E3S Web of Conf.
Volume 389, 2023Ural Environmental Science Forum “Sustainable Development of Industrial Region” (UESF-2023)
|Number of page(s)||9|
|Section||Environmental Policy and Economics|
|Published online||31 May 2023|
Implementation of Business intelligence in Know Your Customer (KYC) for credit card customers’ loan repayment status
Asia Pacific University, Jalan Teknologi 5, Taman Teknologi Malaysia, 57000 Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia
* Corresponding author: email@example.com
Nowadays, the increasing technological improvements followed by data demand made businesses and organizations follow these improvements to continue operating. The Know Your Customer (KYC) assessment is still manually done, followed by the growing amount of data, resulting in data accumulation and affecting the time organizations spend analyzing the prospective applicant data. The unavailability of tools that can help review documents and data leads to more data accumulation and timeconsuming KYC assessments. This paper aims to create a Business Intelligence (BI) system to help financial organizations analyze, process applicant data, and determine applicants’ eligibility who are willing to get credit card services. This paper may be utilized by an enterprise operating in the financial sector that follows the KYC procedure to identify applicants who require credit card services. The development of BI systems is predicted to help reduce the time spent to validate application data, particularly in the banking or financial industry. This study has designed three dimension tables and a fact table using Microsoft SQL Server 18 for the data warehouse. Pentaho Data Integration is used for the ETL process, and Tableau creates the dashboard. The dashboard contains general information and the loan repayment status of an applicant. Two pivot tables were created using Microsoft Excel to summarize the loan repayment status of an applicant.
Key words: Business Intelligence / Know Your Customer / Loan Repayment / Credit Card / ETL Process / Tableau
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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