EDM Council Webinar
Update and Outlook
Michael Atkin
Managing Director, EDM Council
June 12, 2013
Confidential
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Regulatory Drivers
Mandatory
Basel Requirements
• Transparency (Dodd-Frank,
Regulation AB2, EMIR, UCITS, AIFMD,
COREP, FINREP, ACORD)
Governance and Infrastructure (Board
of Directors accountability, independent
validation, integrated data taxonomies,
aligned metadata, standard identifiers,
standard naming conventions,
mechanism for data alignment and
comparability (semantics)
●
• Systemic Risk Oversight (Basel Risk
Data Aggregation Principles, SBSG
Report on Risk Appetite Frameworks,
FSB Key Attributes, FRY-14Q, FRY-9C)
• Capital Requirements (Basel III, CCAR,
Solvency II)
• Functional Areas (collateral flows,
leverage and liquidity measures,
guarantee and transmission of risk,
degree of diversification, systemic
contagion)
• Surveillance (shadow banking,
electronic execution, concentration of
power, structural vulnerability,
consumer protection, hedge funds,
insurance and reinsurance)
●
Risk Data Aggregation (data quality - timely,
accurate, comprehensive, clear), data lineage and
root cause remediation, on-demand and ad hoc
reporting capabilities, automated risk aggregation
all relevant business units and functions, near
real time reporting
Supervisory Tools (mandatory tools,
independent audit, capital add-ons,
activity limits, pre-authorization, cross
regulatory agency coordination)
●
Internal Assessment (2013)
Mandatory Compliance (2016)
Business Drivers
• Data Errors and Repairs
(reconciliation, exception processing,
convoluted models, trade repairs,
valuation miscalculation, settlement
instruction mismatches, bad corporate
action processing)
• Data Utilization (manual processes,
maintenance of proprietary feeds and
interfaces, redundant systems,
duplicate master files, duplicate
accounts, integration and
transformation challenges)
• Business Development (upselling
opportunities, enhanced client
service, new product engineering,
contextual big data mining, process
automation, product and client ROI)
• Data Reporting (links between
instruments (what we trade)  entity
(with whom we do business) 
obligations (based on role)  and
holdings (what’s in our portfolios)
Pillars of Data Operations
Content Infrastructure
Standards for the unique and precise
identification of instruments, entities,
language of the contract and
classification schemes (LEI, loan ID,
universal product ID, cash flow, sector
classification, instrument categorization)
(Identifiers and Ontologies)
Data Management Strategy
IT Environment
Governance, funding model, TCO and
measurement, requirements
management, resource strategy, business
semantics, business process flows, data
flows, data quality, executable business
rules, integration strategy
Data workflow, process capabilities and
limitations, technical architecture, legacy
reconciliation, messaging standards,
metadata management, data
management platform, supply chain
management
(Data Management Maturity and
Capability Assessment)
(Technical Architecture, Framework
Standards and Process Engineering)
EDM Council Highlights
• Initial FIBO specifications to be
released June 17 (Foundations
and Business Entitles)
• FIBO Technical Summit held June 4-5 in
San Francisco (collaboration
with semantic processing
community)
• Liquidity template mapping
to FIBO (Bank of England)
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EDM Council Highlights
• DMM pilot with Microsoft
successfully completed
• EDM Council to offer
facilitated DMM assessment
workshops to members
• Office of Financial Research
(OFR) Financial Research
Advisory Committee (FRAC)
initial recommendations
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Core Regulatory Initiatives
• Dodd-Frank Act = total revision of U.S. financial regulatory environment (transparency, financial stability and market
surveillance implications)
• Regulation AB2 = the SEC’s new regulations on mortgage backed/Asset Backed securities (must be able to unravel
links between loan, tranches, pool, etc.).
• UCITS = Undertakings for Collective Investment in Transferable Securities (EU Directive on simplification of
prospectus and their expression using clear, accessible and standardized data).
• AIFMD – Alternative Investment Fund Managers Directive (EU proposed law to provide more oversight and
transparency to hedge funds and private equity).
• Basel III – global regulatory standard on bank capital adequacy, stress testing and market liquidity risk.
• CCAR = Comprehensive Capital Analysis and Review (stress test methodology in the US; CCAR reporting is putting lots
of pressure on data alignment and comparability. This includes the FR Y-9C (Bank Holding Company Capital Report)
and FR Y-14Q (detailed ‘show your calculation methodology work for BHC). This is the US version of Basel III.
• Solvency II – EU Directive that harmonizes insurance regulation (requirements for capital reserve and reduction of risk
of insolvency) – to be implemented January 2014.
• ACORD – Insurance standards development body (UK) likely to be mandated as the format for reporting.
• COREP = Common Reporting requirements (developed by Committee of European Banking Supervisors (CEBS) with
the goal of developing a supervisory reporting framework based on common data standards and formats.
• EMIR – European Market Infrastructure Regulation (EU version of Dodd-Frank Title VII on derivatives transparency).
• MiFID II – Revised Markets in Financial Instruments Directive (mostly about trading, but does require common
instrument identification for consolidated pricing).
