Predicting the ability of a borrower to pay back the loan through Traditional Machine Learning Models and comparing to Ensembling Methods
-
Updated
Sep 11, 2020 - Jupyter Notebook
Predicting the ability of a borrower to pay back the loan through Traditional Machine Learning Models and comparing to Ensembling Methods
Portfolio of projects
Our group chose this question to bring attention to the little knowledge that young loan applicants have. Based on our findings in our models we explore: Which age group is the least likely to apply for loans? Which group is most likely to default on loans?
Credit risk analysis using scikit-learn and imbalanced-learn.
The project involved developing a credit risk default model on Indian companies using the performance data of several companies to predict whether a company is going to default on upcoming loan payments.
This repository contains projects related to data mining. Data mining finds valuable information hidden in large volumes of data and it is the analysis of data and the use of software techniques for finding patterns and regularities in sets of data.
This work is about "Loan Default Prediction" which is one of the most important and critical problems faced by banks and other financial institutions as it has a huge effect on profit
Predicting how much loan will be approved
Credit risk poses a classification problem that’s inherently imbalanced. Using a dataset of historical lending activity from a peer-to-peer lending services company, build a model that can identify the creditworthiness of borrowers.
Reverse engineering of the FICO algorithm
Credit risk analysis determines a borrower's ability to meet debt obligations and the lender's aim when advancing credit. The goal is to identify patterns that indicate if a person is unlikely to repay the loan or labeled as a bad risk through automated machine learning algorithms.
All Main Projects
Machine Learning pipelines are deployed to accomplish the objective of credit risk analysis.
The aim is to understand which are the key factors for a certain level of credit risk to occur. In addition, some ML models capable to predict the credit risk level for a company in an year - given past years data - have been built and compared.
Credit Risk Analysis using Python
CSCI316 Group assignment 1
This repository contains python code from scratch to develop the credit risk model for loan portfolio
Add a description, image, and links to the credit-risk-analysis topic page so that developers can more easily learn about it.
To associate your repository with the credit-risk-analysis topic, visit your repo's landing page and select "manage topics."