2. BLACK ICE - WHO WE ARE
• Black Ice Partners is a global risk management consulting and
technology firm with over 20 years experience in the financial
Experience services industry, and with clients ranging from large global
financial institutions, to small domestic banks.
• We have a comprehensive understanding of best risk
Knowledge management practices, and continually update our services to
cover constantly evolving regulations and demands.
• We are a practical and experienced team of industry veterans who
Implementation have been part of at least ten Basel implementations around the
world, and our partners are industry recognized experts.
Solution • Black Ice Risk Data Aggregation Solution (RDAS)
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3. OUR TRACK RECORD
Client Work Description
Malaysian Bank A ICAAP Gap Analysis
Malaysian Bank B Enterprise Risk Management Risk Data Mart
Canadian Banks (2) Road Map for Basel AIRB Compliance and Gap Analysis Report
South Korean Bank Implementation of Basel II AIRB Compliance
Singaporean / Taiwanese Bank Implementation of Basel II AIRB Compliance
Canadian Bank C Road Map for Basel AIRB Compliance and Gap Analysis Report
Canadian Bank D ERM Risk Data Mart
Singaporean Bank Road Map for Basel AIRB Compliance and Gap Analysis Report and ICAAP
Nth American Bank Road Map for Basel AIRB Compliance and Gap Analysis Repo
Data Warehouse Provider Enterprise Risk Management Risk Data Mart
Independent Audit of ICAAP Implementation on behalf of Board and Senior Management,
Global Bank
Basel III and Dodd Frank Gap Analysis and readiness
Malaysian & Indonesian& Thai Training to the directors and management of various banks on Basel III and ICAAP, Risk
Regulators Governance, Ent Risk Mgmt, Techniques in Risk Management
Malaysian Investment Bank Training for Bank risk team on ICAAP, Risk Appetite, RAROC, Basel III
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4. OUR TRACK RECORD
Client Work Description
Taiwanese Bank ICAAP Gap Analysis
Australian Bank Enterprise Risk Management Risk Data Mart
Thailand Bank Road Map for Basel AIRB Compliance and Gap Analysis Report
Canadian Bank Implementation of Basel II AIRB Compliance
Hong Kong Bank Implementation of Basel II AIRB Compliance
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5. BLACK ICE RISK DATA AGGREGATION SOLUTION (RDAS)
A Physical/Logical Data Model framework developed
on IBM PureData that enables the organization of data
efficiently and effectively in a way that makes sense.
Wholesale
Credit
The Black Ice Risk Data Aggregation Solution (RDAS)
addresses all levels of Basel and Dodd Frank
compliance with all relevant analytic engines and
comprehensive reporting.
The Black Ice RDAS compromises of four Logical Data
Models that organizes data and feeds analytic
Operational Black Ice Retail Credit engines:
Risk RDAS u BRC Wholesale Credit Data Model
u BRC Retail Credit Data Model
u BRC Market Data Model
u BRC Operational Risk Model
Allows a financial institution to meet the following
regulatory requirements:
Market u Risk Data Aggregation & Reporting (2016)
Risk
u Global Legal Entity Identifier
u Basel II/III
u Capital and Risk Weighted Asset calculations
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7. CAPABILITIES FINANCIAL INSTITUTIONS MUST MEET
Basel Committee on Banking Supervision (BCBS) – Basel II and III
u Guidance on international standards on capital adequacy, and principles for effective banking supervision
BCBS – Risk Data Aggregation & Risk Reporting
u A set of principles to strengthen banks’ risk data aggregation capabilities and risk reporting practices.
National supervisors expect G-SIBs to implement these principles by 2016.
Financial Stability Board – Global Legal Entity Identifiers
u The Global Legal Entity Identifier is designed to accurately identify financial transactions.
Country Specific Regulator Guidance
u ImplementationNotes on Data Maintenance, that prescribe Senior Management Oversight, Data
Collection and Data Processing guidelines.
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8. EVOLVING & EMERGING REGULATOR EXPECTATIONS
Governance & Infrastructure
How does an
Data Arch and IT institution
Governance
Infrastructure
effectively
operationalize
regulatory
requirements?
