Data Quality Improvement: Case Study Financial Regulatory Authority Reporting

Haryani Diah Sitawati, Yova Ruldeviyani, Achmad Nizar Hidayanto, Rizaldy Septa Amanda, Anggoro Septa Nugroho

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Financial Regulatory Authority implements Integrated Reporting to improve data quality which is very important because this report will be input for making monetary and macroprudential policies. Data assessment is needed to fulfill the needs of standardization of data quality. The objective of this research is to analyze the quality of critical data from the Integrated Reporting for the monthly period that is reported to the financial regulatory authorities based on the dimensions that are used to perform measurements. There are 4 dimensions of data quality used to define the data quality requirements in this Financial Regulatory Authority, which are completeness, accuracy, currency, and timeliness. To analyze the data, a specific framework for financial data was chosen which is Quality Assessment on Financial Data (QAFD) framework with slight modification. The result of the objective assessment from 48 variables for the completeness dimension is 100% for the mandatory variable, the dimensions of syntactic accuracy and accuracy that related to precision and validity show 100% results but the semantic accuracy for loan, time deposit, and demand deposit shows the percentage of 81.77%, 85.04% and 81.22%, currency dimension is 96.93% and timeliness dimension is 80.89%. Comparison between objective and subjective assessments from 6 variables as a sample shows that there is still a discrepancy for the currency and accuracy dimensions, while the completeness and timeliness dimensions are aligned between objective and subjective assessments. Based on the results of this study, recommendations were made to regulators to improve data quality.

Original languageEnglish
Title of host publication2021 International Seminar on Machine Learning, Optimization, and Data Science, ISMODE 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages272-277
Number of pages6
ISBN (Electronic)9781665405447
DOIs
Publication statusPublished - 29 Mar 2022
Event2021 International Seminar on Machine Learning, Optimization, and Data Science, ISMODE 2021 - Jakarta, Indonesia
Duration: 29 Jan 2022 → …

Publication series

Name2021 International Seminar on Machine Learning, Optimization, and Data Science, ISMODE 2021

Conference

Conference2021 International Seminar on Machine Learning, Optimization, and Data Science, ISMODE 2021
Country/TerritoryIndonesia
CityJakarta
Period29/01/22 → …

Keywords

  • Data quality
  • Data quality assessment
  • Data quality dimension
  • Financial data
  • QAFD

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