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Research Article
An AHP-based Approach for Banking Data Quality Evaluation

Keting Yin, Yufei Pu, Zirui Liu, Qi Yu and Bo Zhou

Information Technology Journal, 2014, 13(8), 1523-1531.


With the growth of business in modern enterprises, data volume in enterprise is increasing significantly. The quantity of the data has entered the age of TB in most enterprises. As a result, data quality has become an important and attention-needed part in the construction of information systems in enterprises, especially in the banking industry, where data quality is even more crucial. Data quality issues in banks often lie in aspects such as incompleteness, inconsistency, invalidity, untimeliness, which has not only resulted in the bank’s huge direct economic loss but has also influenced its strategic decisions to some extent. As an important part in data quality management, data quality assessment plays an indispensable role in data quality assurance. This study proposes an evaluation index system for banking data quality and an AHP-based evaluation method used to calculate weighting coefficients of each index in the data quality evaluation index system. The method proposed in this study is based on a real project of data quality assessment in a commercial bank. With a purpose to establish a whole set of data quality evaluation system and coefficient weighting method for the bank, the project produces accurate, systematic and scientific data quality assessment results, which is instructive to the implementation of data quality assessment in other banks.

ASCI-ID: 28-3456

Cited References Fulltext

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