Risk Data Aggregation
Capabilities
Risk Data Aggregation Solution
Accuracy and
Integrity Completeness
Data
?
Timeliness Adaptability Aggregation
BITS
u
Risk Reporting
The majority of
institutions will
Accuracy Comprehensive require an
investment in
technology
Frequency Clarity solutions to meet
requirements
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9. INDUSTRY MATURITY ANALYSIS – INVESTMENT REQUIRED
Level 1 Level 2 Level 3 Level 4
Infancy Developing Mature Leading
Collaboration of business
Limited involvement of senior Top management actively
Localized Initiatives driven by and IT mangers with senior
business and management engaged in enhancing the
Executive Sponsorship individual IT teams management sponsorship
in information integration enterprise
Business driven data Functional areas own data
Lack of data ownership; No
Assigned data caretaking for governance; Augmented by IT assets and benefit from
defined responsibilities for
Data Governance caretaking of data
selected data sets support and infrastructure senior business executive
support
Data accuracy and Data accuracy and
Data consolidation is
Data is not trusted, not completeness is trusted completeness is trusted
Data Quality and consolidated & errors are
underway, basic data quality
enterprise-wide; Quality is
within silos; Quality tools and
Integrity corrected manually
requirements have been
& processes in place actively monitored &
defined
improved
Standardized data model located
Single and widely used data in a central repository, centrally
No enterprise reference data Defined data model but not model but lacking formalized managed and governance model
Data Architecture model in use widely used governance of the model well known across the enterprise
No organized BI plan or BI Strategy linked to BI strategy integrated with
Data Analytics & strategy; Lack of alignment Multi-year BI strategy and functional strategy; benefits the Enterprise information
Business Intelligence to business objectives budget tracked & realized needs and strategy
BITS Implementation Industry Average
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10. MAIN DRIVERS OF THE PROBLEM FOR AN INSTITUTION
Undefined
Data Ownership
at the Enterprise
Level
Single View of Client
and Relationship to Data Quality
Exposures
Data
Aggregation
End-to-end data Inconsistent or
element Inaccurate
identification u
Reporting
Complex and Inadequate
Comprehensive Structure or
Regulatory Framework for
Requirements Data
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11. QUESTIONS INSTITUTIONS CANNOT USUALLY ANSWER
u Do you understand the impact of IT projects across the entire organization, or only with systems with
direct relationships (i.e., one-step removed)?
u Do you know who owns your data, is there a central group that will drive changes, or does each business
unit determine their own priorities?
u Do you know how accurate your data is, are you confident that all reports reflect the same information?
u Do you know your data strategy, is there an enterprise or a business-level strategy?
u How comprehensive is your data framework and data policies to support your approach and to ensure
regulatory requirements and senior management expectations?
u Has your institution identified Mandatory Risk Data from origination to reporting/calculation?
u Has your institution identified controls to ensure accuracy for Mandatory Risk Data?
u What validation/monitoring do you perform on data quality?
Actual Observations at financial institutions
• ALCo reports being generated using incorrect data. The data dictionary was incomplete, and the business
thought the data was “real-time/current” and was the same value as the book of record.
• Retail risk reports being generated by two different groups for different purposes, but the values for the
same period did not match. Neither group could determine which was the correct value.
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12. WHAT IS BEING SAID ABOUT DATA AGGREGATION
u G-SIBs
need to act now to meet the deadline, but those that embrace this opportunity to deliver strategic
change will gain competitive advantage.
- Deloitte EMEA Centre for Regulatory Strategy
u Overall,we see further evidence in these changes of the shift from risk as a compliance function to risk
as a support function for improved performance across the business. And, as we look ahead, the baseline
is that G-SIBs have got to get moving and start investing in the systems that will keep them on track
towards the 2016 deadline.
