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TRANSCRIPT
Business Intelligence to Drive Risk Management Improvement
25 April 2013
Craig Rowlands
Head of Decision Systems
Page 1 of 12
Table of Contents
• How do we achieve automation and productivity gains
• Leveraging data structures to derive key business outcomes
• The range of business intelligence reporting capability available today
• How do we achieve true innovation
Page 2 of 12
4 Key Actions
Job scheduling tools supervise a logical process (several jobs or programs) as they execute in a mainframe or distributed environment, providing scheduling and dependency management of the process as it runs, mainly in sequence, across disparate systems, geographies and applications.
Parallel processing or multi threading - the solution of a single problem across more than one processor. Parallel processing allows distribution across the platform utilizing all available processing capability.
Page 3 of 12
How Do We Achieve Automation and Productivity Gains
What does that mean?
• Faster run times.
• Reduced errors due to less human interaction.
• Job starts as soon as the batch process completes.
• If errors occur ability to resolve the error without having to start the process from the beginning.
• Sequenced controls and checks.
• Usage of simulations tools to optimize the batch processing.
Job Scheduling and batch triggers
Page 4 of 12
How Do We Achieve Automation and Productivity Gains
Parallel processing/Multi threading
Page 5 of 12
How Do We Achieve Automation and Productivity Gains
Data Quality Controls & Checks
Material Data Elements are monitored across the Production Process in order to identify Data
Quality Issues and Attest to the Quality of Data used in the RWA Production Process. Data
Quality Measures in place for: Completeness, Accuracy, Consistency, Timeliness & Retention
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Leveraging data structures to derive key business outcomes
ENTERPRISE DATA ACCESS
INFRASTRUCTURE SUPPORT:
Text & Unstructured Data Support, Security, Meta-data & Lineage, Monitoring & Deployment
DATA
INTEGRATION DATA
QUALITY MASTER DATA
MANAGEMENT
DECISION
MANAGEMENT
Events,
Workflow &
Business Rules
MODEL
MANAGEMENT
&
MONITORING
Analytics
Management
MODEL
DEPLOYMENT
&
INTEGRATION
Infrastructure
Support
INFORMATION GOVERNANCE
STRATEGY & IMPLEMENTATION SUPPORT
Data
Management
SuperMart0 Values, volumes, percentages - business intelligence metric reporting
Mart0 Aggregated data - fact or summarized data for analytical insight
Detail0 Granular data - detailed account, product, customer level
Staging Cleansed data - formatting, removal of data corruption
ODD Raw data - replica of source systems
Page 7 of 12
Evaluate &
Build
Deploy
Operate
Data
Sourcing
Data
Requirements
‘..to develop a clear set
of model characteristics
for each product and
portfolio. This ‘shopping
list’ will form the basis of
the variables required for
model build, monitoring
and analysis
‘..to source the data.
Completing data quality
and investigation.
Providing an accurate
reflection of source data
with the required history
for the modeller to build
the scorecard. Code
must conform to the
highest standards to
ensure complete
accuracy and allowance
for dataset to become a
production asset.
‘to evaluate the data
provided and use this to
build a strong model.
‘to rigorously complete
pre-production testing
prior to deployment in an
operational
environment.’ ‘..to run the model on a
monthly basis in an
operational environment
completing thorough
controls and checks to
ensure its accuracy.’’
Leveraging data structures to derive key business outcomes
Model Ready Data – the process
Page 8 of 12
Leveraging data structures to derive key business outcomes
ENTERPRISE DATA ACCESS
INFRASTRUCTURE SUPPORT:
Text & Unstructured Data Support, Security, Meta-data & Lineage, Monitoring & Deployment
DATA
INTEGRATION DATA
QUALITY MASTER DATA
MANAGEMENT
DECISION
MANAGEMENT
Events,
Workflow &
Business Rules
MODEL
MANAGEMENT
&
MONITORING
MODEL
DEPLOYMENT
&
INTEGRATION
INFORMATION GOVERNANCE
STRATEGY & IMPLEMENTATION SUPPORT
Model Ready Data – the strategic advantage
1. Speed to Market
2. Built for future improvements and recalibration
3. Regulatory compliant
4. Multi purpose usage
5. Consistent data definitions
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The range of business intelligence reporting capability available today
Page 10 of 12
The range of business intelligence reporting capability available today
Data Discovery/Visual Analytics – Birst, Qlikview, Tableau
The Main Players BI – IBM Cognos, SAS eBI, Oracle OBIEE, Microsoft and Microstrategy
Contenders – Tibco Spotfire
Decision System suppliers – FICO, Experian
New - Pentaho, Semantifi, 1010data, Jedox, Yellowfin
Page 11 of 12
The range of business intelligence reporting capability available today
Page 12 of 12
The range of business intelligence reporting capability available today
Page 13 of 12
How do we achieve true innovation
The Innovation Lab