Workshop on Knowledge Representation and Information Management for Financial Risk Management
The credit crisis of 2008 and the ensuing Great Recession have shone a light into the hitherto esoteric world of investment
data processing. The lack of consensus or acceptable best practices around standards, agreed upon definitions, procedures,
metrics, and mathematical techniques have left supervisory agencies unable to ingest market information in either a timely
manner that would permit a macro-prudential response, or even determine what information might be missing. This has resulted
in the following unsatisfactory situation:
- Corporate managers are uncertain of the trustworthiness of their internal risk and accounting numbers;
- The academic community is lacking the information required to examine and analyze actual market operations and behavior;
- Regulators, analysts, and the financial press are denied an understanding of capital market operations sufficient to forge knowledgeable and prudent financial policy.
The purpose of this NSF sponsored workshop is to help develop the underlying theory and framework that might unify the disparate ongoing and planned
efforts at understanding and managing the enormous data and information flows in the financial services industry, and to develop
a comprehensive list of the challenges in this domain with respect to robust risk assessment and management.
The workshop is sponsored by the National Science Foundation CISE III Program under Grant IIS-1033927.
When
July 21-22, 2010
Where
Principal Investigators
- Louiqa Raschid, University of Maryland, PI
- Mark D. Flood, University of Maryland, co-PI
- A. "Pete" Kyle, Robert H. Smith School of Business, University of Maryland, co-PI
Disclaimer
The opinions expressed by speakers at the workshop, as well those expressed in the workshop report, are those of the speakers,
organizers, and participants, and do not necessarily reflect the opinions or policies of the participants' employers, the
National Science Foundation or the U.S. government.


