DESCRIPTIVE ANALYSIS OF CUSTOMER PROFILES OF MICRO WAKAF BANK USING THE 4C APPROACH
Keywords:
Bank Wakaf Mikro, Credit Scoring, Machine Learning, Non-performing FinancingAbstract
The use of machine learning as an automatic and efficient system for predicting and observing changes in welfare for loan customers approved based on credit scoring, as well as the health of BWM institutions, can increase efficiency in program evaluation. Therefore, the author was interested in conducting a descriptive analysis of the customer profiles of Bank Wakaf Mikro using the 4C approach. In this study, the analysis tools used were descriptive quantitative and qualitative analysis as well as linear regression using the SPSS version 25 program. Based on the results of the research and discussion that has been carried out regarding the descriptive analysis of the customer profiles of Micro Waqf Banks with the 4C approach, it can be concluded that the customer profiles with current financing status which is the target customer of Bank Wakaf Mikro namely female gender, age 36-45 years, minimum education D3, type of side business, length of joining BWM 1-2 years, length of business less than 1 year, number of employees more than 5 people, business license already exists, product license already exists, turnover of more than 2 million rupiah per month, loan amount of more than 250 million rupiah, initial capital of 2.5-5 million rupiah, production pattern with tools, manual packaging techniques, marketing and sales digitally or online, as well as existing and routine financial reports.
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