a framework for improving operational efficiency in investment banks
TRANSCRIPT
A Framework for Improving Operational Efficiency in Investment BanksContinuing pressure on operating margins is posing a significant challenge for investment banks. This calls for a holistic approach to improve operational efficiency while reducing the complexity of the business and the technology architecture.
Executive SummarySince the financial crisis of 2008, investment banks’ (IBs) operating margins have been narrowing while their expenses have been rising (see Figure 16, appendix1). The rising cost of regulatory compliance and a volatile global economic environment have added to the woes of investment banking divisions (IBDs). The growth of electronic trading, regulatory restrictions on proprietary trading (as mandated by the Volcker Rule) and the trading of complex high-margin products have squeezed operating margins. Structural issues such as complex operations, weak corporate governance and inadequate controls compound the problem.
Cost-cutting measures such as headcount reduction, offshoring and outsourcing have helped the IBs in the short term but might not be enough over the long term. We believe that sustainable improvement in the cost profile of
these businesses requires a more systematic and holistic approach.
This paper discusses the key cost and efficiency challenges facing IBDs. It proposes a compre-hensive framework for enhancing operational efficiency by simplifying business processes and improving IT architecture.
A Framework for Operational EfficiencyIn the current macroeconomic environment, investment banks face a range of internal and external challenges (see Figure 1, next page) that can negatively impact operating margins, opera-tional risks and operating flexibility.
Figure 2 (next page) defines a solution framework that can help achieve the two operational efficiency themes identified above. The framework is based on the idea that simplified and standard-
cognizant 20-20 insights | may 2016
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cognizant 20-20 insights 2
ized business processes that are aligned to business strategy can support improvements in technology architecture and ultimately drive sustained operational efficiency improvements.
As Figure 2 depicts, the framework consists of the following six interrelated steps.
Challenges, Impact Areas and Key Themes
Figure 1
Increased cost of compliance due to multi-jurisdictional
nature of regulations
Commoditization of existing products and increased
regulatory scrutiny of high revenue streams
Misaligned & non-standard business processes between front, middle and
back offices
Inflexible and complex business/IT architecture
Inadequate control mechanisms and poor data quality
Challenges Impact
Reduced operating margin
Increased operational risk
Reduced flexibility for future changes
Operational EfficiencyThemes
Simplification of businessprocesses
Improvement in IT
architecture
Simplification of Business P
rocesses
Improvem
ent in IT Architecture
STEP 6Establish well-defined metrics to measure
operational efficiency and identify/track risks
and issues that need attention.
STEP 1Based on the business strategy, outline core
business capabilities and sub-capabilities and identify target data
flows.STEP 2
Document the current state business processes and data flows for each
entity and product within the IBD that are
impacted by the business strategy.
STEP 3Based on the capability/business process map, identify redundancies/
variations/issues across regions/entities/products
and devise resolution strategy.
STEP 4Based on the identified
resolution strategy, streamline underlying
IT architecture.
OperationalEfficiency
FrameworkSTEP 5Realign supporting
control model to ensure timely, efficient
monitoring of data flows.
Solution Framework for IBD Processes and Architecture
Figure 2
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STEP
1 Define Core Business Capabilities and Sub-capabilities Based on Business Strategy and Identify Target Data Flows
Core capabilities can be defined by logically grouping similar business activities performed within the IBD. These capabilities can then be divided into sub-capabilities. For example, trade execution and management is a core capability with sub-capabilities of market connectivity, order management, trade capture, etc.
Figure 3 provides an example to illustrate Step 1.
STEP
2 Document Current State Business Processes and Data Flows for Each Entity and Product Impacted by Business Strategy
The current state documentation can be used at the product level to:
• Identify inter-entity variations in functional ownership for each capability. For example, position management done in trade execution and management for entity A but in operations for entity B.
• Identify duplication in the functional ownership of capabilities within an entity. For example, for an entity, trade capture process resides in both trade execution and management and operations.
