FROM THEORY TO ACTION In January 2016, the Basel Committee on Banking Supervision (BCBS) published final rules for the framework for capital requirements. The BCBS proposed the end of 2019 as a compliance deadline for with a significant presence in capital markets.1

The new rules – known as Fundamental FTRB encompasses a revised internal Review of the Trading Book or FRTB – are model approach characterized by a shift designed to address Basel 2.5 issues from Value-at-Risk (VAR) to the Expected such as the under-capitalization of the Shortfall (ES) measure of risk, for a better trading book, capital arbitrage between reflection of “tail risk” and capital adequacy banking and trading books, and internal during periods of significant financial risk transfers. Through the FRTB rules, market stress.3 BCBS is seeking, for example, to establish a more objective boundary between the trading book and the banking book, and to eliminate capital arbitrage between the regulatory banking and trading books.2

2 FUNDAMENTAL REVIEW OF THE TRADING BOOK (FRTB) CHALLENGES TO FRTB IMPLEMENTATION

Accenture believes that adoption of the FRTB • Additional investment in technology rules presents banks with major challenges infrastructure for risk calculation. in areas related to business operations and infrastructure provisioning. According FRTB rules require banks to strengthen to our analysis and estimates we expect: their existing market risk infrastructure and overall technology capabilities, with • Significant increases (as much as additional computational capacity to 40 percent) in market risk capital support calculations as required under new requirements; capital requirements. Banks should also plan for additional complexity in operations and • Higher costs for rules implementation processes due to changed desk structures programs – ranging from $100 million and should undertake the standardization to $250 million for large banks; of data sources to support these changes.

• Large increases in Business as Usual (BAU) costs due to desk level requirements; and

Figure 1. Expected FRTB Timeline

Q2 Q3 2019 Supervisor approvals

Q4 2017 Advanced implementation DEC 2019 of standardized approach Compliance and internal model deadline approach components to be completed

Q4 2016 Q2 Q3 2018 Project plan, gap analysis Production parallel and program funding run of FRTB to begin to be completed Q2 2017 Foundational components of strategic market risk infrastructure under implementation

Note: Industry participants are in discussion with national supervisors and the BCBS around the compliance timeline for FRTB. This may lead to the compliance deadline moving beyond December 2019. Source: Minimum capital requirements for market risk, BCBS, January 2016 and Accenture estimates.

3 FUNDAMENTAL REVIEW OF THE TRADING BOOK (FRTB) The BCBS recommended deadline of Data requirements and risk December 31, 2019 may not seem imminent, measures at desk level but the journey to compliance is not easy. Banks should begin to address their FRTB FRTB rules are explicit in proposing implementation strategy immediately and the reporting structure of market risk plan for implementation issues going forward. to management and regulators would be checking this at the trading desk New rules affect these key areas: level.6 As we see it, banks would also need to obtain the data and run their P&L (profit and loss) attribution test risk calculations at a trading desk level and to adjust their data sourcing and P&L attribution test helps evaluate the calculation strategies accordingly. efficiency of the internal models and their ability to capture all the relevant For banks, major areas of focus include risks impacting the portfolio. This is strengthening existing market risk a new requirement and each trading infrastructure and technology capabilities; desk must independently pass this test. positioning additional computational If a desk experiences breaches four capacity to support FRTB calculations; or more times, then it will be put on and planning for additional complexity standardized approach methodology.4 in operations and processes due to changes in their desk structures (although Risk factor eligibility (modelable we believe that some banks may seek vs non-modelable) to incorporate this into ongoing Volcker Rule implementation activities) and Each of the risk factors which banks model the standardization of data sources. will need to undergo an eligibility check, meaning that the banks will need to obtain As shown in Figure 2, a majority of FRTB real prices for them.5 With this measure, rules have a direct or indirect impact we believe that BCBS aims to strengthen on banks’ data management strategies. the internal models to include only those Solving for data challenges would be risk factors which would have consistent a top priority as banks mobilize their interpretation by the banks. This will also resources in their efforts to comply. eliminate any ad-hoc risk factor inclusion to help reduce the capital impact.

