From 93b6932e51328fa3915617d00161e20b4c417c22 Mon Sep 17 00:00:00 2001 From: Hugo Hiraoka Date: Mon, 18 Mar 2024 18:11:42 -0400 Subject: [PATCH] Update README.md Updated wording --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 2222225..86e4547 100644 --- a/README.md +++ b/README.md @@ -6,11 +6,11 @@ Classification models to predict credt card customer attrition using Logistic Re ### Context -Thera Bank has seen a steep decline in the number of users of its credit cards. Like other banks, credit cards are also a good source of income for Thera Bank because they generate revenue by collecting annual fees, balance transfer fees, cash advance fees, late payment fees, foreign transaction fees, and others. +First National Bank has seen a steep decline in the number of users of its credit cards. Like other banks, credit cards are also a good source of income for Thera Bank because they generate revenue by collecting annual fees, balance transfer fees, cash advance fees, late payment fees, foreign transaction fees, and others. When a credit card customer leaves, the bank will lose that revenue source, so it is very important that the bank implements measures to avoid losing those customers. -To achieve this, we will implement a classification model that will help Thera Bank improve its services so credit card customers do not leave the service. +To achieve this, we will implement a classification model that will help First National Bank improve its services so credit card customers do not leave the service. Finally, we will generate a set of insights and recommendations that will help the bank reduce credit card customer churn.