©2017 Cambridge Semantics Inc. All rights reserved. Company Confidential
Applying Data Engineering and Semantic Standards to Tame the "Perfect Storm" of Data Management
March 2nd, 2017
Marty LoughlinVice PresidentCambridge Semantics500 Boylston St., Suite 1700, Boston, [email protected](o) 617.855.9565
Introduction to Cambridge Semantics (CSI)
Agenda
• IntroductionMarty Loughlin, Vice President, Cambridge Semantics
• Financial Industry Data Challenges & Solution OverviewCarl Reed, Adviser, Cambridge Semantics
• Regulatory Perspective & FIBO UpdateMike Atkin, Managing Director, Enterprise Data Management Council
• State Street - FIBO Interest Rate Swap DemoArthur Keen, Managing Director, Cambridge Semantics
• Q&A
The Anzo Smart Data LakeSmart Data Discovery, Analytics & Management
Company: Founded in 2007 by senior team from IBM’s Advanced Internet Technology Group Privately Funded Select customers:
Software: Market leading Anzo software suite is built on open Semantic Web standards 3rd generation of Anzo in production
Introduction to Cambridge Semantics (CSI)
MIT Innovation Showcase
Business Intelligence / Analytics Solutions
Financial Industry Data Challenges & Solution OverviewCarl Reed, Adviser, Cambridge Semantics
Trad
ing
Settl
& C
lear
Risk
Ope
ratio
ns
Ord
er M
gmt
Com
plia
nce
Trea
sury
Reg
Repo
rting
Ref D
ata
...
Enterprise Data Governance, Architecture & Execution
The World Most of Us Grew Up In
• Process Driven Architecture• Vertically Alligned Implementations
Regulatory
BCBS239, CCAR, MiFiD II, CATS, .....
Big D
ata
Mar
ket,
Clien
t, Op
erati
onal,
Risk
& R
ep
Operating Margins
Cybe
r Sec
urity
Data Center Mgm
t
DisruptionTension
Carl Reed February 24th 2017
Can We Turn Tension and Disruption into Opportunity?
Three Key IngredientsThree Key Ingredients
Organization Structure
Technology ArchitectureCommon “Lingua Franca”
Enterprise Data
GOVERN
S
SPECIFIES IMPLEMENTS
Data Engineering Data Science
Knowledge Engineering(Ontology)
Enterprise Data
External Data
Ontologies
Domain Expertise(Business SME’s)
Harmonized Data Expertise
Business Intelligence Requirements
New Intelligence
Scope
Semantic Mappings
Knowledge Graphs
Data Governance
Internal
External
1: Data Oriented Roles and Activities
C Suite Accountability, Responsibility, Authority
Carl Reed February 24th 2017
1. Data Oriented Roles and Activities
2.1: A Semantically Driven Enterprise Data Archtecture
Carl Reed February 24th 2017
Business & Technology Governance
Information Marts/Warehouses
Source Meta Data
ConceptsRelationships
Domains
Scale Out Compute
Semantic Enrichment
Semantic TransformsIdentity Resolution
Scale Out Storage
Indexing
Integrated Data SetsRaw Data Sets
Data Engineering
Business Intelligence & Data Analytics
Client/Customer Market Operational Risk/Reputational
OntologyExecutionPersistence
Data Sourcing
DistributionRefinement
Structured Unstructured Visual PhysicalCommunication
Data Sources
Acquisition Modes
Search
Source Registry
Business Glossary
Access Control
Relational NoSQL GraphTSDB Archive BRM Other
Lineage
2.1: A Semantically Driven Enterprise Data Architecture
Carl Reed January 25th 2017
Business & Technology Governance
Information Marts/Warehouses
Source Meta Data
ConceptsRelationships
Domains
Scale Out Compute
Semantic Enrichment
Semantic Transforms
Identity Resolution
Scale Out Storage
Indexing
Integrated Data Sets
Raw Data Sets
Data Engineering
Business Intelligence & Data Analytics
Client/Customer Market Operational Risk/Reputational
OntologyExecutionPersistence
Data Sourcing
DistributionRefinement
Structured Unstructured Visual PhysicalCommunication
Data Sources
Acquisition Modes
Search
Source Registry
Business Glossary
Access Control
Relational NoSQL GraphTSDB Archive BRM Other
Lineage
Koverse
FTP/CSV, Apache Kafka, Sqoop, Storm
Cloudera
Koverse
Cambridge Semantics
ANZO
GQERedOwl
Digital Reasoning
TopBraidAllegro
2.2: That Can be Implemented and Execute at Scale 2.2: That Can be Implemented and Executed at Scale
The New Big Data EcosystemLegacy Enterprise Data Problems Incrementally solving legacy data problems
using new Big Datatechnology & techniques
Carl Reed February 24th 2017
Add sources to data registry and distribute via hub supporting legacy client semantics for existing clients and enforcing enterprise semantics for new.
