Fundamental Review of the Trading Book (FRTB) – Data Challenges

1. Fundamental Review of the Trading Book (FRTB) – Data Challenges

4. 4 The new framework proposed by the Basel Committee on Banking Supervision (BCBS) is in our view an improvement to the existing market risk management processes The revised framework for market risk capital requirements, also known as the Fundamental Review of the Trading Book (FRTB) during the consultative phase, seeks to remove the weaknesses around risk evaluation found in “Basel 2.5,“ by addressing the undercapitalization of the trading book. Copyright © 2016 Accenture All rights reserved. Trading and Banking Book Boundary  Clear identification of trading instruments:  Limitation in moving instruments between Regulatory Books.  Trading desk identification with clearly defined business/trading strategies. Standardized Approach (SA)  Emphasis on standardized model (SM).  Will serve as de facto” floor for capital requirements and possible benchmark between banks.  Becomes more sophisticated (sensitivities based) and narrows gaps between internal models.  Mandatory reporting of SA results. Internal Model Approach  Move away from value-at-risk (VaR) towards expected shortfall.  Introduction of non-modelable risk factors to capture residual risk.  Use of market liquidity horizons for calculating stressed market risk provisioning.  Three stage approval process – from firm-wide internal risk capital model to assessment of individual trading desks.  Use of P&L for internal model validation. HighlightsBCBS Proposed Changes A. Trading Book Boundary B. Standardized Approach C. Internal Model Approach Trading Book Boundary Internal Risk Transfer Trading Desk Identification Non-Modelable Risk Factors Default Risk Charge Covered Instruments Residual Risk Add-On Expected Shortfall Sensitivities-Based Method Profit and Loss (P&L) Attribution Backtesting Supervisory Approvals Source: Minimum capital requirements for market risk, BCBS, January 2016. Access at: http://www.bis.org/bcbs/publ/d352.pdf.

5. 5 The compliance deadline appears to be far out in the future … but the TIME TO ACT IS NOW… Although the compliance deadline of December 31, 2019 seems far into the future, banks should begin their FRTB compliance journey today in order to properly address some of these key FRTB implementation issues. Copyright © 2016 Accenture All rights reserved. Q3 2016 – Detailed project plan and gap analysis complete Q4 2016 – FRTB Project scheduling and funding aligned 2017 – Infrastructure development and facilitating technology Q1 2018 – Parallel run of FRTB begin Q1 – Q3 2019 – Supervisor approvals Dec 2019 – Compliance deadline • Banks should ideally use 2016 to organize and plan their efforts for FRTB implementation. • We are expecting FRTB rules to lead to significant technological and procedural changes in the market risk management function which would need ample lead time for implementation as required by the rules. Source: Minimum capital requirements for market risk, BCBS, January 2016. Access at: http://www.bis.org/bcbs/publ/d352.pdf, and Accenture estimates.