4 FUNDAMENTAL REVIEW OF THE TRADING BOOK (FRTB) Figure 2. FRTB Impact Analysis Framework

1. TRADING BOOK BOUNDARY 2. STANDARDIZED APPROACH 3. INTERNAL MODEL AND RISK POLICY APPROACH

2.1 Sensitivity 2.4 Delta, Vega 3.4 Default 1.1 Trade and 1.4 Covered 3.1 Risk Based Method and Curvature Risk Charge Book Boundaries Instruments Factor Analysis (SBM) Calculation (DRC) – IMA

3.2 Expected 3.5 Non-Modelable: 1.2 Trading 1.5 Risk 2.2 Establish 2.5 Default Risk Shortfall Capital Add-Ons Desk Identiication Management Risk Classes Charge (DRC) - SA Policies Calculation (SES)

1.3 Internal 1.6 Reporting 2.3 Securitization 2.6 Residual 3.3 Trading 3.6 Multi Liquidity Risk Transfers Requirements Risk Add-On Desk Eligibility Horizons

2.7 SA Capital 3.7 Calibration 3.8 IMA Capital Calculation to Stress Period Calculation Methodology Methodology 1, 2, 3. FUNCTIONAL FUNCTIONAL 3. 2, 1, REQUIREMENTS

4.1 Trading 4.3 Instrument 4.4 Residual Risk 4.6 SBM 4.8 IMA 4.10 P&L Book Boundary Redesignation Add-On Approval Calculator Risk Factors Attribution

4.2 Exception 4.5 Internal Risk 4.7 Model 4.9 Backtesting 4.11 Changes for Covered Transfers Controls Validation to IMA Model Instruments 4. SUPERVISORY SUPERVISORY 4. APPROVALS

5.1 Asset 5.3 Instrument 5.3 Risk 5.5 Capital 5.6 Risk Factor 5.8 Full Classiication Master Sensitivities Aggregation Pricing Data Revaluation Data Sourcing

5.2 Security 5.4 Data 5.7 Stress 5.9 P&L Attribution Reference Data Taxonomy Calculations and Backtesting 5. DATA & DATA 5. TECHNOLOGY

High Impact Activities

Source: Accenture Analysis

5 FUNDAMENTAL REVIEW OF THE TRADING BOOK (FRTB) DATA ISSUES FOR BANKS

We see three data issues as fundamental to an effective implementation of the FRTB framework

6 FUNDAMENTAL REVIEW OF THE TRADING BOOK (FRTB) 1 RISK SENSITIVITIES Under the revised rules, a bank would SOURCING need to compute at least 79 different calculation inputs for each sensitivity The rules for standardized approach (SA) and class for risk computation under SA. The internal models approach (IMA) advocate new prescribed risk factors and liquidity both: the use of risk sensitivities and computation may lead to as many as consistency in their calculation which, for 12,000 calculations per trade, compared the first time, should be the same as those to the current 250 to 500 calculations per used for the pricing models or instrument trade under earlier Basel 2.5 regulations. prices in the P&L statement that management receives.7 Unlike previous standardized The SA has introduced the concept of models, the SA under FRTB rules makes use curvature risk to capture nonlinear risk of risk sensitivities to capture both linear which is not captured by the delta of the and nonlinear risk in the trading desk. instruments with optionality. Curvature risk is Banks are also required to calculate risk not a second order approximation, but rather charges using SA, identifying Delta, Vega and a full revaluation needed for every instrument Curvature sensitivities across all risk classes. affected. This means, we believe, that The rules specify the maturity buckets for banks would need to update infrastructure, each risk class and sensitivity combination to data availability, and IT capacity to run the arrive at a final sensitivity value per bucket, revaluation for all products with optionality. using netting rules. This should lead to a The new rules also specify that the comprehensive calculation of risk using SA, sensitivities should be calculated on the adding to the complexity of computation. prices of instruments or on pricing models Figure 3 below shows the number of buckets which are used for P&L reporting or market for each sensitivity and risk class combination risk management within the bank. This calls under a sensitivities-based method for SA. for consistency between the calculations used for computing sensitivities and the valuation models used by the front office for trading purposes.

Figure 3. Number of Buckets for Sensitivities Calculation

RISK CLASSES

GIRR CSR – CSR – CSR – Equity Commodity FX Non-Securitization Securitization Securitization (CTP) (Non-CTP)

Delta Individual 16 16 25 11 11 Individual currency currency

Vega Individual 16 16 25 11 11 Individual currency currency

SENSITIVITY Curvature Individual 16 16 25 11 11 Individual currency currency

LEGEND: CSR: Credit Spread Risk CTP: Correlation Trading Portfolio GIRR: General Interest Rate Risk Source: Minimum capital requirements for market risk. Basel Committee on Banking Supervision, January 2016.

