Current Challenges in Counterparty Collateral Management Informational Presentation for our Clients...

Current Challenges in Counterparty Collateral ManagementInformational Presentation for our ClientsApril 2008

2PricewaterhouseCoopers Collateral Management • Challenges & Opportunities

Table of Contents

Page

1. Point of view 2

2. Why firms are concerned 4

3. Key issues & opportunities 9

4. Industry environment 10

5. Likely regulatory response 11

6. Suggested approach 12

7. Case studies 13

8. Summary 15

9. Appendix 17

10. PwC contacts 24


Point of view

The recent turmoil in the credit markets has highlighted significant errors and shortfalls in CM operations. These errors have translated into material actual losses and sizable additional exposure which is under-reported to management, hence undermining the risk management benefits of collateral management.

Significant operational challenges persist

Although the role of collateral is straightforward, the volume, diversity and complexity of collateralized transactions have surpassed the scalability and flexibility of processes, people and technology that support the function.

Credit and operational risks are significant

Besides the direct impact of increased counterparty default exposure, underperforming CM functions may also cause or mask significant hidden risks such as portfolio concentration, flawed credit and customer data, and substandard or missing legal documentation – creating potentially dangerous latent exposures.

The benefits of technology advances and the adoption of industry standards have been limited

Bullish statements from Industry groups such as ISDA may over-state the degree to which derivatives-related CM operational issues have been reduced or eliminated by technology, e.g., the adoption of uniform confirmation and call practices. Our experience confirms that some large banks continue to experience high exception rates and difficulty processing collateral calls in a timely manner, and that root-cause remediation of these on-going challenges is difficult and costly.

Many banks’ CM functions have not sufficiently evolved to support complex OTC derivatives

A primary cause of substandard CM performance may lie in the historically low-profile role this cross-departmental function played in most investment banks, prior to the widespread use of complex OTC derivatives. The function may have been designed to support activities such as FX forwards and vanilla repos, where collateral movements were straightforward, products were simple, and there was a relatively small and static base of well-known customers.

Management’s attention was distracted during market expansion

The boom market for OTC derivatives and credit risk transfer products from 2000-2007 saw dramatic revenue growth and constant competitive pressures to deliver innovative products and to increase leverage for hedge fund clients. This may have distracted management’s attention from the growing insufficiency of CM resources and operating models to service the rapidly increasing counterparty exposure.


Point of view

CM operations are challenged to keep pace with product volume and diversity growth

Faced with myriad new and different derivative transactions and a continuous flow of new hedge fund counterparties, CM organizations and IT systems proved unable to change and scale quickly enough to keep up with marketplace demands. This has resulted in backlogs of tasks and documentation, significant data quality issues, and bottom line underperformance and unwanted counterparty default exposure, in the form of insufficiently called and/or ineligible collateral.

Recent market events have led to greater management scrutiny of operational practices

The credit crunch and market turmoil which began in 2007 have cast a harsh light on the requirement to measure, manage and mitigate counterparty exposure, particularly with respect to highly leveraged counterparties and/or less liquid underlying reference securities. Many financial services firms are aggressively seeking to remedy previous oversights and rapidly mitigate excess counterparty exposure – and to get better management intelligence on all credit risks.

Regulatory focus is inevitable

Regulators are aware of the operational weaknesses in collateralized derivative transactions and are likely to scrutinize these functions closely during financial soundness examinations – or on a targeted basis, if a major default event occurs.

Sustainable operation model changes will bring benefits

A focus on end-to-end data management and data quality assurance – not only fixing errors in the current CM data environment, but equally importantly, developing sustainable changes to the operating model to maintain data integrity moving forward – can offer significant benefits as banks seek to overhaul and transform their CM operations.

