Business rules for business experts
Sphinx is an XBRL business rules language that can be used by auditors, regulators, analysts and business report preparers, to protect and enhance the quality and compliance of your data.
How Sphinx® works
The language doesn’t require extensive IT or programming skills making it ideal for business experts. Use Sphinx® to implement the following business rules across your enterprise:
- Quality rules with the aim of stopping errors at their source.
Compliance rules allowing anomalies to be flagged instantly.
Information rules identifying problems.
Sphinx® can assist regulators to rapidly identify problems and is often used to capture bad data before it gets into the system. Sphinx® rules are authored in an optional SpiderMonkey® module and can also be used within Magnify®. Alternatively, rules validation can be achieved using True North® or the True North® Web Services Processor. Examples of use include:
- Ensuring that the required data items are incorporated into a file.
Ensuring that co-constraints are enforced (For example, if you report X, you must also report Y).
Comparing data across dimensions
More and more accounting firms responsible for XBRL and iXBRL filings are looking to develop their own sets of rules to check the quality and consistency of documents, Sphinx makes this a reality.
At CoreFiling, we work with leading firms and community of accountants in the UK and US, assisting them when it comes to using the combined power of Magnify® and Sphinx®. Our aim is to prevent them from filing clients documents that contain errors, omissions or inconsistent data.
Analysts and large investment firms are rapidly investing in systems and processes which consume and analyse XBRL data and we believe Sphinx® can play a key role when it comes to this.
If you’re an analyst or an end user of XBRL data, you can develop “screens” of Sphinx® rules to capture data quality issues at an early stage. This will help you to eradicate inconsistencies and automatically identify aspects of corporate performance that are of interest.
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