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)




         2
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




                     3
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




                  4
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




              5
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.




                     7
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




                                               8
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



                 9
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



         10
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.




                    11
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




                  12
BLACK ICE RDAS – THE SOLUTION PARTNERS




                                     BLACK ICE
IBM PureData System                TECHNOLOGIES




                    BLACK ICE
                      RDAS




         14
BLACK ICE RDAS – PROVIDES COMPLIANCE




                               BCBS
             Global Legal    Risk Data
               Identity     Aggregation
              Identifier     and Risk
                             Reporting


                             Board and
             BCBS Capital     Senior
             Calculations   Management
                             Reporting




        15
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.




                         16
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


          17
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
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




       19
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




                                          20
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



                              21
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




                  22
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




                     24
PROJECTED FINANCIALS


Financials - Asia        Financials - USA




                    25
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




          26
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




                  27
Black ice technologies rdas (finance)
Black ice technologies rdas (finance)

Black ice technologies rdas (finance)

  • 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) 2
  • 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 3
  • 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 4
  • 5.
    BLACK ICE RISKDATA 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 5
  • 7.
    CAPABILITIES FINANCIAL INSTITUTIONSMUST 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. 7
  • 8.
    EVOLVING & EMERGINGREGULATOR 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 8
  • 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 9
  • 10.
    MAIN DRIVERS OFTHE 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 10
  • 11.
    QUESTIONS INSTITUTIONS CANNOTUSUALLY 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. 11
  • 12.
    WHAT IS BEINGSAID 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 12
  • 14.
    BLACK ICE RDAS– THE SOLUTION PARTNERS BLACK ICE IBM PureData System TECHNOLOGIES BLACK ICE RDAS 14
  • 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 15
  • 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. 16
  • 17.
    BENEFITS OF HOLISTICDATA 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 17
  • 18.
    HOW DOES RDASFIT 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 FORRDAS 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 19
  • 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 20
  • 21.
    RISK DATA AGGREGATIONSOLUTION – 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 21
  • 22.
    MAPPING AVAILABLE FORSEVERAL 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 22
  • 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 24
  • 25.
    PROJECTED FINANCIALS Financials -Asia Financials - USA 25
  • 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 26
  • 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 27