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Is the European Union legislating the Ratings process towards an Open Source Model?

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nikos croppedApproval of new Regulation will raise standards for the issuance of credit ratings used in the Community

New rules for Credit Ratings Agencies include the following:

  1. Credit rating agencies may not provide advisory services.

  2. They will not be allowed to rate financial instruments if they do not have sufficient quality information to base their ratings on.

  3. They must disclose the models, methodologies and key assumptions on which they base their ratings.

  4. They must differentiate the ratings of more complex products by adding a specific symbol.

  5. They will be obliged to publish an annual transparency report. 

  6. They will have to create an internal function to review the quality of their ratings.

They should have at least two independent directors on their boards whose remuneration cannot depend on the business performance of the rating agency. They will be appointed for a single term of office which can be no longer than five years. They can only be dismissed in case of professional misconduct. At least one of them should be an expert in securitisation and structured finance. 


Comments

The Argument for Open Source in Financial Predictive Analytics

 

The Central Banks, Universities, Software Vendors, individual developers and consulting firms are constantly publishing papers in the public domain about how to do modern risk management, most of these model risk management in R. There is no question that in general black box proprietary closed source predictive analytics have failed the banking industry and thus society through this crisis period. The detailed evidenced argument that the manner of implementing risk analytics is already done by the Central Banks and Academics is out there, this entails that there is no need for any single financial entity to re-invent the whole domain intellectual capital of macroeconomic stress testing, for example. Most of the macroeconomic stress testing has been conducted in R by the Central Banks and Universities. The key business accelerator in Open Source is Community, particularly in Financial Predictive Analytics; since it is via the community in an open source framework that one's initial intellectual capital is gathered, that these assets are farmed.

The Community Open Source idea in relation to meeting Banking Supervision requirements is just the kind of innovation in thinking and technology that Europe should be exhibiting in the middle of this recession, to develop a path to the future and exit this recession on a stable trajectory such that a Crisis like the one we are in will never happen again. The Objective is to setup departments in individual banking entities which are capable of deploying the Community intelligence in R and thus obviate the need to re-invent the wheel continuously to meet Banking Supervision requirements.

The Argument for Open Source in Financial Predictive Analytics

There are commercial challenges to managing an Open Source project in-house. Some Banks can do it but it is "new stuff". All too often we ignore the real effects of "new stuff" on our project timescales. The impacts of technology change on IT projects in general and on the planning process in particular is often underestimated. You need to have the right knowledge and experience about the new stuff; methodology and development techniques; to plan and execute on its implementation.

There is no way that an ordinary user can manage all of the disparate communities and forges which exist and may develop in an open source development language that is they key deliverable of the support centre to appraise, unit test and understand all of the objects out there in the social or community networks. This stuff is complex, the code is complex, so are the questions which the code is supposed to answer, what is known as the pre-code methodology issue.

Therefore Robust and Rigorous Commercialized Support for the Community in terms not only of the development process but also of the methodological issues is fundamental to the success of this innovation.

 

Open-Source Credit Ratings: REvolutions

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