallax" interaction model to create a visually rich first impression. Layers of stars and galaxies will translate at different speeds as users scroll, providing depth and engagement.
• Internal pages, such as the admin portal, will adopt a "static" model for clarity and ease of use.

9. Non-Functional Requirements

• The system must handle up to 10,000 loan applications per day.
• The AI model should provide risk scores with 95% accuracy.
• The admin portal should load within 3 seconds on standard internet connections.

10. Tech Stack

• Frontend: React.js
• Backend: Python, FastAPI
• Database: MySQL or MariaDB
• AI Models: Machine Learning models for risk scoring
• Local Orchestration: Docker, docker-compose
• Server-side Orchestration: Kubernetes

11. Assumptions and Constraints

• The system will integrate with existing CRM systems via APIs.
• AI models will require periodic retraining with new data.
• The project will adhere to data privacy regulations applicable in India.

12. Glossary

• CRM: Customer Relationship Management
• AI: Artificial Intelligence
• AUC: Area Under the Curve (a measure of model performance)
• API: Application Programming Interface

This document outlines the system requirements for the Credit Lander project, ensuring a comprehensive approach to automating hospital emergency lending with AI.