Leaked Document – Review Project
Sometimes new and introduced sets of data need to be rapidly reviewed or interrogated. For instance, a nation’s Tax Office acquiring the Panama and Paradise Papers. Current procedures to understand the content and priority of the datasets were slow and manual. Frisk was deployed to enable deep, penetrative examinations at speed, producing world-class outcomes.
|A new and valuable dataset was acquired by our client. The client wanted to interrogate and cross reference the data against its own intelligence. In the past, significant time and resources were required.||Frisk was deployed to rapidly connect and enrich the data, which in turn allowed our client to identify items for further investigation. Frisk processed the data within a 7-day timeframe reducing the time taken to process via existing technology by 92%.||
The Paradise Papers are a set of 13.4 million confidential electronic records relating to offshore investments that were leaked to a German newspaper. Through the International Consortium of Investigative Journalists, some of the documents in the leak were shared with Tax Offices around the world, including the Australian Taxation Office (ATO). One of the challenges faced by the ATO was how to rapidly review the vast number of documents, quickly identify Australian entities referenced within, and then initiate further detailed reviews of pertinent information.
A typical review of all the unstructured content would have taken thousands of man hours. Alternative technology solutions available within the ATO presented significant speed and capability limitations when it came to OCR and indexing.
Frisk was implemented to conduct the document indexing and discovery process, heavily reducing the time required to get insights from the documents. The process Frisk implemented included rapid indexing and OCR of the files, to enable a detailed review within 24 hours. The next step was to utilise the numerous reference sources of known companies, individuals and other relevant data, to build and execute multiple bulk queries (100’s of 1000’s) against the index utilising Frisk’s bulk query capability, and iteratively refine the accuracy. This enabled rapid identification of ‘entities of interest.’ This fast and comprehensive initial review identified unknown relationships and avenues for further investigation.