Migrate Over Time
2.3: That Can Accommodate the Existing as well as Execute the New2.3: That Can Accommodate the Existing as well as Execute the New
Regulatory Perspective & FIBO UpdateMike Atkin, Managing Director, Enterprise Data Management Council
Data Management in Perspective
Beachhead for Data Management Established
Data Management Implementation Based on Best Practice
Unified View of Data Meaning (primary data objective)
Consistent Measurement of Data Management Progress
Data Management Operational Playbook
Inference Processing for Analytical Adaptability
Why Harmonized (common language) Data Matters
Why Harmonized (common language) Data Matters
• Degree of interconnectedness
• Transitive relationship• State contingent cash flow• Collateral flow• Degree of centricity • Funding durability• Leverage & liquidity• Guarantee & transmission
of risk• Degree of diversification
Instruments• Identification• Classification• Description (rates, dates,
features, schemes, provisions)
• Value (i.e. price, date, time)• Calculate (volatility,
correlation, duration, tax)• Maintain (corporate actions)
Entities• Entity type (legal persons,
formal organizations, corporations, partnerships, affiliates, trusts, functional, etc.)
• Ownership structures• Controlling relationships
Obligations• Issuance process• Trade and execution• Guarantee • Allocate and administer• Clear and settle• Transfer
Holdings• Firm portfolio (individual
entity risk)• Corporate structure
(organizational risk)• Industry wide (systemic
risk)
BCBS 239 in Context
2008 Crisis: Inability to model contagion (who finances who, who is linked to who, what are the obligations of complex financial instruments)
Senior Banking Supervisors Group: Observations on Developments in Risk Appetite Frameworks and IT Infrastructure (intractable relationship between data and risk management and definition of control environment)
BCBS 239: Principles of Risk Data Aggregation and Reporting (governance, content infrastructure and data quality as mandatory objectives)
EDMC Regulatory AreasRegulatory Actions
Fundamental Review of Trade Book (FRTB)
Dodd-Frank: Title I (systemic risk) and Title VII (derivatives)
European Market Infrastructure Regulation (EMIR)
BCBS 239: Principles of Risk Data Aggregation & Reporting
Comprehensive Capital Analysis and Review (CCAR) and Basel III
General Data Protection Regulation (GDPR)
Investment Book of Records (IBOR)
Bank Integrated Reporting Dictionary (BIRD)
Financial Data Standardization Project (EC)
Regulatory Fitness and Performance Program (REFIT)
Common Data Template for Systemically Important Banks (FSB)
Data Gaps Initiative (FSB), Common Reporting (COREP) Template and Inventory of Data Reporting Requirements (DRR)
Markets in Financial Instruments Directive (MiFID2)
Capital Requirements Regulation & Directive (CCD/CDR IV)
Alternative Investment Fund Managers Directive (AIFMD)
Directive on Undertakings for Collective Investments in Transferable Securities (UCITS)
Solvency II (EIOPA)
Regulatory Agencies• Office of the Comptroller of the Currency (OCC)• Federal Reserve Board (FRB)• Federal Deposit Insurance Corporation (FDIC)• Securities and Exchange Commission (SEC)• Commodity Futures Trading Commission (CFTC)• CPMI-IOSCO Harmonization Group• House Financial Services Committee (Financial CHOICE Act)• Senate Banking Committee consolidated audit • Financial Stability Oversight Council (FSOC) and Office of Financial
Research (OFR)• Consumer Financial Protection Bureau (CFPB)• White House: National Economic Council (NEC)• White House: Office of Science and Technology Policy (OSTP)• National Institute of Science and Technology (NIST)• European Central Bank (ECB)• Financial Stability Board (FSB)• Basel Committee on Banking Supervision• European System of Financial Supervision (ESFS)• European Banking Authority (EBA)• European Security and Markets Authority (ESMA)• European Commission (EC): Directorate General for Financial Stability,
Financial Services and Capital Markets Union (DG FISMA)• European Reporting Framework (ERF)• European Systemic Risk Board (ESRB) • European Insurance and Occupational Pensions Authority (EIOPA)• Single Resolution Board (SRB)
Data Management Principles
Principles of Data Management
Content Infrastructure Data Quality Governance Integration