6. 6 Majority of FRTB rules have a direct or indirect impact on banks’ data management strategies The new market risk framework is expected to have the highest impact on banks’ data intensive activities within their risk management functions. Copyright © 2016 Accenture All rights reserved. Source: Accenture Analysis. High Impact Activities 1. Trading Book Boundary and Risk Policy 3. Internal Model Approach 2 Standardized Approach 1.1 Trade and Bank Book Boundaries 1.2 Trading Desk Identification 1.6 Risk Management Policies 1.3 Internal Risk Transfers 1.7 Reporting Requirements 1.4 Covered Instruments 3.4 Default Risk Charge (DRC) – IMA 3.5 Non-Modelable: Capital Add-Ons (Stresses Expected Shortfall) 3.1 Risk Factor Analysis 3.2 Expected Shortfall Calculation 3.6 Multi Liquidity Horizons 2.6 Residual Risk Add-On 2.4 Delta, Vega and Curvature Calculation 2.5 Default Risk Charge (DRC) - SA 3.3 Trading Desk Eligibility 3.7 Calibration to Stress Period 2.2 Establish Risk Classes 2.1 Sensitivity Based Method (SBM) 2.3 Securitization 2.7 SA Capital Calculation Methodology 3.7 IMA Capital Calculation Methodology 4.Supervisory Approvals 5.Dataand Technology 4.1 Trading Book Boundary 4.2 Exception For Covered Instruments 4.3 Instrument Redesignation 5.1 Asset Classification 5.2 Security Reference Data 5.3 Instrument Master 4.8 IMA Risk Factors 4.9 Backtesting 4.10 P&L Attribution 4.11 Changes to IMA Model 5.6 Risk Factor Pricing Data 5.7 Stress Calculations 5.8 Full Revaluation 5.9 P&L Attribution and Backtesting 5.3 Risk sensitivities data Sourcing 5.5 Capital Aggregation 5.4 Data Taxonomy 4.4 Residual Risk Add-On Approval 4.6 SBM Calculator 4.7 Model Validation 1,2,3.Functional Requirements

7. 7 It is vital to have a set of core design principles when planning the implementation of a strategic FRTB solution Copyright © 2016 Accenture All rights reserved. Planning For Compliance Now The complexity of FRTB proposals require firms to act now due to tight implementation timelines and large body of work, and put in place a program to understand the overall impact to the firm from a business and technology perspective. Think Global Not Local How to execute the FRTB framework at a global scale, given the different rules from supervisors of different jurisdictions where the organization operates in. Identify Strategic Capabilities and Synergies Leverage existing infrastructure and programs for current regulations BCBS 239, BASEL III, Comprehensive Capital Analysis and Review (CCAR), Uncleared Margin Rules (UMR), Capital Adequacy Requirements (CCR) etc. to identify strategic platforms and capabilities for further investment. Convert Regulatory Challenges into Opportunities Regulatory reform should be viewed not as a threat to growth or revenues, but as a strategic opportunity to better position the firm going forward through further improvement of existing business as usual (BAU) efforts and processes in managing risks.

8. 8 By grouping the data challenges into three major categories, banks can address their data issues in a planned manner In our assessment, the biggest areas of impact should be the data challenges arising from the new rules. Effectively addressing these is fundamental to the implementation of the FRTB framework and will be one of the foundational areas of work in any bank’s FRTB program. Copyright © 2016 Accenture All rights reserved. • The rules for SA and IMA both advocate the use of risk sensitivities and consistency in their calculation which for the first time will be required to be the same as used in the pricing models or instrument prices being used for the profit and loss that is reported to management. Risk Sensitivities Sourcing • Banks need to source pricing information for risk factors to be eligible for inclusion in IMA calculation. These market prices need to be “Real” and from observable transactions. • Due to P&L attribution there is a greater need to align front office (FO) pricing models and risk calculation engines which necessitate the need for consistent data sourcing. Market Data Sourcing • Understanding the incremental data requirements vs. the existing data calculation models and calculators is crucial as FRTB has introduced changes to the way risk charge is calculated under both SA and IMA. Risk Calculator Data Gaps Source: Minimum capital requirements for market risk, BCBS, January 2016. Access at: http://www.bis.org/bcbs/publ/d352.pdf, and Accenture analysis.

