XBRL-Trail --- A model for introducing digital forensic readiness to XBRL

Business is reliant on Information Technology to process and share financial data. Proprietary formats often hinder the sharing of financial data as stakeholders can not uniformly read or access the data. As a result, XBRL (The eXtensible Business Reporting Language) was developed to address the information sharing issue, and is rapidly becoming the standard format for financial data. XBRL does however pose a significant fraud risk, as it is trivial to edit the financial records in an unauthorised manner. Typically such a case requires investigation by digital forensic experts, whose duties are in turn complicated by XBRL’s scant retention of forensic evidence (lack of forensic readiness). This article addresses XBRL’s lack of forensic readiness and proposes a model to enhance the forensic readiness of XBRL. Using a mediator, placed between the users of the XBRL data and the XBRL data itself, we show that forensic evidence can be captured in real time, which would significantly reduce the investigation time.