1. Executive Air Cover with Visible Support2. Line of Business Alignment with Commitment3. Enterprise Wide Ontology stored as Metadata4. Reverse Engineering of Business Processes5. Authority via Mandatory Policy6. Resources for Sustainability
STRATEGY• Data Strategy• Cultural Alignment• Stakeholder Commitment
FORMALITY• CDO/ODM• Policy Compliance• RACI (accountability)
INFRASTRUCTURE• Data Domains and Mapping• Identifiers and X-reference• Conceptual Model/Unified View of
Meaning• Business Definitions• Physical Data Models• Metadata Repository
DQ/CONTROL• Reverse Engineering• Data Lifecycle• Business Requirements to Data
Requirements• Fit-for-Purpose Quality
Organizational Goals
Data Content Goals Operational Goals
COLLABORATION• Coordinate with IT• Align with Control Functions• Data Flow Forensics• Technical Integration
GOVERNANCE• Funding• Roadmaps and Project Plans• Metrics and Reporting• Communication• Education and Training
Financial Industry Business Ontology (FIBO)
FIBO is a business conceptual model that precisely describes financial instruments,
pricing, legal entities and financial processes (what they are and how they work)
FIBO facilitates data harmonization across disparate repositories based on legal meaning and
contractual obligation
FIBO provides structural validation to ensure completeness,
consistency and allowable values
FIBO feeds analytical processes with trusted data and powers smart contracts
FIBO is expressed in the W3C standard (RDF/OWL) for flexible and scenario-
based/inference analysis
FIBO is built on state-of-the-art collaboration technology and supported by documented and tested governance
Infrastructure for linking users into the “Build, Test, Deploy, Maintain”
process is fully operational
(generate diagrams from OWL and incorporate changes from diagrams to OWL)
FIBO – Collaboration Process is OPERATIONAL
Unified repository linking all FIBO domain ontologies has been delivered
(published on spec.edmcouncil.org/fibo)
automated testing and generation of machine executable FIBO
FIBO Master and FIBO Release are OPERATIONAL
Tools are now in place toexpedite SME verification of domain models
FIBO Model Validation Pathway
Foundational Elements(core components needed to express
financial concepts)
FIBO-FoundationsBusiness Entities
Financial/Business ConceptsIndices/Indicators
FIBO Content Teams(organized and validated)
EquitiesCorporate Bonds
Interest Rate SwapsLoan Concepts
Model Validation(member SME activity ready for rollout
and implementation)
DerivativesDebt (beyond corporate bonds)
MortgagesFunds
Rights/WarrantsPricing
Financial Processes (corporate actions, issuance, securitization)
DELIVERED Organized and Regular Meetings
Operational Rollout 2017
Continual Enhancement
Regulation W (business rules) – CompletedState Street (unified meaning and classification) – Completed
|-------------------------------------------------------|
CFTC (navigation across multiple counterparties) – 2Q1725 Member Use Cases (EDW Conference) – April 2017
|-------------------------------------------------------|
FIBO Training & Certification – Planned 2018FIBO Applications Event – Planned 2018
FIBO Pilots and POCs to Demonstrate Potential
FIBO Contributors
State Street - FIBO Interest Rate Swap DemoArthur Keen, Managing Director, Cambridge Semantics
Business Objectives
• Purpose: Demonstrate Real World Capability- The practicality of using FIBO to harmonize diverse derivative and entity data- The usefulness of FIBO for comprehensive reporting and analytics, both traditional and
innovative
• PoC approach: Apply FIBO to operational “In the wild” data- Implement using a state-of-the-art semantics platform
• Rapid implementation, no coding required
• Project Participants:State Street Business requirements and operational dataEDM Council FIBO mode and recommended reports/analytics
Cambridge Semantics Operational platform and implementation services
dun & bradstreet Business Entity and Corporate Hierarchy data
Wells Fargo FIBO consultation
State Street Bank/D&B/EDM CouncilFIBO PoC Solution Architecture
FrontArenaData
Dun &BradstreetData
Internal Data Sources
Map & Load (QA) Link & Query (Classification, analytics)
External Data Sources
Derivatives Data
Entity &Corp. Hierarchy
Data
Reports & Analytics
© 2016 State Street Corporation. All rights reserved. Information Classification: Limited Access16
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