Homecredit dataset

This project was made as a final project at Rakamin Academy in collaboration with Home Credit Indonesia.

Obejctive project are create a system to help loan assessments automatically & Business Metrics are daily resolved applications and average resolved time

東京大学グローバル消費インテリジェンス寄付講座

Many people struggle to get loans due to insufficient or non-existent credit histories. And, unfortunately, this population is often taken advantage of by untrustworthy lenders. Home Credit strives to broaden financial inclusion for the unbanked population by providing a positive and safe borrowing experience. In order to make sure this underser…

Build a machine learning model that can automatically assess loans with goal to predict client’s repayment abilities and speed up inspection filing without spending more money.

kaggle data-mining competition

My submission for the Home Credit Default Risk Kaggle competition. The objective is to predict how capable each applicant is of repaying a loan.

Explore Home Credit's default risk data using EDA and a Baseline Machine Learning models. Help predict future payment problems for clients, ensuring a positive borrowing experience and empowering financial inclusion

House Prices Prediction and Credit Default Risk Prediction competitions. Advanced decision tree-based regression and classification models are used.