10. FRTB rules have introduced changes to the standardized approach process, as well as tightened the norms for use of IMA. Due to this banks should expect to face increased technological and process complexities. • Comprehensive calculation of risk under SA. • Previously, SA processes did not include the calculation of risk sensitivities, therefore banks may need to develop this capability. • Banks making use of IMA models may have been computing these sensitivities as part of their internal models but the computation methodology used may have differed, thus leading to changes in the technology setup. • Use of correlations between assets pairs for each risk class within each of the sensitivities add to computational challenges. • The SA has introduced the concept of curvature risk to help capture nonlinear risk, which is not captured by the delta of the instruments with optionality. • Curvature risk is not a second order approximation, but rather a full revaluation needed for every instrument affected. • New rules mandate consistency between the calculations used for computing sensitivities and the valuation models being used by FO for trading purposes. Therefore synchronizing data between FO and the Risk Office is critical. FRTB rules should result in a quantum jump in the number of calculations made using both SA and IMA Copyright © 2016 Accenture All rights reserved. 10 GIRR CSR – Non- Securitization CSR – Securitization (CTP) CSR – Securitization (Non-CTP) Equity Commodity FX Delta Individual currency 16 16 25 11 11 Individual currency Vega Individual currency 16 16 25 11 11 Individual currency Curvature Individual currency 16 16 25 11 11 Individual currency Source: Basel Committee on Banking Supervision, 2016 Under FRTB, banks have to compute at least 79 different calculation inputs (excluding General Interest Rate Risk (GIRR) and Foreign Exchange (FX) risk, also assuming that the market portfolio has assets across the buckets) for each sensitivity class for risk computation under SA. Example: The new prescribed risk factors and liquidity computation complexity may lead to ~12,000 calculations per trade compared to the current range of 250 – 500. Changes From Existing Process

11. 11 Banks should be well served if the operational and technological challenges are provided for in the implementation plan SA-based calculations are mandatory for all banks and some of the key operational and technological challenges they face include: Copyright © 2016 Accenture All rights reserved. Operational Challenges Technology Challenges 1. Maintaining consistency in FO and Risk Management data for calculating sensitivities. 2. Having the FO Risk engine generate sensitivities across the prescribed buckets and tenors for each asset classes and for each risk factor. 3. Sourcing and aggregating FO sensitivities data for all risk classes along specified buckets and tenors. 4. Capturing the value of investment in sourcing full set of risk sensitivities for SA calculation vs. partial set of risk sensitivities. 5. Addressing computational challenges for the mandatory calculation of SA. 6. Maintaining consistency and common risk taxonomy of risk factors across FO and risk infrastructures. 1. Redesigning infrastructure to deal with FRTB computational challenges: a. Mandatory calculation and reporting of SA at desk level. b. Sourcing of a significantly increased data set for SA calculation. 2. Assessing the right trade-off between computational speed and the complexity/ granularity of calculation processes.

12. 12 Banks should streamline their market data sourcing efforts to maintain consistency in the calculation of risk metrics across the firm With the requirement of having "Observable Real Prices," BCBS has put the onus on banks to base each of the risk factors used in internal models on market data and not on internal bank data which may be arbitrary. Copyright © 2016 Accenture All rights reserved. Risk Factor Analysis •“Real Prices” to help identify if risk factors are modelable. •24 observations in a year. •Pricing of illiquid positions. Liquidity Horizon Management •Differentiated liquidity horizons by risk class to compute Expected Shortfall. •Alignment of liquidity horizon buckets with instruments across the trading desks. Banking and Trading Book Data •Consistency of internal ratings between banking and trading books. •Sync probability of default (PD), loss given default (LGD) and Recovery Rates with banking book issuers. Calculation Models •Risk sensitivities calculated in FO and the risk team to use same data sets. •Consistency in risk factors used for pricing and sensitivity calculation. Risk Sensitivity Data •Identification of the term structure on which to map the risk factors for each sensitivity. •Tagging of trading book instruments which are to be included in “Residual Risk Add-on” calculations. Source: Minimum capital requirements for market risk, BCBS, January 2016. Access at: http://www.bis.org/bcbs/publ/d352.pdf, and Accenture analysis.

