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EasyClaim

by Ganesh Asapu, Nauhar Kapur, Raunak Madan, Vibhas Raizada, and Caesar Saleh

Consistent Adjudication, Made Easy


Screenshot 2023-12-07 at 9 29 26 PM

Presenting EasyClaim, a platform to streamline and digitize the adjudication process for Securian Canada.

This project was made as part of the Technology Leadership Initative's integrated-industry project at the University of Toronto.

View the deployed project here


Our expected features (WIP):

  • An inbox page to view claims submitted by policyholders
  • A 'historical claims' page to view previous
  • Viewable claims that feature submitted pdf's and a side display listing the main
    • An algorithm that displays claims similar to the claim being currently viewed, and the recommended next steps in the process
    • Assisting in processing claims faster based on precedent

Tech Stack:

  • Frontend in React and Typescript
  • Backend in Spring Boot and Java
  • Database running on Firebase
  • Deployed using Microsoft Azure

Main folder components:

  • backend
    • Contains Folders following th Clean Arhcitecure Engine:
      • Controllers
      • Entity
      • Firebase Initializer
      • Services
    • Spring Boot connection test file
  • dummy_data
    • Completed JSON files for:
      • Disability Claims
      • Employment Claims
      • Life Claims
    • Each JSON file contains count number of mock models based on specific number in json_generator.py
  • frontend
    • An app folder containg:
      • Additional Components frontend file
      • Database 'Historical Claims' page frontend file
      • Inbox page frontend file
  • JSON Models
    • Blank JSON files for:
      • Disability Claims
      • Employment Claims
      • Life Claims
  • json_generator.py
    • Python file use to automatically generate filled out JSON claim mock files

Using json_generator to create JSON mock files:

  1. Open json_generator.py
  2. In the main branch at the bottom of the file, specifiy the count for the number of dummy JSON models you would like
  3. Run the file in your favourite compiler!
  4. Check the dummy_data folder; each file in the folder contains count number of mock models, all placed into one compliation file for each type of claim

Running the program locally:

  1. Install node.js with the command npm i
  2. Get the firebase API key from CaesarSaleh
    • This will be stored in a .env file that should NOT be made public or stored on the GitHub repo!
  3. Run npm run dev in the Terminal
  4. Open http://localhost:3000

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  • TypeScript 57.3%
  • Java 34.9%
  • Python 7.3%
  • Other 0.5%