In the banking sector, the loan approval process is critical as it significantly impacts individuals in quick need of financial assistance. I propose a solution utilizing a machine learning algorithm, specifically a Support Vector Machine (SVM), to predict whether a loan can be approved or not.
How Svm helps:
:) Accuracy: SVM is good at correctly predicting whether loans should be approved or not.
:) Handles Lots of Information: It can manage and analyze many details from loan applications, like credit history and income.
:) Prevents Mistakes: SVM is designed to avoid making errors even when dealing with complicated data.
:) Clear Decisions: It makes clear and confident decisions about who gets approved for a loan.
:) Flexible: SVM can adapt to different types of data patterns, helping it understand various relationships in the data.
:) Works with Big Data: It can process large amounts of data, which is common in banking.
Using SVM can make the loan approval process faster and more reliable, helping banks make better decisions.