7 FUNDAMENTAL REVIEW OF THE TRADING BOOK (FRTB) 2 MARKET DATA should also manage the liquidity horizon, SOURCING which is differentiated by which risk factor is necessary for the computation of the Banks need to source pricing information expected shortfall. Other areas of concern for risk factors to be eligible for inclusion in risk factor pricing include the new level in IMA calculation. These market prices of segmentation of the different instruments need to be “real” and “observable” based and the assignment of different weights (for upon market transactions.8 If pricing is not example, for creditworthiness of the issuer, available for a risk factor then the bank or for currency) as prescribed in the rules. would need to add a Non-Modelable Risk Factor charge to the capital calculation P&L attribution thereby increasing the . Issues in P&L attribution include integration of The rules specify conditions which need to data and time series to secure the adequacy be fulfilled for risk factors to be considered of the input data for the computation of modelable.9 Due to these restrictions, the measures of risk and P&L, and changes and the limited availability of pricing in the workflow and the definitions of new information, we anticipate that market processes of analysis for each trading desk. data would be a high hurdle for banks. Market data quality issues Market data is also needed for computation A key concern here is the non-availability of of risk sensitivities for a SA-based capital market data for risk factors. Grouping these calculation, meaning that the data used for within the non-modelable risk factor category computation of sensitivities is consistent may increase the capital requirements for with front office use of pricing information, these risk factors in case of error. as required by the regulations. Banks are considering a number of solutions Costs for a pooled market data utility can to deal with these challenges, including run up to $15 million for initial setup, with the pooling of data to overcome the lack additional costs for routine maintenance of market data. This approach, however, and global sourcing of data.10 presents risks of its own, such as the potential for abuse of the framework if We see implementation challenges uncommitted quotes are provided; this could for banks in these main areas to source lead to regulatory sanctions on the entire market data for risk factors: initiative. There are also concerns about collusion between financial institutions, Risk factor pricing which could lead to manipulation of market Banks should look at issues such as risk data. Strong governance and controls factor analysis, which entails obtaining would be needed to prevent any misuse risk factors for inclusion in the internal or manipulation of the market data utility. models to identify if each risk factor is modelable or non-modelable. Banks

8 FUNDAMENTAL REVIEW OF THE TRADING BOOK (FRTB) 3 RISK CALCULATOR Assumptions DATA GAPS Due to existing data challenges in banks’ risk Understanding the incremental data process models, many assumptions have requirements versus the existing data to be made by the risk management teams, calculation models and calculators is which may lead to inaccurate calculations crucial, as FRTB has introduced changes for capital charge under SA. Specifically, to the way risk charge is calculated under banks may need to make assumptions in both SA and IMA. doing linear extrapolation of their calculation of risk sensitivities, where underlying data Some broad data gaps affect risk is not available to them. calculators across risk factors and asset classes. These relate to the mismatch of Data taxonomy maturities of existing risk factors and the Because of differences in front office maturity classifications prescribed by FRTB and risk management systems, there is regulations. Another gap is related to the a challenge in classifying the different mapping of internal ratings to FRTB rules, products, as per the FRTB rules, to especially for US institutions, as regulations maintain consistency in calculation and a prohibit the use of external ratings. uniform interpretation of the asset classes across the bank. Mapping instruments to The data gaps for calculating capital the relevant asset classes can therefore charge using SA touch on the following become a major challenge for the banks. broad themes:

Maturity mismatch The FRTB rules framework defines the risk factors and vertices in a way designed to calculate sensitivities. These risk factors and vertices have maturities which may differ from the existing risk computation systems within banks.

Data sourcing gaps The existing risk infrastructure at banks does not source and/or obtain all the data required for calculation of capital charge under SA, as specified in the FRTB rules. Data sourcing challenges exist in the decomposition of equity baskets and/or indices, in underlying products decomposition, in sourcing equity rating data for default risk charge computation, and in managing internal ratings for both credit and equity issuers.

