Bank Offer Booster

Bank Offer Booster is an application dedicated for banks , It's created to solve problem of finding the best offer to their clients, also to help them to detect whether their clients are trustworthy

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Inspiration

The power of data and how we can improve our life with it

What it does

This application has two main function for the moment which are :

  1. Predict whether an offer is beneficial to their clients.
  2. Classify the clients as trustworthy for loans or no. ## How we built it The application has passed by several process:
  3. Collecting dataset for the model training.
  4. Preprocessing data
  5. Training many models and selecting the best one (ANN)
  6. Deploying the model as "tflite"
  7. Designing UI/UX of the application, both for mobile and web version
  8. Building the app using Kotlin
  9. Adding authentication
    ## Challenges we ran into
  10. Finding the problem
  11. Collecting data
  12. Deploying the model ## Accomplishments that we're proud of
  13. New idea in Algeria for now.
  14. Solving the problem with modern technologies
  15. There's satisfying UI/UX design ## What we learned
  16. Problem solving.
  17. UI/ UX design
  18. How to deploy a model as tflite for Android ## What's next for Bank Offer Booster
  19. Adding more features and functionality
  20. Builsing the web version and improve it

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