Confidential 11 Knowledge Representation & Information Management for Financial Risk Management “What We Know Now” Michael Atkin, Managing Director, EDM.

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Confidential 11 Knowledge Representation & Information Management for Financial Risk Management “What We Know Now” Michael Atkin, Managing Director, EDM Council Sponsored by National Science Foundation CISE III Program July 21-22, 2010

Confidential 2 Copyright © 2010 EDM Council Inc. 2 The Data Benefit of Crisis The credit crisis, economic meltdown and the rise of the concept of systemic risk analysis is great news for data management Forced participants to think about data content as the foundational building blocks for complex analysis Data content management is a relatively new discipline for the financial industry We’re good at processing data, but not experienced at managing the meaning of data where granularity, precision and comparability matter The “financial industry” meets the “information industry”

Confidential 3 Copyright © 2010 EDM Council Inc. Data Tagging and Knowledge Management (1963) GML – describe format, organizational structure and content components (1986) SGML – ISO standard for describing a documents structure and attributes = rise of online information industry (1991) HTML – Tim Berners-Lee for document sharing = rise of dynamic web formatting (1996) XML – abbreviated version of SGML allowed for separation of components of a document –Logical from physical structures, elements from attributes from processing instructions –Communication of precise meaning and structural relationships

Confidential 4 Copyright © 2009 EDM Council Inc. Systemic Analysis is Not a Thing There is no standard report for identifying market vulnerabilities –Assess the interrelationships and interdependencies of factors to determine the impact of specific events on the overall financial system –Look at the nature of risk concentrations, monitor unusual escalations in asset prices or variances in credit spreads, etc. Understand the legal characteristics of instruments and portfolios –Understand all the obligations and restrictions related to trading, managing, clearing, settlement and custody –Comply with the terms of indenture, redemption, maturity, priority and exercise –Understand the terms and parameters for payment and reinvestment Determine the links and relationships between issuers, issues, instruments and obligations in order to know what is being traded with whom and under what conditions

Confidential 5 Copyright © 2010 EDM Council Inc. Necessary Conditions (building blocks) Instrument Reference Data (factual) –Identifiers at the instrument level –Standard language associated with the legal and contractual structure of financial instruments –Classification of instruments types and cash flow Entity Reference Data (factual) –Identifiers for all involved in the transactions chain and where due diligence is required –Ownership structures and business relationships throughout the transactions process Economic Statistics (factual) –Employment, income, global trade, money, output, prices and production –Cooperative standards initiative of BIS, ECB, Eurostat, IMF, OECD, UN and World Bank Pricing and Valuation Data (interpretative) –No problem for exchange traded –Exposure and comparability of calculation methodologies and all derived inputs for off exchange and thinly traded Positions and Transactions Data (sensitive) –Summary of settled/unsettled contracts where financial entity has a legally binding role –The goal is comparability among factors of input into positions and transaction

Confidential 6 Copyright © 2010 EDM Council Inc. Data Attribute Tagging First rule of complex systems is to get the language straight Prime directive: data that users have confidence in to be fit for purpose without reconciliation Our industry is dominated by common words with different meaning, common meaning using different words, important nuances not captured Semantic precision is essential in order to: –Compare data –Set precedence rules –Achieve straight through processing (automation) –Promote confidence in analytical models –Structure portfolio strategies and perform cross asset risk assessment

Confidential 7 Copyright © 2010 EDM Council Inc. MDDL (Strike One) Late 90’s – captivated by the capabilities of XML “We need an XML schema for market data” (Chairman of Board) Two years building an XML schema with all the bells and whistles (dominated by IT experts – business context not included) Innovative XML but didn’t address core problem of data comparability among multiple data silos and by myriad of data vendors

Confidential 8 Copyright © 2010 EDM Council Inc. ISO (Strike Two) Creation of working group within ISO TC68 / SC4 with clear business objective (underlying data ontology) Business domain knowledge lacking - so reliance on data modeling expert from large financial institution with a functional data modeling process Standard data model but still didn’t address the core problems of data comparability or integration

Confidential 9 Copyright © 2010 EDM Council Inc. Regulatory Driver (Solid Hit) Driven by real business problem (municipal bond transparency mandate from MSRB) DTCC initial implementation document contains proprietary technical tags and definitions Impossible to map, deadlines loom, regulators watching – brought industry together to reconcile definitions Eight week battle among various stakeholders on “terms” and definitions. Holy war because of impact on database design and implementation Conversation shifted to the “meaning” of the data needed to respond to regulatory requirements = epiphany

Confidential 10 Copyright © 2010 EDM Council Inc. Semantics Philosophy Formal and factual representation of reality (things, facts about things and relationship among things) No technical design – must be able to communicate requirements between business applications and IT implementation Transparent development structure to enable subject matter experts (business and IT) to add, challenge and modify Must be flexible and extensible to accommodate new developments Must help solve real business challenges (integration of multiple repositories, alignment of data dictionaries, reduction of reconciliation, minimize transformation) in a practical manner

Confidential 11 Copyright © 2010 EDM Council Inc. This is What is Required Identify financial instruments, legal entities and classification schemes with precision (ISO-based identifiers) Establish a common language for all contractual obligations that drive our industry (XBRL and linked ontologies, EDMC Semantics Repository, ISO and data dictionary, FpML and links to ISDA contracts) Coordinate globally! We need uniform identification standards Mature governance to overcome the organizational challenges of ignorance, arrogance, obsolescence and power (the four horsemen of the EDM apocalypse) Manage our fragmented chain of data supply and shift from ‘data scrubbing’ to ‘data manufacturing’ mindset (legal compulsion)

Confidential 12 Copyright © 2010 EDM Council Inc. The Objectives are Achievable Instrument identification and the historical lesson from the 1968 paper reconciliation crisis (we’ve done this before) Entity identification is a direct parallel except only 800,000 entities versus 8 million financial instruments (we can do this again) Stop thinking about semantics as an IT problem. Start thinking about it as a simply a formal and factual representation of reality (remember Aristotle) Majority of reference data needed for business processing and regulatory oversight are based in legal contracts (tag them at the point of issuance using industry standards) The one aspect of regulatory reform that is common to everyone around the world is DATA. Global harmonization of data standards is logical and inevitable (and the financial industry would be forever grateful)

Confidential 13 Copyright © 2010 EDM Council Inc. Contact Information Michael Atkin Managing Director, EDM Council web: Semantics Repository