9 FUNDAMENTAL REVIEW OF THE TRADING BOOK (FRTB) Banks opting for IMA face challenges of their own, including:

Data sourcing Data taxonomy The revised IMA approval process proposed As is the case with SA, a consistent data under FRTB rules puts the burden on taxonomy is essential for all risk computation banks to obtain the data for market risk within the bank. The IMA approach calls calculations, as well as for developing for addressing products booked outside a robust testing mechanism to obtain the normal data ecosystem, which may approval for use of internal models. present bespoke data challenges. Data sourcing for IMA models present challenges such as managing complex Rules interpretation risk factor mappings containing different There are data issues related to the asset classes; having a clear process of interpretation of the rules for Risk non‑modelable risk factors for identification Theoretical P&L for satisfying the P&L and implementation, and mapping liquidity attribution using the IMA approach. This horizons for different asset classes. The means that additional guidance is needed IMA framework also specifies that the risk from the supervisors to avoid delays related factors should be supported by an external, to incorrect implementation of the P&L verifiable price, rather than the internal implementation models in the banks. prices many banks use for risk calculation.

Assumptions FRTB rules detail the process for P&L attribution for the internal models, which requires full revaluation methods rather than the approximation methods banks currently use. To use full revaluation methods, banks would need to use data for full sets of positions; they would need to create systemic assumptions to fill in the missing data. This may not sit well with regulators, who may insist on the SA calculation in the absence of hard data to back the internal models.

10 FUNDAMENTAL REVIEW OF THE TRADING BOOK (FRTB) REMEDIATION EFFORTS TO ADDRESS DATA CHALLENGES

In our view, for an effective implementation of Banks should be well served if they form an FRTB program, banks should have a sound the data strategy of the organization data sourcing, calculation and management around FRTB rules by considering the strategy. Addressing the data challenges key recommendations, issues and can provide the foundation to be flexible analysis dimensions that follow. and agile in their FRTB compliance efforts.

ANALYSIS DIMENSION BENEFITS

Methodology Taxonomy Consistent Take a systematic approach Maintain the same sensitivities treatment of data to bucketing sensitivities definition across the front office across the bank. or risk exposure for individual and risk management teams Front office and risk classes. by having a common taxonomy risk management for both. Make sure calculation teams have the methodologies are consistent Establish standard data same calculations 1. IDENTIFY A and sensitivity data. CONSISTENT SET across different areas of the taxonomies for attributes across OF SENSITIVITIES bank. The ideal scenario risk classes and sensitivities and would be that the sensitivities use throughout the organization. are calculated only once by a golden source calculator and then utilized by different teams of the bank as needed.

Data Sourcing • Define feed formats for Golden source Set up a central repository obtaining data for each of risk data across for all risk sensitivities within sensitivity. A favored practice the bank. is to establish a unified feed the bank. This repository Ease of data quality format which can be used for would receive data from management. different golden sources for sourcing data from multiple risk sensitivities and it should sources. This should lead to Availability of 2. DEFINE A be stored and organized by consistent data processing for data across the CENTRALIZED risk class, bucket, tenor and storing in the repository. organization as ARCHITECTURE risk factor respectively. per SLA needed. FOR SOURCING • Establish data feed service RISK DATA • Finalize the list of sensitivities to level agreements (SLAs) Support approval be sourced in the repository for and frequency with source process and each bucket across risk classes. systems for obtaining the supervisory data. Favored practice is to auditing. • Identify golden sources obtain the data feed daily of sensitivities calculation with a pre‑defined cutoff across risk classes. time for global operations. • Create data sourcing standards Data Quality for sensitivity data sourcing. Create data quality standards for managing high quality risk sensitivities data for internal and external audit approvals.

11 FUNDAMENTAL REVIEW OF THE TRADING BOOK (FRTB) ANALYSIS DIMENSION BENEFITS

Taxonomy by an industry consortium to Support to Individuate criteria and skirt the regulatory requirement individual desk indicators for distinguishing and this may be rejected by approval for IMA. the supervisors. between modelable and Flexibility in non‑modelable risk factors. Identify data providers and switching to SA Exploit monitoring of the establish vendor relationships approach in case time series and the quality to obtain real pricing information. of rejection by 3. MANAGE IMA supervisors. RISK FACTORS of the contribution. Data Quality AND LIQUIDITY Data Sourcing Develop activities for the control Reduced capital HORIZONS charges due Participate in data pooling of data for each desk instead to IMA. initiatives within the industry of the legal entity as a whole. or subscribe to third-party Aggregation vendors for obtaining real prices. Structure computations to easily However, note that this approach manage the inclusion/exclusion has its own risk as there is a of the desk considered eligible/ possibility of price manipulation ineligible for the internal model.