Scalability and adaptability are key in responding to the complexity of collateralized transactions

Longer term, firms that participate in large volumes of collateralized transactions are seeking to restructure their CM operating models – including people, processes, enabling IT systems and data management practices – to achieve scalability and adaptability appropriate to the elevated complexity of collateralized transactions in today’s capital markets. At the same time, firms are beginning to assess the need for more disciplined new product approval processes in order to make better informed decisions about the total lifecycle costs to support the exotic derivative or credit risk product du jour, instead of assuming ‘all new products are good new products.’

Bottom Line: Often the risk is not apparent until it’s too late to react (e.g., the counterparty has defaulted). Strong risk managers are placing the spotlight on their CM operations to ensure they are adequately protected and to prevent further actual dollars being lost.


How we got here…

Why firms are concerned

Collateral management effectively reduced credit losses during the Asia, Russia and Hedge Fund ‘crisis’ in 1997/98.

The complexity of unraveling the complex web of trades in a crisis today would be unprecedented and may have been one of the prompts for government intervention in the market recently.

1998 2008Market characteristics at that time:• International Swaps and Derivatives

Association (ISDA) estimated $200bn collateral assets

• High thresholds linked to credit worthiness• Calendar driven MTM margin calls –

straightforward calculations• Weekly/monthly margin frequency• Single product margining• Standard ISDA/Global Master Repo

Agreement contract terms• Collateral types: cash, govt bonds

Market characteristics currently:• ISDA estimates >$1 trillion in collateral

assets• Wide range of CP creditworthiness and

thresholds• Market driven margin calls – complex

formulas• Daily/intra-day margin calls• Portfolio margining• Client driven contract terms• Collateral securities include corporate bonds,

equities

Sources: ISDA, PwC research


Overtaxed operations and collateral management processes have led to many millions of dollars in collateral deficiencies

• Explosive growth of derivative volumes, cheap funding and upward biased asset prices drove a period where core risk mitigation received less focus than revenue and market share growth.

• In such a climate, front office focused on product innovation and market share – there was minimal incentive to follow a disciplined new product approval and rollout process which would have better assured that support functions like CM could accommodate structures and meet volume expectations.

• Key data like collateral agreement terms & conditions and trade upfront amounts have been captured incorrectly, late, or not at all.

• Automation and straight through processing (STP) tools for CM and associated trade types are not as mature as those for cash trade processing and most firms choose to build in-house tools which may lack technical flexibility and may become overly dependent upon the key personnel who support and maintain them.


Growth of value of estimated collateral 2000 to 2007

0

200

400

600

800

1000

1200

1400

2000 2001 2002 2003 2004 2005 2006 2007

Year

Bill

ions

of

US

$

Source: ISDA Margin Survey 2007 Source: ISDA Operations Survey 2007

Average reported monthly deal volume 2005 to 2007

02000400060008000

100001200014000160001800020000

2005 2006 2007

Year

Num

ber

of t

rade

s


The landscape has changed significantly in the last ten years


Dimension Then (FX, repos, IRS were dominant collateralized transactions)

Now (Complex OTC derivatives dominant; larger volumes of all collateralized transactions)

Margin Calculations • Vanilla – Single product margining• Mature, standardized affirmation, comparison

and settlement process• Single product margining

• Complex – portfolio margining• Non Standard – Model/market driven• Portfolio margining/cross margining

Data Management • Narrow range of asset types on handful of front office systems

• Relatively simple data management• Limited Dependencies

• Upstream Dependencies – capture of non-standard terms

• Product innovation has led to multiple asset types on wide range of front office systems

• Multiple agreement types• Front office modification of standard T’s & C’s

Portfolio Risk Management

• Hedged products were largely cash/FX based• Collateral was cash and short duration

government debt

• Rapid, unbounded product diversification• Cross border activity• Wide range of security types, quality and

maturities accepted as collateral

Customer Experience • Consistent experience• Low employee turnover• Infrequent customer/broker relationship

changes

• Inconsistent experience – high staff turnover• Staff skill level exceeded in some areas• Inadequate training given complexity

of products• Constant flow of new clients


Increased complexity has led to breakdowns throughout the operations and collateral management life cycle and…


Sources: SWIFT, PwC

Set up legal framework

People: Training, Standardization, Quality Assurance Technology: Efficient document management and indexing

Initiate the transaction

Front office system rationalization and >99% day one capture Eliminate IT bottlenecks which inhibit timely upfront calls

Settle the collateral

Performance metrics and real-time risk management

Manage collateral (margin calls, reconciliation, substitutions, etc.)