Understanding Business Strategy for Trade Execution & Management (TEM)
Strategic goal: Address key areas of inefficiency and complexity by standardizing TEM capability (data and processes) for a product across entities and defining a consistent representation of trade model (data attributes that make up a trade) front to back.
A. Identifying Core Capabilities & Sub-capabilities Impacted by TEM Business Strategy
As the business strategy focuses on standardization of trade management model, capabilities and sub-capabilities which generate and consume trade data are considered.
Trade Execution & Management
Market Connectivity
Trade Lifecycle Events
Trade Capture
Risk Management
EOD Capture
Operations
Clearing & Settlement
B. Identifying Data Flows Between Sub-capabilities
A target state mapping of data flows between sub-capabilities is created. For example, trades and positions data should flow from TEM to risk management in the target state once the TEM business strategy is implemented.
Mapping of Data of Sub-capabilities
Trade Execution &
Management
Risk Management
Operations
Trade Capture
EOD Risk Clearing & Settlement
Trade Execution &
Management
Market Connectivity
Trades Market Data
Trade Capture
Trades, Positions
Trades
Trade Lifecycle Events
Trade Lifecycle
Cash
Trades, Positions
Asset Servicing Outcomes
Defining Core Capabilities/Sub-capabilities/Data Flows for Target State
Figure 3
Legend Business Capability Business Sub-capability Data
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IBDs will typically trade multiple products, and each product will be traded across multiple entities. As the intention is to standardize the business flows for a product across entities, the current state mapping process should be documented for each product/entity pair (see Figures 4 and 5).
STEP
3 Identify Redundancies/Variations/Issues Across Regions/Entities/Products and Devise Resolution Strategy
After defining the target state of the different sub-capabilities and associated data flows, the next step is to identify issues in the current state for each product. To standardize business processes across entities and eliminate any redundancies:
• For each product and entity, analyze the current state capability-process map. Focus on those business processes that can be mapped to multiple business capabilities within an entity. Examine these processes thoroughly, as they typically indicate either straight through processing (STP) defi-ciencies between capabilities (e.g., dual keying of trades in trade execution and management, and in operations) or process redundancies in the existing infrastructure.
Mapping Current State Business Process to Capabilities/Sub-capabilities
Figure 4
Figure 5
Product 1 – Entity A Product 1 – Entity B
Capability Sub-capability Business Process
Trade Execution & Management
Trade Capture & Routing
Trade Capture
Trade Booking
Trade Enrichment
Risk Management EOD Risk
P&L Calculation
Position Management
Risk Methodology
OperationsClearing & Settlement
Trade Capture
Trade Enrichment
Capability Sub-capability Business Process
Trade Execution & Management
Trade Capture & Routing
Trade Capture
Trade Booking
Trade Enrichment
Position Management
P&L Calculation
Risk Management EOD Risk Risk Methodology
OperationsClearing & Settlement
Trade Capture
Trade Enrichment
Mapping Current State Data Flows Between Sub-capabilities
Product 1 – Entity A Product 1 – Entity B
Mapping of Data of Sub-capabilities
Trade Execution & Manage-ment
Risk Management
Operations
Trade Capture
EOD Risk Clearing & Settlement
Trade Execution & Management
Market Connectivity
Trades Market Data
Trade Capture
Trades Trades
Trade Lifecycle Events
Trade Lifecycle Cash
Trades
Mapping of Data of Sub- capabilities
Trade Execution & Management
Risk Man-agement
Operations
Trade Capture
EOD Risk Clearing & Settlement
Trade Execution & Management
Market Connectivity
Trades Market Data
Trade Capture
Trades, Positions
Trades
Trade Lifecycle Events
Trade Lifecycle Cash
Trades, Positions
Asset Servicing Outcomes
Legend Business Capability Business Sub-capability Data
Legend Business Capability Business Sub-capability Business Process
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• For each product, compare the capability-process map across entities to pinpoint areas where the same business process is mapped to different capabilities in different entities. Examine such entity variations and rectify them for a more standardized business process architecture.