13. External and internal data sourcing could prove to be demanding given the complexity of the technology environment in banks and the need to have consistent data sets among different teams. • Potential for abuse of the framework by providing uncommitted quotes which could lead to regulatory sanctions on the entire initiative. • Concerns of collusion between institutions which could lead to manipulation of market data in a similar fashion as that of the LIBOR manipulation (London Interbank Offered Rate). • Strong governance and controls, essential to preventing any misuse or manipulation of the utility and which would pose its own set of challenges. • Single vendor may not be able to support all external data requirement leading to increase in complexity. External Market Data • Data used in FO is sometimes not consistent between different teams. Example: Treasury curves used for pricing may be different across teams leading to different valuations. • Lack of standardized data sources for reference data, instrument masters etc.. and which may lead to inconsistencies in data input for models. • Credit risk models in banking book and trading book should be consistent to align default risk charge computations to each other. Consistency of models • The volume of issuers in the trading book is going to be significantly higher than those in the banking book; resulting in cases where internal ratings are not available for issuers in trading book. • These internal ratings for trading book issuers should be consistent with the banking book issuers. • There may be instances where the banking book processes cannot assign an internal rating for an issuer. Banks would have to prepare for these scenarios and define a process to handle such cases. Internal Ratings Management Sourcing external market data and maintaining consistency of internally sourced data is key to the implementation effort Copyright © 2016 Accenture All rights reserved. 13

14. 14 With SA-based calculation being mandatory for banks, there are risk calculator gaps which need to be considered during implementation Maturity Mismatch • The FRTB rules framework defines the risk factors and vertices to calculate the sensitivities. • These risk factors and vertices have maturities which may differ from the existing risk computation systems. • This mismatch in maturities may cause a deviation in the calculation of risk charge under SA. Data Sourcing Gaps • The existing risk infrastructure does not source/obtain all the data required for calculating the capital charge under SA as specified in the FRTB rules. • Data sourcing challenges exist in the decomposition of equity baskets/indices, multi underlying products decomposition, sourcing equity rating data for default risk charge computation and managing internal ratings for both credit and equity issuers. Assumptions • Due to existing data challenges in the risk process models, many assumptions have to be made by the risk management teams which may lead to poor calculations for capital charge under SA. • Banks may need to make assumptions for doing linear extrapolation of risk sensitivity calculations where underlying data is not available to them. Another area is for allocation of exposures to buckets of risk factors which may be based on certain assumptions. Data Taxonomy • Due to difference in FO and risk management systems, there is a challenge in having the different products classified and bucketed as per the FRTB rules. Consistency in calculation and uniform interpretation of the asset classes should be a priority. • Mapping instruments to the relevant asset classes as per FRTB rules becomes a major challenge. Creating an instrument master will be a big driver of change in risk processes for complying with FRTB provisions. • Inconsistent definition of risk factors and valuation methodologies across different teams should be resolved. Copyright © 2016 Accenture All rights reserved.

15. 15 Similar to SA, IMA-based risk calculators also have data challenges which should be accounted for during the implementation phase Rules Interpretation • There are key data issues around several possible interpretations of the rules for Risk Theoretical P&L for satisfying the P&L attribution burden for IMA. • Upfront guidance is needed from supervisors to help avoid poor implementation of the P&L attribution models and risk factor issues which may arise on account of “modelable or not” classification. Data Sourcing • The revised IMA approval process requires data for market risk calculations as well as for developing robust testing mechanism to obtain approval for use of internal models. • There are multiple challenges in data sourcing for IMA models. These start with managing complex risk factor mappings which contain different asset classes, having a clear process for “non-modelable” identification of risk factors and the implementation and mapping of liquidity horizons for different assets classes. Assumptions • FRTB rules detail the process for the P&L attribution for the internal models and require full revaluation methods. Due to high demand on computing resources, banks currently use approximation methods to simplify calculations. • Systemic assumptions to be made for full revaluation of positions would in our view lead to auditory comments from supervisors. Worst case scenario should lead to fall back on SA calculation in absence of hard data to back the internal models. Data Taxonomy • As stated before for SA, having a consistent data taxonomy should serve as a bedrock for all risk computation. • In addition to the challenges listed for SA, IMA to also cater to products which are booked outside of the normal data ecosystem which may present bespoke data challenges. This along with inadequate risk factor selection and inventory to satisfy the audit burden of P&L attribution should help strengthen the case for data taxonomy. Copyright © 2016 Accenture All rights reserved.