Improved STP technology – designed to support the business objectives end-to-end

Close the transaction

Leverage industrytools, messagingprotocols (FpML) and settlement utilities

Trades notTimely captured

Missing AgreementsInefficient processes

Poor upstream data =Inaccurate margin calcs

Upfronts notcalled

Collateral not returned by deadline on closed transactions = poor client experience

Standardize processEstablish or clarifydata ownership


…Technology infrastructure supporting operations, including collateral management, is often inadequate to identify and/or control risks


…

Legal

Trade Whse

Credit

CMS

Trade input systems

(numerous, inconsistent and not fungible)

Other collateral systemsfor Prime Brokerage, Private Clients…

Legal documentation system (CSA, ISDA)

Credit system (CSA, ISDA)

Trade data warehouse

Settlement

Collateral Management System

Trade settlement system

Cash Manager

Cash Manager – Routes cash movements to payments system

Corrections of trades incorrectly routed

Incomplete trade data causinginaccurate portfolio margincalculations

Inaccurately captured terms,conditions, thresholds, currencies,MTAs, collateral types etc

Untimely, inaccuratecollateral requestsImproper netting

Trades not timely inputTrade terms not capturedUpfront amounts never calculated


So what are the key issues and what can clients do

Key issues & opportunities

Key Issue Impact Opportunity

Poorly controlled and/or inconsistently executed customer on-boarding/ legal/credit processes

Significant number of missing, outdated, incomplete, or legally ineffective documents

Conduct a fast track, risk based remediation effort to inventory and resolve discrepancies

Document management and indexing systems lack required flexibility to capture all relevant T’s &C’s; Contract amendments not consistently captured in terms database

Incorrect downstream calculations leading to inaccurate collateral calls

Re-align people, processes and technology resources to properly support the business going forward – a fancy document management solution won’t solve core process issues by itself

Changes negotiated to ISDA boilerplate language/non-standard variances to terms and parameters agreed

Unnecessary process complexity to handle rare and/or marginally useful variances to standardized contracts

Streamline document workflow and reduce number of routinely allowed changes

Incomplete/inconsistent deal data flow to collateral management systems on Trade Date

Upfront calls not timely issued; incorrect portfolio netting calculations

Get control over trade data flow; establish and use daily metrics to monitor process integrity

Upfronts and MTMs not properly valued, leading to under-margined exposure

Excess counterparty default risk Improve upstream data processes to drive accurate margin and collateral calls; identify and remedy shortfalls

Lack of visibility on actual risk of aggregate collateral pool, e.g. by asset class, rating, issuer

Potentially unmanaged market and portfolio exposure if undue concentrations exist

Monitor and manage these types of exposure to reduce risk

Inconsistent customer experiences due to information quality and staff training issues

Poor client service, reputational risk Restructure customer –facing CM roles and functions to improve quality and consistency


Because the OTC Derivative space is mostly unregulated, there is a wide performance gap between the ‘best’ and the ‘worst’ firms.

