Which of the following would BEST help to detect errors in data processing?

The most effective option for detecting errors in data processing is the use of hash totals. Hash totals are calculated values that are generated from the data input and are used to verify the integrity and accuracy of that data as it moves through processing. By creating a hash total of a specific dataset before and after processing, any discrepancies between the initial and final hash totals would indicate that an error occurred during processing.

For example, if a company is processing payroll data, a hash total could be created from the employee IDs or salaries. After processing, if the hash total changes, it suggests that some data may have been altered or lost, prompting further investigation. This method serves as a powerful control mechanism for validating data integrity and ensuring that all pieces of data have been accurately processed.

While programmed edit checks and well-designed data entry screens also contribute to data quality by preventing incorrect data entry, they are less focused on post-processing validation. Segregation of duties is primarily about preventing fraud and errors through the separation of responsibilities, rather than directly detecting errors in data processing.