Transparency

Risk Model Ontology

Risk Model Ontology

Semantic Web Technologies The Risk Model Ontology is a framework that aims to represent and categorize knowledge about risk models using semantic web information technologies. In principle any semantic technology can be the starting point for a risk model ontology. The Open Risk Manual adopts the W3C’s Web Ontology Language (OWL). OWL is a Semantic Web language designed to represent rich and complex knowledge about things, groups of things, and relations between things.
Transparency, standards, collaboration key to regaining trust in financial services

Transparency, standards, collaboration key to regaining trust in financial services

Transparency, collaboration key to regaining trust in financial services In banking, confidence is the first order of business Maintaining the confidence of market participants, clients, shareholders, regulators and governments is uniquely important for the financial sector. Trust is, quite literally, the real currency. Yet it is a truism that confidence is hard to build up and rather easy to destroy. Why is this so? The short answer: The difficulty in rebuilding trust is linked to the lack of transparency.
Securitisation versus Banking – the Shootout

Securitisation versus Banking – the Shootout

Securitisation versus Banking The ever elusive CMU dream There is(/was) renewed interest in EU-land over deepening a “capital markets union”, aka “CMU”. It is among the initiatives being pursued by the Commission in order to help accelerate growth in the European Union. The initiative encompasses many elements, both around equity (shares) and debt markets. One important pillar of the CMU aims to re-launch some version of an EU securitisation market. This segment was never really defined in a EU-wide basis.
Top Ten Reasons Why Open Source is the Future of Risk Modeling

Top Ten Reasons Why Open Source is the Future of Risk Modeling

Financial Risk Modelling has suffered enormous setbacks in recent years, with all major strands of modelling (market, credit, operational risk) proven to have debilitating limitations. It is impossible to imagine a modern financial system that does not make extensive use of risk quantification tools, yet rebuilding confidence that these tools are fit-for-purpose will require significant changes. These need to improve governance, transparency, quality standards and in some areas even the development of completely new strands of modelling.