Industry Environment

Dimension Global Investment Bank A Global Prime Broker B Global Investment Bank C

Consistent and accurate terms & conditions data across multiple functional groups (e.g., Front Office, Legal, Credit, and Middle Office)

Poor – 100% error rate, dozens of agreement templates, data quality not managed

Fewer standard forms , management limits non-standard language

Proactive limits on non-standard language changes Sole source database with clear owner

Accurate and timely independent price verification of collateral

Mainly manual – some stale prices and marks

Some automation Use of automated price feeds

Timely collection of collateral including margin calls and upfronts

Widely variable by product type Medium Consistent and measured

Time required to react to credit events and counterparty deterioration

Slow – multiple days Typically next business day Same day

Monitoring and regulatory reporting capabilities Significant gaps in all relevant data sets = inaccurate reports/metrics

End-of-day batch process, fewer data issues

Near real time margin calculation abilities

Collection of collateral types appropriate to counterparty and market risks being secured

Aware of issue, some manual reviews

Passive monitoring of correlation matching issues

Daily analysis of acceptable collateral types, prompt corrective action

Estimated annual technology spend in CM area >$5M $3-$5M >$15M

Client Satisfaction Rating Poor Medium Good – Excellent

A firm that is effective at collateral management is a firm which has the ability to match its risk objectives with the amount and type of collateral it pledges and receives.


Likely regulatory response

• Financial Regulators are aware of the systemic risks presented by weak operational processes and practices:- Immature state of OTC derivatives processing and collateral management processes

industry-wide cited in US Treasury Dept report to President Bush as a key risk and area for attention (March 2008)

- We have strong indications that all risk management and operational functions are going to receive increased scrutiny in the current environment

- Regulators are beginning to show interest in operational issues and how they impact the market/credit risk of an entity

- Special examinations, including operational processes, are likely to increase at top tier banks in 2Q08 and 3Q08, and we recommend clients be prepared


Suggested approach

3 – 12 months

Remediation & Tactical Fixes

9 – 18 months

Strategic Solution

People • Establish Policy Board, Steering Committee and Working Groups

• Agree on resourcing approach

• Deploy data remediation and project management resources

• Develop current state view of organizational structure, roles and responsibilities

• Examine linkages of policies back to roles and responsibilities

• Define organizational roles and responsibilities

• Draft and agree principles relating to interim changes to Operating Model, e.g. data, sourcing, technology, locations

• Update procedures and training, including upstream procedures e.g. new product approval processes.

• Develop and train staff on new procedures

• Refine enhanced operating model from a process, data, technical, functional and organizational perspective

Process • Confirm project scope• Develop project plan

and define workstreams

• Develop workstream project charters

• Develop data remediation metrics and progress reporting

• Interpret and assess results and determine remediation priorities

• Remediate collateral positions

• Develop current state view of end to end processes

• Assess exception management and escalation procedures, including cross-departmental procedures

• Drilldown on targeted areas causing problems and Identify key control breakpoints

• Perform gap analysis of policies and procedures

• Define manual and automated workarounds and associated control reporting tools

• Assess compliance of policies/procedures with regulatory guidelines and identify changes required

• Implement manual and automated solutions and associated control reporting tools.

• Embed policies in processing environment

• Implement exception reporting metrics:- incorrect or stale valuation

of exposures- common CSA errors- ratings based downgrade

provisions

• Define future business service offering based on business and operational strategies

• Utilizing process analysis work completed in earlier phases, identify gaps between current state and enhanced operating process model

Technology • Confirm support required from technology teams

• Define initial data quality queries

• Refine/tailor diagnostic query tools

• Run targeted diagnostic queries

• Develop current state view of CM system architecture and datawarehousing

• Assess timeliness and accuracy of system feeds between front/middle/back office

• Define tactical and strategic IT upgrades

• Manage “quick win“ and medium term implementation processes with IT

• Enhance use of automation, workflow and document management options

Data • Review existing documentation on data sources and reconciliations

• Confirm data sources and data population

• Perform standing data quality tests:

- Counterparty data

- CSA data

- Credit risk data• Run scenarios/perform

reconciliation on:

- Marks

- Trade level details

- Collateral

• Review data integrity management processes and standards

• Design cross functional CM data integrity standards and controls, focusing on highest risk/return areas.