17. In our view, for the effective implementation of an FRTB program, banks should have a sound data sourcing, calculation and management strategy. Addressing these key data questions provides the foundation to be flexible and agile in the FRTB compliance efforts. # Key Recommendations Analysis Dimension Benefits 1 Identify a consistent set of sensitivities Methodology • Methodological approach for bucketing sensitivities or risk exposure for individual risk classes. • Have consistent calculation methodologies across the bank. Ideal scenario would be that the sensitivities are calculated only once by a golden source calculator and then utilized by different teams as needed. Taxonomy • Have the same sensitivities definition across FO and risk management teams. This can be done by having a common taxonomy for both teams. • Have standard data taxonomies for attributes across risk classes and sensitivities and use these throughout the organization. • Application of sensitivities to product types in a consistent manner and across the bank. • Consistent treatment of data across. • FO and risk mgmt. teams have same calculations and sensitivity data. 2 Define a centralized architecture for sourcing risk data Data Sourcing • Have a centralized repository for all risk sensitivities that receives data from different golden sources for risk sensitivities and store/organize it by risk class, bucket, tenor and risk factor. o Finalize the list of sensitivities to be sourced in the repository for each bucket across risk classes. o Identify golden sources of sensitivity calculation across risk classes. o Create data sourcing standards for sensitivity data sourcing. o Define feed formats for obtaining data for each sensitivity. Preferred practice would be to establish a unified feed format which can be used for sourcing data from multiple sources. This helps lead to consistent data processing for storing in the repository. o Establish data feed service-level agreements (SLAs) and frequency with source systems for obtaining the data. Preferred practice is to obtain the data feed daily with a pre-defined cutoff time for global operations. • Golden source of risk data. • Ease of data quality management. • Availability of data across the organization as per SLA needed. • Support to approval process and supervisory auditing. Banks can implement an FRTB solution by considering recommendations to address data challenges posed by the new rules (1/4) Copyright © 2016 Accenture All rights reserved. 17

18. # Key Recommendations Analysis Dimension Benefits 3 How to manage IMA risk factors and liquidity horizons? Taxonomy • Individuation of criteria and indicators for distinguishing between modelable and non- modelable risk factors. • Exploiting monitoring of the time series and the quality of the contribution. Data Sourcing • Participating in data pooling initiatives within the industry or subscribing to third-party vendors for obtaining real prices. However, this approach has its own risks as there is a possibility of price manipulation by industry consortium in order to skirt the regulatory requirement and thus may be rejected by the supervisors. • Identify data providers and establish vendor relationships to obtain real pricing information. Data Quality • Develop activities for the control of data for each desk instead of the Legal Entity as a whole. Aggregation • Structuring computations in order to more easily manage the inclusion/exclusion of the desk considered eligible/ineligible for the IM. • Support to individual desk approval for IMA. • Flexibility in switching to SA approach in case of rejection by supervisors. • Reduced capital charges due to IMA. 4 How to plan for P&L attribution? Taxonomy • Define the factors governing the portfolio which is to be considered for P&L attribution and communication protocols to different departments involved such as Finance to help integrate the desks which are eligible for internal model. Governance • Revision of report system for Risk Management on the outcome of the backtesting. • Approval for use of IMA to compute capital charges. • Successful P&L attribution tests. Banks can implement an FRTB solution by considering recommendations to address data challenges posed by the new rules (2/4) Copyright © 2016 Accenture All rights reserved. 18