Taxonomy Governance Approval for use Define the factors governing of IMA to compute Revise the report system for capital charges. the portfolio which is to be Risk Management based on considered for P&L attribution the outcome of the backtesting. Successful P&L and communication protocols attribution tests. to different departments involved, such as Finance, 4. PLAN FOR P&L for integrating the desks which ATTRIBUTION are eligible for the internal model.

Governance Data Quality Consistent Document the existing data Periodically update the dataset calculation of risk which is useful for sensitivity to confirm the existing risk sensitivities across management from the front factors and identify any new risk the front office office systems. factors impacting the models. applications. Identification of sensitivity gaps 5. MANAGE SA RISK which can be SENSITIVITIES corrected. Up to date SA calculators.

Infrastructure Data Quality Data quality Integrate the IT processes Signal to both users and affected management. which warn/alert users of data functions the data issues and Efficient issues in the repository. This eventual delays to improve communication should help with the ability to management of the activities. for reporting. proactively take action and resolve issues on a timely basis, 6. IMPROVE with direct communication with MARKET DATA the Risk Technology function. PROCESS FOR DATA QUALITY MANAGEMENT

12 FUNDAMENTAL REVIEW OF THE TRADING BOOK (FRTB) ANALYSIS DIMENSION BENEFITS

Infrastructure • This then becomes a question Identification Identify synergies with other of scalability and flexibility of strategic tools strategic regulatory initiatives of the bank’s UMR calculator. within the bank. A bank would be well served such as BCBS 239 and the Avoiding if it can leverage the UMR Uncleared Margin Regulation duplicative work. (UMR). Leverage the existing work and extend it to the infrastructure for supporting SA calculator for FRTB. Cost savings due to sharing 7. SEEK FRTB, or, if they are in the BCBS 239 regulations propose TECHNOLOGY of processes middle of implementation, the use of automated risk SYNERGIES and infrastructure make sure that the technology reporting and data traceability WITH OTHER across multiple REGULATORY solutions for different regulatory from source, as well as the programs. INITIATIVES programs are supporting the use of risk data within the FRTB requirements as well. bank. Within a bank, an FRTB Permits compliance UMR regulations proposed program can leverage the across all regulatory by BCBS in their final rules standards established as regimes. published in December 2013 part of BCBS 239 as follows: and adopted by regulators • Sourcing data directly from in the US propose the use of golden sources without “Greeks” which are similar any data transformation to the sensitivities proposed and manipulation. under the SA framework for FRTB. Additionally the • Maintaining strong data lineage calculation mechanism is documentation for traceability similar to the one shared by and supervisory approvals. FRTB. The comparison of • Using a BCBS 239 frameworks is given below: infrastructure for risk reporting • As can be seen below UMR to generate market risk rules have a strong parallel reporting under FRTB. with FRTB regulations with the only difference being that UMR applies to uncleared derivatives while FRTB regulations apply to the entire market portfolio of the bank.

FRTB Rules UMR Rules (ISDA, 2016)

Calculate Delta, Calculate portfolio “Greeks” for each of the risk factors, Vega and Curvature which can be done using internal models, vendor supplied for each risk class models or counterparty provided “Greeks.”

IMx=DeltaMarginx+VegaMarginx+CurvatureMarginx

The total market risk Aggregate the margins for each asset class calculated charge is an aggregate using the above formula. of the risk charge SIMM=SIMMRatesFX+SIMMCredit+SIMMEquity+SIMMCommodity for Delta, Vega and Curvature across risk classes

Source: Accenture analysis of the International Swaps and Derivatives Association (ISDA) Standard Initial Margin Model (SIMM) version 3.15

13 FUNDAMENTAL REVIEW OF THE TRADING BOOK (FRTB) CONCLUSION STEPS TO TRANSFORMATION OF MARKET RISK PROCESSES

We believe that most banks have elements in place to begin an effective transformation of their market risk processes in response to FRTB. We strongly encourage them to link these elements together to create a comprehensive approach to market risk management.