• Implement selected cross functional CM data integrity standards and controls

• Enhance data warehousing architecture and data integrity management

Scoping & DiagnosisData Clean-up& Remediation

Process Analysis Process Re-Design Implementation Continuous Improvement


Collateral Management Data Remediation and Operational Process Redesign

Case Study

Problem

• The client was a leading global financial institution• Client’s global Collateral Management (CM) group provides essential risk mitigation and client

service functions to support the OTC derivatives and securities repurchase agreements (“repo”) businesses. The CM function was struggling with outdated enabling technology, major data management issues, and lack of mature and documented business processes. Collateral calls were not being properly issued, creating over $500 million in unnecessary risk exposure. Recognizing the urgency to address these challenges, the client created a global initiative involving PwC, internal resources and technical temporary resources in London and New York.

Approach

• Working with the client, PwC developed over 50 multi-variable scenario queries to identify and prioritize collateral deficiencies

• These scenarios were run against the client’s data to identify high impact quick wins as well as to develop a detailed understanding of the failures that were continuing to occur, leading to new defects appearing in the data on a daily basis.

• We also created an efficient, documented repeatable process to conduct a mass data clean-up effort in ISDA Credit Support Annex documentation.

• We worked with the client to develop and prioritize near and long-term process improvements to the day-to-day functioning of the global Collateral Management group.


Collateral Management Data Remediation and Operational Process Redesign

Case Study

Impact and Benefits to the Client

• We helped the client gain a deep understanding of the population of risks and exposures that exist within its Collateral Management unit – a deep root cause analysis of how the client came to have substantial uncollateralized exposure and what needed to be done to fix it.

• We helped the client remediate thousands of key data elements in the Collateral Management contract terms system – enabling immediate, significant improvements to the functioning of the Collateral process and the rapid collection of several hundred million dollars in deficient collateral.

• The client further identified and fixed potential deficiencies (e.g., wrong credit limits, thresholds etc.) which carried aggregate potential exposure in the billions of dollars.

Next Steps

• We are beginning to assist the client in developing and implementing a fundamental re-design, including process re-design and an enhanced technology platform.


In summary

• Certain clients are experiencing significant error rates and exposures generated from broken operational processes and flawed data – leading to as much as hundreds of millions of dollars in margin deficiencies and untold billions in parameter errors

• A root cause of the high levels of operational risk and/or actual operational failures can be traced to fragmented processes and siloed systems that can’t keep pace with product and volume growth

• We recommend that organizations undertake end-to-end operational effectiveness assessments in highly complex product areas

• Processes need to be re-designed to meet the current and future needs of business and large stores of critical data may need to be remediated

• Experience shows millions (USD) or more may be at unnecessary risk and can be identified and collected in an early phase of the overall project

Summary

Appendix

• What does an effective collateral management operation look like• Case Study – Detailed Project Approach


What are some characteristics of an effective collateral management operation

• Ensuring the right data is uploaded into systems in a timely manner. • Maintaining the integrity of the data across various functional groups and their corresponding

systems, e.g., reconciliation, data warehousing, data control/governance systems• Utilizing the data to price, collect, and track the collateral needed to stay within firm regulated

exposure limits, i.e.- Do we have enough collateral to cover our counterparties?- Did we call the correct amount of collateral, based on counterparty ratings, loss given

default, potential credit exposure, etc.?- Are we pledging more collateral than is required?

• Escalating issues where exposure exceeds firms’ acceptable limits due to insufficient collateral

• Adjusting and responding appropriately to changes in market conditions• Ensuring execution aligns with collateral management business strategy, i.e.:

- What types of collateral are we holding?- Is it appropriate for the counterparty, given the industry they are in?- Are exposures or counterparty creditworthiness positively or negatively correlated with

the type of collateral the counterparty is posting?