19. # Key Recommendations Analysis Dimension Benefits 5 How to manage SA risk sensitivities? Governance • Document existing data in FO systems which is used for risk sensitivity calculations. Data Quality • Periodically update the data set to help confirm the existing risk factors and identify any new risk factors impacting the models. • Consistent calculation of risk sensitivities across FO applications. • Identification of sensitivity gaps which can be corrected. • Up to date SA calculators. 6 Where to improve market data process for data quality management? Infrastructure • Integration of the IT processes which warn/alert the users of the data issues in the repository. This would help with the following: o Ability to proactively take action and the timely resolution of the issues with direct communication toward the Risk Technology function. Data Quality • Signaling to both users and impacted functions the data issues and eventual delays in order to help improve the management of the activities. • Data quality management. • Efficient communication for reporting. Banks can implement an FRTB solution by considering recommendations to address data challenges posed by the new rules (3/4) Copyright © 2016 Accenture All rights reserved. 19

20. # Key Recommendations Analysis Dimension Benefits 7 What are the technology synergies with other regulatory initiatives? Infrastructure • Banks would do well to identify synergies with other strategic regulatory initiatives such as BCBS 239 and UMR. To leverage the existing infrastructure for supporting FRTB or if they are in the middle of implementation, so that the technology solutions for different regulatory programs are supporting FRTB needs as well. • UMR regulations proposed by BCBS in their final rules, published in December 2013 and adopted by regulators in US, propose use of “Greeks” which are similar to the sensitivities proposed under the SA framework for FRTB. Additionally the calculation mechanism is similar to the one shared by FRTB. • BCBS 239 regulations propose automated risk reporting and data traceability from source to use of risk data. • Identification of strategic platforms and technologies to invest in. • Avoiding duplicative work. • Cost savings due to sharing of processes and infrastructure across multiple programs. • Delivering compliance across all regulatory regimes. Banks can implement an FRTB solution by considering recommendations to address data challenges posed by the new rules (4/4) Copyright © 2016 Accenture All rights reserved. 20

21. Most banks have elements in place to begin implementing their FRTB solution. They should link these elements together to create a comprehensive approach to market risk management. Proposed FRTB rules seek to remove the weaknesses around market risk evaluation found in “Basel 2.5.” These rules are a comprehensive overhaul of the market risk framework in place today Copyright © 2016 Accenture All rights reserved. 21 • Identify gaps using the current state assessment and target state definition. • Identify areas where remediation work is required for compliance. • Finalize funding requirements and make provisions. • Identify gaps in resources and skills. • Finalize the technology changes to deliver target state. • Revisit target state and make changes if needed. Gap Analysis and Implementation Strategy • Finalize target state technology and business operation capabilities. • Identify strategic platforms and solutions to be leveraged in target state environment. • Define the organizational structure for compliance. • Participate in industry forums. Target State Operating Model • Perform a detailed impact analysis of the FRTB rules on capital requirements and processes involved. • Form assessment workstreams. • Identify categories of impact and analysis dimensions. • Understand current capabilities for People, Process and Technology. Rules Interpretation 1 2 3

23. How Accenture can help? Accenture has project experience in supporting FRTB programs with a select group of large global banks. Using our investment accelerators and tools, banks can ramp up their FRTB implementation.  Mapping of FRTB requirements to different bank functions and teams.  Analyze data source required for compliance.  Develop a common and consistent internal interpretation of what is required for new market risk framework. 1. FRTB Rule Interpretation Analysis  Setup FRTB program governance standards.  Identify implementation workstreams.  Develop solution design.  Analyze funding requirements and budgetary estimates for implementation. 3. Program Initiation  Review and challenge of compliance activities.  Define scope and body of work required for capital charge calculation.  Develop an internal point of view on activities required for compliance.4. Data Gap Analysis and Solution Design  Business analysis capabilities to drive business requirements and the analysis for FRTB implementation.  Large body of work in application development, integration and support.  Project Management Office (PMO) support for managing FRTB program workstreams. 5. Implementation Support  Vendor selection and strategic fit evaluation.  Preferred vendor relationships with the major market risk solution vendors.  Integrated implementation of third-party solutions.6. Vendor Selection and Product Implementation  Define scope and body of work for capital charge calculation under the new methodology.  Inform and define framework for capital calculation and estimate the impact on a bank.  Develop and evolve capabilities for calculating capital estimates.  Develop strategy for engagement with regulator(s) and market participants.  Trading book boundary setup.  Technology environment readiness for transition.  Trading desk eligibility analysis for IMA. 2. FRTB Impact Assessment Copyright © 2016 Accenture All rights reserved. 23

