The objective is to identify patterns which indicate if a person is likely to default, which may be used for taking actions such as denying the loan, reducing the amount of loan, lending at a higher interest rate, etc.
- General Information
- Technologies Used
- Conclusions
This case study has detailed analysis of leading club. We graphically represent different possibilities of data and explained it in PPT which can be used for taking decision on approving or denying the loan
Based on dataset identify a pattern for make decision on approving and denying loan
The dataset we used contains information about past loan applicants and whether they 'defaulted' or not
We build relationship between different combinations of data and identified defulters pattern based on person's loan amount, annual income, purpose, title, grade, etc
- Anaconda Navigator (v2.4.0)
- Jupyter Notebook (v6.5.2)
- GIT (v2.41.0)
Created by
- Kiruthiga R
- Karthik R [@baskarkarthik]