Suggested approach

3 – 12 months

Remediation & Tactical Fixes

9 – 18 months

Strategic Solution

People • Establish Policy Board, Steering Committee and Working Groups

• Agree on resourcing approach

• Deploy data remediation and project management resources

• Develop current state view of organizational structure, roles and responsibilities

• Examine linkages of policies back to roles and responsibilities

• Define organizational roles and responsibilities

• Draft and agree principles relating to interim changes to Operating Model, e.g. data, sourcing, technology, locations

• Update procedures and training, including upstream procedures e.g. new product approval processes.

• Develop and train staff on new procedures

• Refine optimal operating model from a process, data, technical, functional and organizational perspective

Process • Confirm project scope• Develop project plan

and define workstreams

• Develop workstream project charters

• Develop data remediation metrics and progress reporting

• Interpret and assess results and determine remediation priorities

• Remediate collateral positions

• Develop current state view of end to end processes

• Assess exception management and escalation procedures, including cross-departmental procedures

• Drilldown on targeted areas causing problems and Identify key control breakpoints

• Perform gap analysis of policies vs procedures

• Define manual and automated workarounds and associated control reporting tools

• Assess compliance of policies/procedures with regulatory guidelines and identify changes required

• Implement manual and automated solutions and associated control reporting tools.

• Embed policies in processing environment

• Implement exception reporting metrics:- incorrect or stale valuation

of exposures- common CSA errors- ratings based downgrade

provisions

• Define future business service offering based on business and operational strategies

• Utilizing process analysis work completed in earlier phases, identify gaps between current state and optimal operating process model

Technology • Confirm support required from technology teams

• Define initial data quality queries

• Refine/tailor diagnostic query tools

• Run targeted diagnostic queries

• Develop current state view of CM system architecture and datawarehousing

• Assess timeliness and accuracy of system feeds between front/middle/back office

• Define tactical and strategic IT upgrades

• Manage “quick win“ and medium term implementation processes with IT

• Optimize use of automation, workflow and document management options

Data • Review existing documentation on data sources and reconciliations

• Confirm data sources and data population

• Perform standing data quality tests:

- Counterparty data

- CSA data

- Credit risk data• Run scenarios/perform

reconciliation on:

- Marks

- Trade level details

- Collateral

• Review data integrity management processes and standards

• Design cross functional CM data integrity standards and controls, focusing on highest risk/return areas.

• Implement selected cross functional CM data integrity standards and controls

• Optimize data warehousing architecture and data integrity management

Scoping & DiagnosisData Clean-up& Remediation

Process Analysis Process Re-Design Implementation Optimization


Detailed project timeline

Case Study

Scoping, planning, stakeholder and key metric reporting definition

Confirm data sources and data population

Perform selective process mapping

Identify key control breakpoints

Sco

pin

g

an

d P

lan

nin

g

Dia

gn

osi

s a

nd

A

sse

ssm

en

tD

ata

& C

olla

tera

l P

ositi

on

Re

med

iatio

n

Roo

t C

ause

A

naly

sis

Pro

cess

R

ede

sig

n

Run diagnostic queries

Perform comparison of system data to source Credit Support Annex’s (CSA)

Interpret and assess results and develop remediation priority list

Review results and agree resolution activity with management

Perform updates to correct data errors (Manual or IT upload)

Remediate collateral positions

Report progress and MI on issues identified

Develop tactical and strategic process redesign recommendations

Time


Diagnostics: Data Scenario Analysis

• Working with the client, PwC developed over 50 multi-variable scenario queries to identify and prioritize collateral deficiencies

• We also created an efficient, documented repeatable process to conduct a mass data clean-up effort in ISDA Credit Support Annex documentation

• Scenarios were run against the client’s data to identify high impact quick wins - for example, customers with live trades and:- No upfront call issued- Stale MTM- Credit MTM ≠ Trade MTM- Out-of-range MTA and threshold values- Wrong call frequency

• The query results were also used to prioritize strategic (business re-design) objectives based on actual patterns and frequencies of particular kinds of errors and deficiencies