These steps include: 3. Documenting gap analysis and create an implementation strategy 1. Defining internal understanding This entails identifying gaps (using the current of FRTB rules and requirements state assessment and target state definition) This includes performing a detailed as well as areas where remediation work is impact analysis of the FRTB rules on required for compliance. In this step, the bank capital requirements and the processes also finalizes funding requirements and makes involved. The bank should form assessment provisions, identifies gaps in resources and workstreams, identify categories and skills, and details the technology changes dimensions of impact, and understand required to reach the target state. the current capabilities for people, process and technology within the bank. 4. Creating an implementation roadmap Once the first three steps have been taken, 2. Developing a target state the bank can create a detailed roadmap operating model and direct different workstreams aimed The bank should finalize the target state at reaching the desired target state. technology and business operation capabilities, and identify strategic platforms As we have seen, challenges related to and solutions to be leveraged in a target FRTB implementation are significant. While state environment. In addition, the bank banks still have enough time to meet the should also define the organizational 2019 deadline, they have no time to lose in structure for compliance and participate organizing and planning what amounts to a in industry forums to identify the current comprehensive reordering of their market level of industry practice. risk processes. The needed talent is in short supply and banks that move quickly to develop and execute a plan would have an advantage over competitors who are slower to respond to this major regulatory initiative.

14 FUNDAMENTAL REVIEW OF THE TRADING BOOK (FRTB) REFERENCES ABOUT THE AUTHORS 1. “Minimum capital requirements for Amit Gupta market risk,” Basel Committee on Banking Supervision, January 2016. Access at: Amit is a Managing Director, Accenture Finance http://www.bis.org/bcbs/publ/d352.htm & Risk. Based in New York, Amit has over 15 years of risk consulting and capital markets industry 2. Ibid experience delivering strategic solutions for 3. Ibid a broad range of client situations. He also 4. “Minimum capital requirements for market has extensive experience in assessing market risk,” Basel Committee on Banking Supervision, risk and credit risk capabilities, and helping January 2016. Access at: http://www.bis.org/ clients enhance their risk governance, risk bcbs/publ/d352.htm processes, analytics capabilities and implement 5. Ibid risk systems. Amit works closely with client 6. Ibid executives to increase their organizational focus on proactive risk measures and to better 7. “Minimum capital requirements for leverage their enterprise risk management market risk,” Basel Committee on Banking capabilities to support their growth agenda. Supervision, January 2016. Access at: http://www.bis.org/bcbs/publ/d352.htm Rahim Inoussa 8. Real prices – Under risk factor analysis, each of the risk factors need to have 24 observable Rahim is a Senior Manager, Accenture Finance price points over a year. These observable price & Risk. Based in New York, Rahim leads the points have to be “Real” which is defined as: North America Market Risk Offering group, It is a price at which the institution has focusing on the Fundamental Review of the conducted a transaction; Trading Book (FRTB). He has over 15 years of broad‑based consulting and industry experience It is a verifiable price for an actual transaction in the capital markets sector delivering strategic between other arms-length parties; or initiatives at global financial institutions. The price is obtained from a committed quote; Specialized in market risk, credit risk and If the price is obtained from a third-party regulatory compliance, Rahim works with vendor (with some conditions to accepting clients on their journey to high performance. the vendor data). 9. “Minimum capital requirements for Gaurav Kapoor market risk,” Basel Committee on Banking Gaurav is a Manager, Accenture Finance & Supervision, January 2016. Access at: Risk. Based in New York, Gaurav has over http://www.bis.org/bcbs/publ/d352.htm 6 years of consulting experience in the Capital 10. “Manipulation threat to FRTB data pooling,” Markets sector delivering large scale business Risk.net, May 24, 2016. Access at: http:// transformation and Regulatory front-to-back www.risk.net/risk-magazine/feature/2458359/ change programs for large investment banks. manipulation-threat-to--data-pooling He has broad experience in business analysis, data management, specification, design and implementation of Capital Markets functions and is currently focused on the Fundamental Review of the Trading Book (FRTB).

15 FUNDAMENTAL REVIEW OF THE TRADING BOOK (FRTB) STAY CONNECTED ABOUT ACCENTURE Accenture Finance and Risk Accenture is a leading global professional www.accenture.com/financeandrisk services company, providing a broad range of services and solutions in strategy, consulting, Finance and Risk Blog digital, technology and operations. Combining financeandriskblog.accenture.com/ unmatched experience and specialized skills Connect With Us across more than 40 industries and all business www.linkedin.com/showcase/16183502/ functions—underpinned by the world’s largest Follow Us @AccentureFSRisk delivery network—Accenture works at the www.twitter.com/AccentureFSRisk intersection of business and technology to help clients improve their performance and create sustainable value for their stakeholders. With more than 401,000 people serving clients in more than 120 countries, Accenture drives innovation to improve the way the world works and lives. Its home page is www.accenture.com.

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