• FSB Templates = Common Data Template for G-SIB’s seeking to harmonize the data compounding methodology for
reporting.
• Basel Principles for Effective Risk Data Aggregation and Reporting = new principles related to the implementation
of a “data control environment” and healthy “risk appetite framework” within systemically important financial institutions.
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Common Data Themes
Data Harmonization – alignment of definitions
and the ability to aggregate consistently across
the industry
Data Production – understanding of what it
takes to create new information and link content
for scenario-based analysis
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Basel Principles for Risk Data Aggregation
• Governance: ownership at the BOD
and executive management level
for enterprise-wide adoption
of control environment
• Data Infrastructure: facilitate
comparability and ability to
aggregate on consistent basis
• Ad-Hoc Reporting: data that
regulators have confidence in to
facilitate comparability without
reconciliation
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Derivatives Transparency
• Validate and Normalize Data (across SDR’s
and across geography)
• Standardize Product Identification (719(b),
SDR aggregation and OFR instrument
database)
• Aggregate and Classify (type, counterparty,
cash flow, obligation)
• Align with Messaging Standards (FpML,
FIX derivatives, ISO 20022)
• Support Complex Analytics (filter, sort,
search, link, query based on ad-hoc scenarios
and on-demand)
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Stress and Liquidity Testing
• Data: alignment of
terms and definitions, product
type classification, integration
of acquisitions
• Communication: clarity of
requirements, data usage,
data production process
• Timing: change requests,
submission deadline conflicts
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Hierarchical Reporting
• Remember: LEI is a building block for reporting
• Separate the characteristics of “entities” from the types of
“relationships” that exist among entities from the “roles”
performed in the transaction
• This is about describing contractual “facts” and
“relationships” in a formal manner
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What an “entity” is
The types of “entities” that exist
What “ownership” means
What “control” means
Relationship
Types, Definitions,
and Descriptions
Entity B
Entity A
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Relationship
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FRAC Data Committee (core themes)
• Focus on the practical objectives of OFR (advisory
capacity only)
• Manage contagion and support predictive analysis
• Implement standards to support core capability objectives
(identify, describe, classify and link)
• Facilitate data comparability among FSOC member
agencies
• Improve data collection process (reduce cost, improve
quality, support analytical flexibility)
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FRAC/DTS Short-Term Goals
• LEI quality standards (necessary to fulfill the entity
database obligation)
• Employ “legal criteria” for reporting about
relationships (the application of LEI)
• Instrument database is a precise description of all
instrument types (what they are and how they
work)
• Loan ID and classification are pressing standards
objectives
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Data Management Maturity Model
•
Core Model Released (June 2012)
– SIFI request to address MRIA orders on data
quality and governance
– Hybrid of SCAMPI methodology
– Early adoption (30+) and detailed feedback
•
Revised DMM (April 2013)
– Elimination of redundancies and simplification
– Alignment of approach across process areas
– Concept clarification and translation to
non-specialists
– Enhanced relationship to artifacts
– Dependency mapping and value
band categorization
•
Confidential
Pilot Initiatives and Validation
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DMM: Alignment with Basel RDA
“If the DMM is something our bankers would like us to
consider in the context of the BCBS Risk Aggregation
Reporting Principles, let them know we are open to
having a dialogue with them.”
Basel RDA Data Principles
• Accountability for risk aggregation at BOD and
executive management level
• Integrated data taxonomies and aligned
metadata
• Standard identifiers and naming conventions
• Data lineage and root cause remediation
• On-demand and ad-hoc reporting capabilities
• Automated risk aggregation across relevant
business units
• Scenario-based analysis and near real-time
reporting
Molly Scherf
Risk Appetite Working Group
Senior Banking Supervisors Group
Large Bank Supervision
Office of the Comptroller of the Currency
U.S. Department of Treasury
May 2, 2013
Internal Assessment (2013)
Mandatory Compliance (2016)
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Understanding the DMM
•
Structure of DMM
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Top level is organized into core categories
Categories contain a number of primary components
Components are organized into process areas (containing goals,
core questions and capability practice statements)
Capability practices are organized into levels that are used as
the basis for assessment (with expected artifacts/work products)
Capability Practice Levels
• Level 0: Incomplete (not performed or unstable
processes)
• Level 1: Performed (ad hoc processes. Emphasis on
data repair. Reactive and transitory improvements)
• Level 2: Managed (formalized processes.
Infrastructure supports at business unit. Clearly
defined roles and responsibilities)
• Level 3: Defined (Established processes. Tailored to
meet specific needs. Predictable and consistent)
• Level 4: Measured (Established metrics. Variance
management across the process lifecycle)
• Level 5: Optimized (processes are improved on a
continuous basis and advocated at the executive
management level)
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DMM Facilitated Assessment
•
CMMI Institute and EDM Council service offering (on request by members)
•
Workshop Methodology
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Collaborative, interactive and shared understanding
Consistent view of the breadth and depth of data management within the organization
Shared language about components, capabilities, core principles and objectives
Consensus scoring with interaction on rationale
Four Step Process
1.
