Regulations in the financial services industry are becoming increasingly complex and can involve more than one regulator for a firm as well as different products, regulations and jurisdictions. However they play an important role in ensuring the stability of Europe’s markets and economies and protect its citizens. Risk and controls for compliance are becoming more complex. Proposals have been made to use solutions that are based on semantic web technologies.
An initiative related to trading is the Financial Industry Business Ontology (FIBO). This is a collaborative effort engaging participants from the financial industry, the regulatory community, academic institutions and semantic technology vendors to model and build a set of open standard ontologies that will deliver transformational benefits to the financial system. The Enterprise Data Management Council (EDMC) and the Object Management Group (OMG) are partnering to lead this effort. Following the 2008 global financial crisis it became clear that the absence of certain data standards led to a lack of awareness of the magnitude of risk that the industry was exposed to. The goal of FIBO is to introduce semantic capabilities that will better enable: common terminology for business entities, financial contracts and instruments; improve data transparency; improve data integration and linkage; and improve financial reporting and analytics, so that greater "data" quality and health can be introduced into the financial system. 

Other activities use collaborative groupings such as the Fix Protocol Ltd organization and the XBRL International Federation to leverage eXtensible Mark-up Languages (XML) and its offspring such as XBRL to identify data elements that computers can query and retrieve.

Big GRC Data would take this collaborative approach and apply it to the space between regulators, market participants and data.

 Regulation Topic Advances by FIORD
 The production of regulation in PDF documents that must be read and reviewed by compliance legal experts. The production and consumption of regulation via semantic technology.

Case Study: US versus EU Visions of Smart Regulation
The Data Transparency Coalition is a US organisation that brings together technology companies, non-profit organizations, and individuals to support the publication of US federal data online in consistent, machine-readable formats. They believe that regulatory agencies should embrace consistent data models for the subject matter that they regulate and apply consistent vocabularies, rules engines, interchange formats, and identifiers based on those models. This is the Coalition's concept of "SMART Regulation“. 

Committed to achieving SMART Regulation in the U.S. and elsewhere through a campaign that includes both top-down mandates, i.e. legislation, and bottom-up persuasion and the development of compelling use cases that show how SMART Regulation can improve the world. When the U.S. Congress passed the Dodd-Frank financial regulatory reform, the House of Representatives almost succeeded in including a provision that would have required all the financial regulatory agencies to adopt consistent interchange formats, such as XBRL. 

At the last minute, Senator Dodd removed the provisions. The Coalition hopes to persuade the next Congress, whose term began in January 2013, to re-introduce and pass a similar proposal. In August 2012, the Coalition and the Object Management Group announced a joint SMART Regulation initiative. The members of the initiative will work to more clearly define SMART Regulation and to develop working use cases. 

In the EU, Smart Regulation is a continuation of the Better Regulation initiative. For the EU, Smart Regulation means:
  • Promoting the design and application of better regulation tools at the EU level, notably simplification, reduction of administrative burdens and impact assessment. 
  • Working more closely with Member States to ensure that better regulation principles are applied consistently throughout the EU by all regulators. 
  • Reinforcing the constructive dialogue between stakeholders and all regulators at the EU and national levels. 

In summary, the US model focused on the semantic production by regulators of rules and regulations that can be then consumed by software agents on behalf of market participants. In turn the response of market participants can be enabled by software agents consuming risk and regulation data and then providing it in an agreed format back to regulators. This system would need to be able to scale to vast amounts of regulation, respond to increases in related data and financial services compliance requirements and be able to react to new information and on-going deadlines from Regulators. Again, access to programmes such as the Legal Entity Identifier would ensure a robust system.