TY - GEN
T1 - Data Quality Improvement
T2 - 2021 International Seminar on Machine Learning, Optimization, and Data Science, ISMODE 2021
AU - Sitawati, Haryani Diah
AU - Ruldeviyani, Yova
AU - Hidayanto, Achmad Nizar
AU - Amanda, Rizaldy Septa
AU - Nugroho, Anggoro Septa
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022/3/29
Y1 - 2022/3/29
N2 - 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.
AB - 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.
KW - Data quality
KW - Data quality assessment
KW - Data quality dimension
KW - Financial data
KW - QAFD
UR - http://www.scopus.com/inward/record.url?scp=85128184959&partnerID=8YFLogxK
U2 - 10.1109/ISMODE53584.2022.9743087
DO - 10.1109/ISMODE53584.2022.9743087
M3 - Conference contribution
AN - SCOPUS:85128184959
T3 - 2021 International Seminar on Machine Learning, Optimization, and Data Science, ISMODE 2021
SP - 272
EP - 277
BT - 2021 International Seminar on Machine Learning, Optimization, and Data Science, ISMODE 2021
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 29 January 2022
ER -