Black Ice Partners is a global risk management consulting firm with over 20 years of experience in the financial services industry, offering clients a comprehensive understanding of best risk management practices and continually updated services to address evolving regulations through practical industry experts who have implemented Basel standards around the world.

2. • Black Ice Partners is a global risk management consulting
and technology firm with over 20 years experience in the
Experience financial services industry, and with clients ranging from
large global financial institutions, to small domestic banks.
• We have a comprehensive understanding of best risk
management practices, and continually update our
Knowledge services to cover constantly evolving regulations and
demands.
• We are a practical and experienced team of industry
Implementatio veterans who have been part of at least ten Basel
n implementations around the world, and our partners are
industry recognized experts.
Solution • Black Ice Risk Data Aggregation Solution (RDAS)

3. 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
Implementation of Basel II AIRB Compliance
Bank
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
Global Bank
Management, 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

4. 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

5. 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
Operational Black Ice Retail Credit Models that organizes data and feeds analytic
Risk RDAS engines:
 BRC Wholesale Credit Data Model
 BRC Retail Credit Data Model
 BRC Market Data Model
 BRC Operational Risk Model
Allows a financial institution to meet the following
Market regulatory requirements:
Risk
 Risk Data Aggregation & Reporting (2016)
 Global Legal Entity Identifier
 Basel II/III
 Capital and Risk Weighted Asset calculations

7. Basel Committee on Banking Supervision (BCBS) – Basel II and III
 Guidance on international standards on capital adequacy, and principles for effective banking supervision
BCBS – Risk Data Aggregation & Risk Reporting
 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
 The Global Legal Entity Identifier is designed to accurately identify financial transactions.
Country Specific Regulator Guidance
 Implementation Notes on Data Maintenance, that prescribe Senior Management Oversight, Data
Collection and Data Processing guidelines.

8. Governance & Infrastructure
How does an
Data Arch and IT
Governance institution
Infrastructure
effectively
operationalize
regulatory
requirements?
Risk Data Aggregation
Capabilities
Risk Data Aggregation Solution
Accuracy and
Integrity Completeness
Data
?
Timeliness Adaptability Aggregation
BITS

Risk Reporting
The majority of
institutions will
Accuracy Comprehensive require an
investment in
technology
Frequency Clarity solutions to meet
requirements

9. Level 1 Level 2 Level 3 Level 4
Infancy Developing Mature Leading
Collaboration of business
Limited involvement of Top management actively
Localized Initiatives driven and IT mangers with senior
senior business and engaged in enhancing the
Executive Sponsorship by individual IT teams management in information
management sponsorship
enterprise
integration
Business driven data Functional areas own data
Lack of data ownership; No
Assigned data caretaking governance; Augmented by assets and benefit from
defined responsibilities for
Data Governance caretaking of data
for selected data sets IT support and senior business executive
infrastructure support
Data accuracy and Data accuracy and
Data consolidation is
completeness is trusted
Data Quality and Data is not trusted, not
consolidated & errors are
underway, basic data
completeness is trusted
enterprise-wide; Quality is
within silos; Quality tools
Integrity corrected manually
quality requirements have
and & processes in place actively monitored &
been defined
improved
Standardized data model
Single and widely used located in a central
No enterprise reference Defined data model but not data model but lacking
Data Architecture data model in use widely used formalized governance of
repository, centrally managed
and governance model well
the model 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

10. Undefined
Data Ownership
at the Enterprise
Level
Single View of
Client and
Data Quality
Relationship to
Exposures
Data
Aggregation
End-to-end data Inconsistent or
element Inaccurate
identification  Reporting
Complex and Inadequate
Comprehensive Structure or
Regulatory Framework for
Requirements Data

11.  Do you understand the impact of IT projects across the entire organization, or only with systems with
direct relationships (i.e., one-step removed)?
 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?
 Do you know how accurate your data is, are you confident that all reports reflect the same information?
 Do you know your data strategy, is there an enterprise or a business-level strategy?
 How comprehensive is your data framework and data policies to support your approach and to ensure
regulatory requirements and senior management expectations?
 Has your institution identified Mandatory Risk Data from origination to reporting/calculation?
 Has your institution identified controls to ensure accuracy for Mandatory Risk Data?
 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.

