From 77716e1a8354ba40d9d758bda76c87622aba7945 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Fabiana=20=F0=9F=9A=80=20=20Campanari?= Date: Sat, 5 Oct 2024 08:03:32 -0300 Subject: [PATCH] Update README.md MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Signed-off-by: Fabiana 🚀 Campanari --- README.md | 9 ++++----- 1 file changed, 4 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 2c50e2d..7bf1673 100644 --- a/README.md +++ b/README.md @@ -15,14 +15,13 @@ Credit card default prediction involves using analytical approaches, such as dat
-1. **Utilizing Alternative Variables**: Beyond traditional variables like income, assets, and payment history, incorporating geographical, behavioral, and consumption data can provide valuable insights into a customer's profile. +1. **Incorporating Alternative Variables**: Adding geographical, behavioral, and consumption data to traditional factors like income, assets, and payment history enhances customer profiling. -2. **Individual Credit Scoring**: Treating credit scores at an individual level to better assess risk. +2. **Individual Credit Scoring**: Evaluating credit scores on an individual basis for improved risk assessment. -3. **Behavioral Profile Analysis**: Analyzing customer behavior to predict potential defaults. - -This approach helps financial institutions improve their credit granting processes and manage risk more effectively. +3. **Behavioral Profile Analysis**: Assessing customer behavior to forecast potential defaults. +This strategy enables financial institutions to refine their credit granting processes and manage risk more efficiently. ## **Table of Contents**