24. Copyright © 2016 Accenture. All rights reserved. 24Confidential and Proprietary Information of Accenture We would use our Accenture Managed Services methodology and the FRTB tools and assets to implement the overall SA Capital Calculation solution. Accenture FRTB Assets and Tools Plan MobilizePrioritize Leadership and Governance Manage Value Measurement Program Control and Administration Stakeholder Management Resource Management Delivery Management Quality Management Value Management Program Delivery Stakeholder Acceptance Plan MobilizePrioritize Leadership and Governance Manage Value Measurement Program Control and Administration Stakeholder Management Resource Management Delivery Management Quality Management Value Management Program Delivery Stakeholder Acceptance Program Management Methods Estimating Models Strategic Delivery Model and Alliance Network Client Sites Strategic Delivery Model Onsite & Regional Global Delivery Methodology, Tools and Architectures Delivery Location Onsite delivery Delivery Centers India, Philippines, China Multidisciplinary Workforce Delivery Centers Wilmington, Chicago, Atlanta, Toronto, London, Spain Prague, Bratislava FRTB Rules Interpretation Tool Integrated Quality Management Are Supported by Is Implemented by Constrains the Process StandardsPolicies PoliciesStandards Training QPI Curriculum, Project Specific & Accenture Core Metrics/Tools Tracking Tools (Risk, Issue, Peer Review, CR/SIR) Process Tailored by Project Procedures Defined by Project Source: "A Software Process Framework for the SEI Capability Maturity Model," PI Liaisons Coaching, Mentoring, Quality Reviews Accenture Delivery Methodology (ADM) Are Supported by Is Implemented by Constrains the Process StandardsPolicies PoliciesStandards Training QPI Curriculum, Project Specific & Accenture Core Metrics/Tools Tracking Tools (Risk, Issue, Peer Review, CR/SIR) Process Tailored by Project Procedures Defined by Project Source: "A Software Process Framework for the SEI Capability Maturity Model," PI Liaisons Coaching, Mentoring, Quality Reviews Accenture Delivery Methodology (ADM) Accenture FRTB Delivery Suite FRTB Assets and Tools FRTB Implementation Framework FRTB Implementation Methods FRTB Implementation Management

25. Fundamental Review of the Trading Book (FRTB) – Data Challenges 25Copyright © 2016 Accenture All rights reserved. Disclaimer This presentation is intended for general informational purposes only and does not take into account the reader’s specific circumstances, and may not reflect the most current developments. Accenture disclaims, to the fullest extent permitted by applicable law, any and all liability for the accuracy and completeness of the information in this presentation and for any acts or omissions made based on such information. Accenture does not provide legal, regulatory, audit, or tax advice. Readers are responsible for obtaining such advice from their own legal counsel or other licensed professionals. About Accenture Accenture is a leading global professional services company, providing a broad range of services and solutions in strategy, consulting, digital, technology and operations. Combining unmatched experience and specialized skills across more than 40 industries and all business functions—underpinned by the world’s largest delivery network—Accenture works at the intersection of business and technology to help clients improve their performance and create sustainable value for their stakeholders. With approximately 384,000 people serving clients in more than 120 countries, Accenture drives innovation to improve the way the world works and lives. Visit us at www.accenture.com Accenture, its logo, and High Performance Delivered are trademarks of Accenture.