- IBM Integrated Risk Platform
u Inadequate data aggregation, insufficient risk reporting and ineffective IT systems were seen as a
significant contributor to the financial crisis
- Thompson Reuters
u The
financial crisis revealed that many banks, including global systemically important banks (G-SIBs),
were unable to aggregate risk exposures and identify concentrations fully, quickly and accurately. This
meant that banks' ability to take risk decisions in a timely fashion was seriously impaired with wide-
ranging consequences for the banks themselves and for the stability of the financial system as a whole.
- The Asian Banker
u Riskdata and reports should provide management with the ability to monitor and track risks relative to
the bank’s risk tolerance/appetite.
- BCBS
u Common data governance and management issues are found across the industry with data aggregation
as a critical foundation for resolution
- Deloitte & Touche LLP
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14. BLACK ICE RDAS – THE SOLUTION PARTNERS
BLACK ICE
IBM PureData System TECHNOLOGIES
BLACK ICE
RDAS
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15. BLACK ICE RDAS – PROVIDES COMPLIANCE
BCBS
Global Legal Risk Data
Identity Aggregation
Identifier and Risk
Reporting
Board and
BCBS Capital Senior
Calculations Management
Reporting
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16. BLACK ICE RDAS – OUR DIFFERENTIATION
The solution provides critical advantages to the client in the areas of:
u Platform agnostic, enterprise-wide risk infrastructure covering Market, Operational, Credit Risk (across retail &
Wholesale asset classes)
u Cost effective solution available as measured in Total Cost to Acquire and Cost to Maintain
u Rapid time to deploy (typically between 3 to 8 months to implement and achieve full compliance)
u Compliant with regulator requirements for end-to-end data lineage
u Supports disparate data and reporting requirements across
- Management reporting;
- Board of Directors reporting;
- Regulatory reports; and
- Regulatory audit processes.
u Provides a foundation for future risk requirements (e.g., by BCBS or by the regulator) through the enterprise risk
data foundation schema, resulting in a reduced effort to assess and meet new requirements
u Delivers the capability for a single identifier across the institution
u Other solutions such as RDAS exist, but are expensive and often are in-house bespoke solutions built by financial
institutions themselves that focus on Integrated Enterprise Wide Risk and Capital Data.
u RDAS is what a Global Financial Institution usually builds for itself given the resources and knowledge they have
in-house but at a significantly higher cost.
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17. BENEFITS OF HOLISTIC DATA AGGREGATION & REPORTING
Improved Decision Making
Improved quality
Improved speed at which
of strategic
information is available
planning
Enhanced Reduced probability
Improved ability to management of of losses resulting
manage risks information across from weak risk
the institution management
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18. HOW DOES RDAS FIT INTO THE IMPLEMENTATION
SOLUTION
Implement
Self Assessment Define Strategy Common
(Consulting Firm and/or
Financial Institution)
(Consulting Firm and/or
Financial Institution)
Data Model
(Black Ice Technologies)
18

19. IMPLEMENTATION OPTIONS FOR RDAS
Data Models by Asset Class (4):
Provides the capability for an institution to
ONE be BCBS data and GLEI compliant
Includes comprehensive library of
regulatory and Board & Management
reports out of the BOX
Analytics (yes/no):
Provides the capability to leverage stored
TWO procedures inside the RDAS, or leverage
existing analytic engines currently in use at
the institution
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20. PureData RISK DATA AGGREGATION SOLUTION – COMPONENTS
IBM
Data
Retail Market Operational
Models Wholesale
Black Ice / 3rd Party / None
RWA RWA RWA RWA
Implementation Options:
Stored Procedures
Economic Capital Economic Capital Economic Capital Economic Capital
Analytic Stress Testing Stress Testing Stress Testing Stress Testing
Engines RAROC RAROC Risk Rating Models
Liquidity Risk Risk Rating Models eVaR
Includes Core
Templates
Report
Management + Management + Management + Management +
Regulatory Regulatory Regulatory
Reports Reports
Regulatory
Reports Reports Reports
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21. RISK DATA AGGREGATION SOLUTION – DATA
ARCHITECTURE
Source Systems
BLACK ICE
Corporate and Commercial RDAS
Banking Systems
• Risk Rating • Collections and Credit Risk Retail/Wholesale
Solution By
Systems Workout Systems SQL / DataStage
• Credit Approval • Trading Systems Operational Risk (AMA)
Systems • Trading Exposure Financial
Market Risk (B2.5)
• Credit Servicing Systems Data
Systems
Basel II Basel II.5 Basel III
Retail Banking Systems
• Small Business • Retail Portfolio
Credit Management
External Application Data Mart
In Database Analytic Engines
• Credit Card • Analytics and Concentration Risk
Products Decision Support
Analysis
• Mortgages
• Physical /Logical
Data Model
Trading Room Credit Risks Risk Adjusted Pricing &
• Facility • Collateral • Basel Asset RAPM
Apportionment Management and Classes
• Ratings Systems Valuation Financial • Global Legal
• Exposure • Securities Reconciliation
OR
Measurement Finance Identity Identifier Regulatory Capital
Calculation
Special Products
• Securitization • Non-Traded GL Data
Equities RAROC & Economic
Capital
Finance Systems
• Detailed GL • Financial
Postings Hierarchies Internal
Reporting Stress Testing and Back
Audit Testing
Source
Systems feed Regulatory Board Management
Metadata
into Physical/ Repository
Logical Data
Model
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22. MAPPING AVAILABLE FOR SEVERAL RISK APPLICATIONS
The BlackIce RDAS is already mapped to the following downstream Risk Applications:
u SAS
u Moody’s Analayitcs
u ALGO Risk Watch
u Sungard Adaptiv,
u Sungard Panaroma,
u Sungard Front Arena
u Sungard B2CM
u Sungard BancWare
u Moodys KMV
u Several G/L
The BlackIce RDAS is already mapped to these upstream aggregated data warehouse models:
u FSLDM
u BDW
u Razor
u Murex
u Calypso
u Xtrader
u Misys
u Sophus
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24. CURRENT OPPORTUNITIES – PHASE ONE
Client Country Status Contract Period
Siam Commercial Bank Thailand Final contract negotiations ~$400k + Q2
Bank of China China Workshop / Proof of Concept ~$1.0M – $2.0M + Q3
China Guangfa Bank China Workshop / Proof of Concept ~$1.0M – $1.5M + Q3
Bank of Bejing China Engagement Started ~$1.0M + Q4
Chengdu Bank China Engagement Started TBC Q4
SBV Vietnam RFP Process with IBM ~$2.0M + Q2/Q4
TMX Group Canada Engagement Started ~$1.0M (plus reseller license) + Q3
Sales Focus
§ Initial sales effort started in Thailand, Philippines, Indonesia and Vietnam due to the infancy of the
financial system
§ Countries are mandated to implement BCBS guidelines as directed by the timelines provided by their
home regulator (see market size in appendix)
Existing Partnerships
§ IBM
§ Deloitte, PwC, Pactera, Camelot, Digital China
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25. PROJECTED FINANCIALS
Financials - Asia Financials - USA
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26. BLACK ICE RDAS – PRICING STRATEGY
Option 1 Option 2
Risk Data Aggregation
Report Templates
Analytics No Analytics
Purchase: $2.5M Purchase: $2.0M
Lease: $110k/month – 3 year contract Lease: $100k/month – 3 year contract
Purchase Option: Support is optional and fixed at 10% - No obligation
Lease Option: Support is included in lease payment
Hardware costs are extra and dependent on size requirements
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27. INVESTMENT PROPOSAL & USE OF FUNDS
Investment Proposal
u $300K -$500K Required
u Set up a syndicate structure – Limited Partnership
u Funds Invested as Shareholders loan
u Loan paid before majority Shareholders loan
u Interest paid on the Investment beginning 12Months from date of Investment
u Syndicate receives 15% - 25% of Equity depending on amount Invested
u Board Seats
Use of Funds
u Hire staff for upcoming projects
u Bridge financing for operations
u Finish documentation for RDAS solution
u Marketing efforts
u Finish development and packaging of the GCD Solution
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