Preparation: define objectives and recruit stakeholders
2.
Assessment Plan: establish sequence, define deliverables, determine
responsibilities and set timeframes
3.
Workshop: managed interviews, verification of requirements, analysis of business
processes/data flows, review of artifacts and analysis of governance
4.
Recommendations: current state assessment, gap analysis, composite scoring,
final report and executive briefing
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Financial Industry Business Ontology
Facilitates complex
queries for risk and
transitive exposure
analysis
Enables risk data
aggregations across
multiple dimensions
Represents real world facts (terms
and standard definitions) and
relationships about financial
instruments, business entities and
1
transactions
7
Integrates easily within
existing environments and
aligns with other standards
2
6
Enables classification of
financial instruments into
categories and supports
quality assurance
3
Can be used to visually express
all forms of data relationships
5
Confidential
Provide common reference point
for mapping from data
4
repositories to a common
business data standard
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FIBO Developments
• Initial Standards Milestone Passed
– FIBO Foundations and Business Entities
combined with OMG architectural rigor
– Standardization of FIBO methodology in RDF/OWL
• FIBO Development
– Wave two: securities, loans and derivatives
– Wave three: market data, corporate actions
and transactions
• Migration to Adaptive Metadata Repository
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FIBO Use Case Activities
•
Derivatives Transparency (live POC demo)
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Liquidity Reporting (underway)
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Evaluation of FIBO as a common data language for standardized
and granular reporting
Test of liquidity forms FSA 047-054 (data definitions and classification)
Potential to reduce reporting burdens and generate comparable data
in support of ad-hoc analysis
Loan Lifecycle (in discussion)
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Operational ontology showing the intersection of interest rate swaps,
credit default obligations and legal entities
Classification based on contractual facts for UPI
Queries about legal entity control and ownership
Alignment with FpML, FIX and ISO 2022 messaging taxonomies
Align loan and MBS lifecycle with FIBO to support reporting consistency
Support accurate and consistent mapping to MISMO messaging taxonomy
Rationalize FR Y-14 data production process and reporting
Copyright © 2013 EDM Council Inc.
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FIBO Technical Summit
FIBO Summit Technical Objectives
Adaptive Inc
Alion Science and
Technology
Black Diamond
Research
Cambridge Intelligence
Cambridge Semantics
CAPSICUM Business
Architects
Carnegie Mellon
Citigroup
EDM Council
Entropy Management
Limited
Expert Systems
FacetApp
Fincore Ltd
FrankelConsulting
Franz
Global IDs
Google
IHMC
Intellegent Software
Solutions
Johns Hopkins
University
Manulife Financial
Confidential
Michigan State
University/REA
MphasiSy
NIST
OCLC
Ontolog & CIM3
Ontology Engineering
Group (OEG)/
Universidad Politécnica
de Madrid
Oracle
Philadelphia University
Price Waterhouse
Coopers
Quantum4D
Raytheon-BBN
Semantic Arts
Smart Cloud Inc
SRI International
Tahoe Blue
Thematix
Top Quadrant
Bank of America
University College
Cork, Ireland
W3C
Wells Fargo
Wizdom Systems
1. The generation of operational ontologies in
RDF/OWL from conceptual ontologies
2. Convert requirements (i.e. regulatory rules)
into executable semantic rule statements
3. Visually represent all forms of semantic
content with enough rigor to support
reasoning
4. Facilitate the sharing of semantics and
analytics at the scale of the financial system
Copyright © 2013 EDM Council Inc.
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Next Steps for Collaboration Process
•
Organize: Create a Semantic Coordination Leadership team with a fixed
membership and published meeting schedule
•
Fund: Identify sources and a coordination process for semantic
technology funding
•
Sustain: Implement a Semantic Technology Laboratory (Center of
Excellence) as a formal mechanism for the advancement of semantic
technology
•
Link: Build and maintain a directory of participants and a listing of
publications/resources for the advancement of semantic technology
•
Meet: Implement an annual Semantic Technical and annual Semantic
Applications Summit as checkpoints
•
Publish: Provide a mechanism for participants to publish articles and
research related to semantic technology implementation
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Get Ready For …
On-Demand and Ad-Hoc Reporting
Meeting the needs of macroprudential
oversight is not possible without a trusted
data infrastructure
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Don’t Forget the …
Mandatory Alignment with Standards
The goal is automated, enterprise-wide
risk reporting. Concordance and data
reconciliation is no longer viable
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Built Upon …
Enterprise-Wide Governance
Board of Directors and executive
management is responsible for managing
the intractable relationship between risk
appetite and data management
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Designed Around …
Data Flows and Business Processes
Provenance over data and how it flows
from process-to-process with SOX-like
certification of capability
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Managed Through …
Better Supply Chain Management
The goal is to manage the flow of data
from originator  source system 
transformation process  transaction 
reporting
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Propelling Vendors …
To New Concepts of Added Value
The data management mandate will
propel data vendors and suppliers to
innovate and integrate in support of
clients enhanced requirements
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Opportunity for …
Partnerships and Collaboration
Between business silos, with vendors,
with regulators and across geographic
boundaries
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