12.  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
 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
 Inadequate data aggregation, insufficient risk reporting and ineffective IT systems were seen as a
significant contributor to the financial crisis
- Thompson Reuters
 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
 Risk data and reports should provide management with the ability to monitor and track risks relative to
the bank’s risk tolerance/appetite.
- BCBS
 Common data governance and management issues are found across the industry with data aggregation
as a critical foundation for resolution
- Deloitte & Touche LLP

14. IBM PureData System

15. BCBS
Global Legal Risk Data
Identity Aggregation
Identifier and Risk
Reporting
Board and
BCBS
Senior
Capital
Management
Calculations
Reporting

16. The solution provides critical advantages to the client in the areas of:
 Platform agnostic, enterprise-wide risk infrastructure covering Market, Operational, Credit Risk (across retail &
Wholesale asset classes)
 Cost effective solution available as measured in Total Cost to Acquire and Cost to Maintain
 Rapid time to deploy (typically between 3 to 8 months to implement and achieve full compliance)
 Compliant with regulator requirements for end-to-end data lineage
 Supports disparate data and reporting requirements across
- Management reporting;
- Board of Directors reporting;
- Regulatory reports; and
- Regulatory audit processes.
 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
 Delivers the capability for a single identifier across the institution
 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.
 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.

17. Improved Decision Making
Improved
Improved speed at which quality of
information is available strategic
planning
Enhanced Reduced probability
Improved ability to management of of losses resulting
manage risks information across from weak risk
the institution management

18. Implement
Self Assessment Define Strategy Common
(Consulting Firm and/or (Consulting Firm and/or
Financial Institution) Financial Institution)
Data Model
(Black Ice Technologies)

19. Data Models by Asset Class (4):
Provides the capability for an institution
to be BCBS data and GLEI compliant
ONE Includes comprehensive library of
regulatory and Board & Management
reports out of the BOX
Analytics (yes/no):
Provides the capability to leverage
TWO stored procedures inside the RDAS, or
leverage existing analytic engines
currently in use at the institution

20. PureData
IBM
Data
Wholesale Retail Market Operational
Model
s
Black Ice / 3rd Party / None
RWA RWA RWA RWA
Implementation Options:
Stored Procedures
Economic Capital Economic Capital Economic Capital Economic Capital
Analyti Stress Testing Stress Testing Stress Testing Stress Testing
c RAROC RAROC Risk Rating Models
Engine
Liquidity Risk Risk Rating Models eVaR
s
Includes Core
Templates
Report
Management + Management + Management + Management +
Regulatory Regulatory Regulatory Regulatory
Report Reports Reports Reports Reports
s

21. 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 Market Risk (B2.5)
Financial
• 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
• Physical Analysis
• Mortgages
/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
• Securities Reconciliation
OR
• Exposure
Measurement Finance Identity Regulatory Capital
Identifier Calculation
Special Products
• Securitization • Non-Traded GL Data
Equities RAROC & Economic
Capital
Finance Systems
• Detailed GL • Financial
Postings Hierarchies Internal
Reporting Stress Testing and
Audit Back Testing
Source
Systems feed Regulatory Board Management
Metadata
into Repository
Physical/Logic
al Data Model

22. The BlackIce RDAS is already mapped to the following downstream Risk Applications:
 SAS
 Moody’s Analayitcs
 ALGO Risk Watch
 Sungard Adaptiv,
 Sungard Panaroma,
 Sungard Front Arena
 Sungard B2CM
 Sungard BancWare
 Moodys KMV
 Several G/L
The BlackIce RDAS is already mapped to these upstream aggregated data warehouse models:
 FSLDM
 BDW
 Razor
 Murex
 Calypso
 Xtrader
 Misys
 Sophus

24. 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

25. Financials - Asia Financials - USA

26. 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

27. Investment Proposal
 $300K -$500K Required
 Set up a syndicate structure – Limited Partnership
 Funds Invested as Shareholders loan
 Loan paid before majority Shareholders loan
 Interest paid on the Investment beginning 12Months from date of Investment
 Syndicate receives 15% - 25% of Equity depending on amount Invested
 Board Seats
Use of Funds
 Hire staff for upcoming projects
 Bridge financing for operations
 Finish documentation for RDAS solution
 Marketing efforts
 Finish development and packaging of the GCD Solution