• A flexible resourcing plan – PwC, client, legal temporary staff – allowed the client to get immediate tangible results while limiting project costs

Case study


PwC’s diagnostic analysis enabled the client to collect several hundred million dollars in deficient collateral

Case study

PwC’s Collateral Diagnostic Tools are designed to quickly and efficiently identify, quantify and help prioritize high impact collateral shortfalls and deficiencies by cause and by client. Outputs can be promptly verified and sent to Margin/Collateral for immediate action during the project

Data in the graphic above are simulated and do not reflect any actual client information

Call Frequency incorrect

1,572instances

$52 mm

Identify

Quantify

Collect


Representative analysis approach and results

Scenario analysis – Update & capture of CSA data Scenario analysis – Trade Data Quality

Analysis of instances of incorrect ‘roll up’ of collateral value

MasterID Counterparty Name Security # Security Type

Sum ofHaircut Market

Value

304707 Counterparty 1 H25D8TSY

BILL/DISCOUNT -1,081,023

747638 Counterparty 2 H26T4TSY BONDS &

NOTES -628,206

865554 Counterparty 3 H25C2TSY

BILL/DISCOUNT -492,090








BILL/DISCOUNT 989,004Total -$2,045,938

Sum of potential 'roll up' issues identified between 01 July and 30 September

150,000,000 100,000,000 50,000,000 0 50,000,000 100,000,000 150,000,000

2-Jul

16-Jul

27-Jul

1-Aug

6-Aug

13-Aug

27-Aug

3-Sep

9-Sep

11-Sep

20-Sep

23-Sep

24-Sep

Distribution of MTAs by Counterparties with no external credit rating:

NR

A

A-

BBB+

BB+ AAA

AA BBB-

AA-

A+

BBB

0

20

40

60

80

100

120

140

160

180

200

Counterparty MTAs

$mm

Decreasing Credit RatingSource: Scenarios K5

0 20 40 60 80 100 120 140

>$ 1bn

>$ 500mm

>$ 100mm

>$ 80mm

>$ 70mm

>$ 60mm

>$ 50mm

>$ 30mm

>$ 20mm

>$ 10mm

>$ 5mm

N umbe r o f C ounte r pa r t i e s

Distribution of Thresholds Amongst Counterparties with no external rating and an internal rating of ‘No Rating’:

Source: Scenarios Z5

Analysis of control risks and policy questions relating to counterparty Minimum Transfer Amounts


Root cause analysis and process re-design

• Assessment of type and frequency of errors• Selective process mapping to identify issues with:

- Data fundamentals – definition, ownership, control- Organization design – roles, responsibilities and controls- Processes – streamlining and improving scalability- Technology – use of automation, workflow and document management options

• Assessment of root cause analysis findings• Strategic recommendations based on global industry practice

- Phased approach including short-term tactical fixes- Addresses organizational, process and technology issues- Develop and implement enhanced future state

Case study


For further information, please contact

John Garvey [email protected]

646-471-2422

Andrew Wilson [email protected]

646-471-7839

Richard Paulson [email protected]

646-471-2519

Karen Joyce [email protected]

646-471-5311

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Although we believe that the information contained in this document has been obtained from reliable sources, PricewaterhouseCoopers is not responsible for any errors or omissions, or for the results obtained from the use of this information. All information in this document is provided "as is", with no guarantee of completeness, accuracy, timeliness or of the results obtained from the use of this information, and without warranty of any kind, express or implied, including, but not limited to warranties of performance, merchantability and fitness for a particular purpose. In no event will PricewaterhouseCoopers, its related partnerships or corporations, or the partners, principals, agents or employees thereof be liable to you or anyone else for any decision made or action taken in reliance on the information in this document or for any consequential, special or similar damages, even if advised of the possibility of such damages.

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Current Challenges in Counterparty Collateral Management Informational Presentation for our Clients...

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