Automated processing of data is a valuable tool through which information is extracted without the need for human intervention. While traditionally used for commercial purposes, these automated systems are increasingly being employed in the field of law enforcement. Data which is filtered and processed utilizing automated analysis is seen as a mechanism for limiting collateral intrusions, focusing disclosures purely on information which is crucial to an investigation. This enables the police to

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... target their inquiries and allocate their resources efficiently. Yet issues remain when the human element is removed from investigations. Often these filters are the creation of third parties who work in conjunction with relevant public bodies to apply automated processes to data. This creates questions concerning the liability of these intermediaries for the processing, and what duties the State has in order to ensure accountability for their actions. Similarly, concerns exist about the transparency of the data sets utilized in these automated investigations, and the existence of any biases therein. These problems are further compounded when the data sets themselves are expanded and the data is taken out of its original context. To address these issues, this paper analyses automated investigations in the context of the 'request filter' for communications data, established by the Investigatory Powers Act 2016, and offers a critique of the extent to which this mechanism can be considered a legitimate safeguard for personal information. Keywords: Big Data, Automated, Request Filter, Investigatory Powers Act.