Work

Credit Card Application Management System

Year: 2025

Type: article

Abstract: In the modern banking industry, efficient and accurate credit card application processing is crucial. Traditional methods rely heavily on manual verification and rule based systems, which can be time-consuming and prone to errors. This research explores the use of machine learning (ML) techniques to improve the accuracy and efficiency of credit card application management. Various ML algorithms, including decision trees, logistic regression, and neural networks, are analyzed for their predictive capabilities in determining the creditworthiness of applicants. The study demonstrates how ML can enhance decision-making, reduce fraud, and streamline the application process.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.15108210

Authors: Aren, Harshit, Singh, Ambuj, Kumar, Joney

Language: English

Topic: Financial Distress and Bankruptcy Prediction

Subfield: Accounting

Field: Business, Management and Accounting

Domain: Social Sciences

Open Access status: green

OpenAlex ID: W6931115926

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