/Artificial-Intelligence-for-Banking

This project contains codes and notebooks related to various use cases for banking.

Primary LanguageJupyter Notebook

Introduction

All artificial intelligence for banking and finance codes sit in this repository. It consists of four parts:

  1. Fraud detection
  2. Recommendation
  3. CLV
  4. Churn Prediction

Folder structure

The following folder structure has been followed and consists of the following:
01_code - Codes related to all the solution cases are part of this folder
02_models - All saved model and weight files are in this folder (JSON and H5)
03_ipy_notebooks - All ipython notebooks pertaining to the solution are part of this folder
04_documents - All documents related to this solution are in this folder.
05_visualization - All PBIX files are in this folder
98_references - All references used are in this folder
99_sample_data - All sample data are in this folder

** Please follow the same naming convention in case any new folders are created and add it to this file. **

Build and Test

All the codes run on Python 3.5.

Contribute

You can add to this project by creating a different branch and push the resources on it if you think you have substantial changes to the existing code.

If you want to learn more about creating good readme files then refer the following guidelines. You can also seek inspiration from the below readme files: