Which method is employed in Avaloq ICE to ensure data accuracy?

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Implementing validation rules and integrity checks is a fundamental method in Avaloq ICE to ensure data accuracy. Validation rules are predefined criteria that data must meet before it can be processed or stored, which helps in maintaining the consistency and reliability of data. Integrity checks are mechanisms that verify the correctness and completeness of the data set, ensuring that data remains accurate over time and conforms to the established rules. By employing these methods, Avaloq ICE minimizes the risk of errors and discrepancies in data, leading to improved decision-making and operational effectiveness within financial institutions.

In contrast, regularly deleting old data may not necessarily enhance data accuracy; it can even lead to the loss of historical information that could be relevant for analysis or compliance. Random data generation does not guarantee accuracy, as it can introduce randomness that does not reflect real or usable data conditions. Conducting manual data audits only relies on human intervention, which can be time-consuming and may not be thorough enough to catch all inaccuracies. Therefore, the multifaceted nature of validation rules and integrity checks is essential for maintaining data quality in Avaloq ICE.

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