My co-ordinates
• LinkedIn: Greg Soulsby• Twitter: #model_dr• Email: [email protected]
You will learn how to:
• Show your management team how data architecture helps meet BCBS239 using his “BCSB239 Model driven solutions checklist” tool.
• Demonstrate compliance to each of the principles by re-purposing your information architecture
• Meet the obligations more efficiently by leveraging FIBO and semantic technology
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Deutsche Bank Libor fine: Seven crazy things traders said about Libor that cost the bank billions
On 21 February 2005, a trader requested of another trader who performed submitter duties on a back-up basis:
Trader 1: "can we have a high 6mth libor today pls gezzer?"Trader 2: "sure dude, where wld you like it mate ?" Trader 1: "think it shud be 095?"Trader 2: "cool, was going 9, so 9.5 it is." Trader 1: "super – don’t get that level of flexibility when [the usual submitter] is in the chair fyg [for your guidance]!“
London CitiAm 2015-04-23
Merrill Lynch hit with £13.2m fine
• The watchdog said the amount levelled at the firm “reflects the severity of MLI's misconduct, failure to adequately address the root causes over several years despite substantial FCA guidance to the industry, and a poor history of transaction reporting compliance”.
• Georgina Philippou, FCA's acting director of enforcement and market oversight, said: “Proper transaction reporting really matters. Merrill Lynch International has failed to get this right again – despite a private warning, a previous fine, and extensive FCA guidance and enforcement action in this area.
London CitiAm 2015-04-23
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Many sources
Multiple views of multiple sources is the data challenge
OpenGamma(Postgress)
Reference Data
Corep Finrep(XBRL Taxonomy)
Spreadsheets
View 1
View 2
View 3
View 4
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Data warehouse
Front office systemClient ID Name Client
type1 Thatcher Gold2 Blair Silver3 Cameron Bronze
Risk system
Client ID
LEI Name Client type
Risk Rating
1 987 Thatcher Gold High
2 654 Blair Silver Medium
3 654 Cameron Bronze Medium
321 Obama LowLEI Name Risk rating
987 Thatcher High654 Blair Medium321 Obama Low
Warehouse duplicates & transforms the data
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Therefore BCBS239
• Why?• What?
o 1 Governanceo 2 Data architecture and IT infrastructure o 3 Accuracy and Integrityo 4 Completenesso 5 Timelinesso 6 Adaptabilityo 7 Accuracyo 8 Comprehensivenesso 9 Clarity and usefulnesso 10 Frequencyo 11 Distributiono 12 Reviewo 13 Remedial actions and supervisory measureso 14 Home/host cooperation
• Who?o Systemically important
bankso Others to follow
• When?• Jan 2016 for SIB• Others later
• How?• Periodic review by
supervisor• Supervisor to supervisor
cooperation
http://www.bis.org/publ/bcbs239.pdf
Show your management team how data architecture helps meet BCBS239 using his “BCSB239 Model driven solutions checklist” tool.
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BCBS239 Programme management tool
• Each row is a obligation paragraph• Columns for
o Output• Obligation #• Section• Description etc• Evidence required
o Input• Level of compliance• Level of evidence• Priority• Owner
• Tool calculateso Readiness score for each obligationo Programme reediness scoreo Averages
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Breakouts
For your BCBS239 paragraphs report back on
• Appropriate evidence• How it implement in Magicdraw
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The Data Point Model
Value Value SetData Point
Aspect
Context
Many
Value
1
The data point meta model separates the data points and their values
And treats concept relationships as data
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Traditional strategy
Example DPM with instance data
DoBs Client
1925-10-13 Thatcher
1953-05-06 Blair
1953-05-06 Cameron
Data Point Model
Aspect Values
1945-01-011953-05-06
Aspect ValuesThatcher
Blair
Cameron
DPs!6#^
7f%$
^rrA
FQ!@
~A¬0
Aspects
DoB
Client Rule
s
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ModelDRExisting systems
Data Point Model architecture
OpenGamma(Postgress)
EBA COREP(Access)
Corep Finrep(XBRL Taxonomy)
Spreadsheets
Data point models
EBA COREP
Spreadsheets
Corep Finrep
FIBO
Open Gamma
In place
access
Sem
antic
s
View 1
View 2
View 3
View 4
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Demonstration subject matter
Para 33: Must have taxonomyPara 34: Data is aligned to
that taxonomyPara 40: Data qualityPara 50: On demand slice
and dice…..……
http://www.bankofengland.co.uk/
statistics/Documents/about/dqf.pdf
http://www.edmcouncil.org/
dataquality
EDM Council Data Quality standard• Completeness, • Coverage, • Conformity, • Consistency, • Accuracy, • Duplication, • Timeliness
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Demonstration
1) Model Spreadsheet report2) Model database table3) Enrich the data points of the reports with their Source system4) Enrich the data points of the reports with their Time cycles5) Synthesis a common view of the 2 data sources using FIBO6) Assign the data points to the US GAAP7) Provide analysis, report and data quality metrics
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1: Untangle a spreadsheet
Report NameY Axis Aspect Y Axis Value Set Name Y Axis Coordinate Aspect Values
ReportableAspect
X Axis Aspect
X AxisValue Set
X AxisCoordinateAspect Values
Reportable Aspect Values
Reverse engineer
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Business Entity
Class Level Adaptor
Attribute Adaptors
Adaptors Class Level Aspect
Attribute Level Aspect
Attribute LevelValue Sets
Resources
2. Untangle an existing data base
Reverse engineer
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5) Synthesis a common view of the 2 data sources using FIBO
Wire together
FIBO Model
Spreadsheet model
Integrated model
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6) Assign the data points to the US GAAP
Reverse engineer
Integrated model
US GAAP model
Wire together
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7) Provide analysis, report and data quality metricsYou now have a complete database• Reports• Ad-hoc queries• Inferencing queries
Systems
Data management tooling
Reporting and analytics Regulator
Duplication
Coverage
ConsistencyAccuracy
completeness
conformity
The model in the BCBS239 ecosystem
Roles
modelDR
Trading systems
Calculation Engine
Reg Report needs
(e.g. XBRL taxonomy)Spreadsheets
Risk systems
Data warehouses
Report writer
Data modelling
Ontology management
Data Architect
Business Domain Expert
Data Owner
FIBO
Cross DBDQ Queries
Data quality metrics
Meta data Analysis
Definition of Good
Data QualityReport Designs
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Resource search terms
• Data Quality Webinar: May 19th “How can I measure the quality and integrity of my data”
• Paper: BCBS239 Principle of Risk Data Aggregation• Progress report: BCBS Progress in adopting the principles for effective
risk data aggregation and risk reporting • Data Point Model: ECB Data Point Model• XBRL: XBRL Abstract Model