Workshop on Knowledge Representation and Information Management for Financial Risk Management

University Of Maryland, College Park, College Park MD

Investigators

Abstract

Workshop on Knowledge Representation and Information Management for Financial Risk Management (KR-Financial Risk) 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 will draw upon an interdisciplinary team of experts from computer science (data management and mining and knowledge representation), finance, mathematics, economics and operations research. The workshop will generate a report which will develop a comprehensive list of the challenges in this domain including the fundamental forces and constraints and policies and models of information management that are critical for robust financial risk management.