Available

Loan Default Prediction in Bank

Loan Default Prediction in Bank

Loan Default Prediction in Bank

HELP University

4 weeks

Machine Learning

HELP University

4 weeks

Machine Learning

HELP University

4 weeks

Machine Learning

Bookease Portfolio in Framer
Bookease Portfolio in Framer
Bookease Portfolio in Framer

Colaborators

Project Overview

BDA Bank addresses loan approval challenges through data mining, employing preprocessing to refine data and utilizing clustering and predictive models to enhance applicant assessment.

Objective

Enhance loan approval accuracy at BDA Bank by applying data preprocessing techniques and comparing predictive models, ultimately identifying the most effective approach for assessing borrower risk.

Skills & Tools

Project Overview

BDA Bank addresses loan approval challenges through data mining, employing preprocessing to refine data and utilizing clustering and predictive models to enhance applicant assessment.

Objective

Enhance loan approval accuracy at BDA Bank by applying data preprocessing techniques and comparing predictive models, ultimately identifying the most effective approach for assessing borrower risk.

Skills & Tools

Project Overview

BDA Bank addresses loan approval challenges through data mining, employing preprocessing to refine data and utilizing clustering and predictive models to enhance applicant assessment.

Objective

Enhance loan approval accuracy at BDA Bank by applying data preprocessing techniques and comparing predictive models, ultimately identifying the most effective approach for assessing borrower risk.

Skills & Tools

Outcomes

The project successfully utilizes clustering to identify borrower patterns and determines that regression is the optimal predictive model, providing BDA Bank with an efficient method to assess loan applicants and improve approval accuracy.

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Made by

Bavenraj

in

© Copyright 2024. All rights Reserved.

Made by

Bavenraj

in

Available for Work

Available for Work