What are the most important data quality checks for Payment Systems?

1 Data completeness

Data completeness is essential to ensure that payment systems are processed correctly and efficiently, without any missing or corrupted information. To check for data completeness, you can count the number of records and compare them with the expected or historical values. Additionally, verify that all the mandatory fields are filled and have valid values. Identifying and resolving any missing, null, or blank values is also important, as well as checking for any duplicates, inconsistencies, or outliers in the data.

2 Data accuracy

Data accuracy is essential for avoiding errors, disputes, and fraud, and for ensuring compliance with relevant regulations and standards. To ensure accuracy, you can compare the data with the original sources, validate it against predefined rules, perform calculations or aggregations on the data and verify the results, and review the data for any anomalies. Furthermore, you can check for data accuracy by comparing it with invoices, receipts, or bank statements; validating it against formats, ranges, or constraints; and verifying any calculations or aggregations.

3 Data consistency

Data consistency is crucial to maintain the integrity and usability of data, as well as to facilitate its integration and analysis. To ensure data consistency, you can compare the data from different sources and ensure that they match or align, standardize the data formats, units, codes, and definitions, harmonize the data schemas, structures, and metadata, and resolve any conflicts, contradictions, or ambiguities in the data. This will help guarantee that the data is coherent and compatible across different sources, systems, and formats.

4 Data timeliness

Data timeliness is essential to support the performance, efficiency, and responsiveness of the payment system, and to enable timely decision making and forecasting. To check for data timeliness, you can measure the latency or delay between the data generation and consumption, monitor the frequency and duration of the data updates and refreshes, evaluate the impact of the data age and freshness on the data quality and value, and establish and enforce the data retention and archiving policies. These methods can help ensure that your payment system is up-to-date with relevant data.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?