Development of a machine learning-based system for credit risk assessment
Table Of Contents
- 1.Introduction
- 1.1Background
- 1.2Motivation
- 1.3Objectives
- 2.Literature Review
- 2.1Credit risk assessment methods
- 2.2Machine learning applications in finance
- 3.Data Collection and Preprocessing
- 3.1Data sources
- 3.2Feature selection and engineering
- 4.Machine Learning Model Development
- 4.1Model selection
- 4.2Training and validation
- 5.System Implementation
- 5.1Software architecture
- 5.2User interface design
Thesis Abstract
The project aims to develop a machine learning-based system for credit risk assessment in the financial industry. The system will utilize historical financial data, customer information, and macroeconomic indicators to predict the creditworthiness of loan applicants. By leveraging advanced machine learning algorithms, the system will provide accurate risk assessments, thereby enabling financial institutions to make informed lending decisions and mitigate potential credit losses.
Thesis Overview
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