• For each product, compare the target-state and current-state data flows between capabilities to identify additional or missing data flows. This indicates redundant data or incomplete data flowing between capabilities that require data enrichment.
Investigating Business Processes Mapped to Multiple Capabilities to Identify Redundancies
Figure 6
Product 1 – Entity A
Capability Sub-capability Business Process
Trade Execution &
Management
Trade Capture & Routing
Trade Capture
Trade Booking
Trade Enrichment
Risk Management
EOD Risk
P&L Calculation
Position Management
Risk Methodology
OperationsClearing & Settlement
Trade Capture
Trade Enrichment
Comparing Capability-Process Map Across Entities for Given Product to Investigate Inter-entity Variations
Product 1 – Entity A Product 1 – Entity B
Capability Sub-capability Business Process
Trade Execution &
Management
Trade Capture & Routing
Trade Capture
Trade Booking
Trade Enrichment
Risk Management
EOD Risk
Position Management
P&L Calculation
Risk Methodology
OperationsClearing & Settlement
Trade Capture
Trade Enrichment
Capability Sub-capability Business Process
Trade Execution &
Management
Trade Capture & Routing
Trade Capture
Trade Booking
Trade Enrichment
Position Management
P&L Calculation
Risk Management
EOD Risk Risk Methodology
OperationsClearing & Settlement
Trade Capture
Trade Enrichment
Issues Trade being captured at multiple places Multiple data enrichments by different business functions
Figure 7
Issues Position being calculated by different business functions in different entities
P&L calculation being performed by different business functions in different entities
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• Once all the issues have been collated, they must be analyzed to identify the root cause. Based on the outcome of the root cause analysis, a comprehensive resolution strategy must be defined. The strategy must not only help simplify business processes but also provide inputs for streamlining the underlying IT architecture and control framework.
Comparing Current-State and Target-State Data Flows Between Sub-capabilities to Identify Data Attributes Issues
Product 1 – Current State Product 1 – Target State
Mapping of Data of Sub-capabili-ties
Trade Execu-tion & Manage-ment
Risk Manage-ment
Operations
Trade Capture
EOD Risk Clearing & Settlement
Trade Execu-tion & Manage-ment
Market Connec-tivity
Trades Market Data
Trade Capture
Trades Trades
Trade Lifecycle Events
Trade Lifecycle Cash
Trades
Mapping of Data of Sub-capa-bilities
Trade Execution & Man-agement
Risk Man-agement
Opera-tions
Trade Capture
EOD Risk Clearing & Settle-ment
Trade Ex-ecution & Manage-ment
Market Connec-tivity
Trades Market Data
Trade Capture
Trades, Positions
Trades
Trade Lifecycle Events
Trade Lifecycle Cash
Trades, Positions
Asset Servicing Outcomes
Figure 8
Figure 9
Issues Data flow variation between TEM and risk management across current state and target state
Data flow variation between TEM and operations in current and target state
Investigating Issues and Defining Resolution Strategy Based on Root Cause Analysis
Issues Investigation Resolution
Trade capture happening within multiple functions.
Lack of STP between front and back office; no com-mon definition of trade between them.
Canonical trade data model defined and owned by trade execution & management with a capability to handle all trade life-cycle events thus removing the need of back office to capture trade and generate P&L.
Trade lifecycle events captured in back office due to lack of capability in the front office.
P&L calculation being performed by different business functions in different entities.
Back office and front office have their own P&L view due to capture of certain lifecycle events in the back. This leads to increase in reconciliation effort.
Multiple data enrichments by differ-ent business functions.
Lack of common sourcing of reference data across functions leading to enrichment of data in multiple business functions.
Establish data standards with robust governance.
Position being calculated by differ-ent business functions in different entities.
Granularity of position data required varies across business functions.
Creation of business services (e.g., position management services), which can cater to requirements of various business functions.
Data flow variations between busi-ness capabilities across entities.
As per target mapping of data flows between sub-capabilities, trade management should be sending positions to risk management.
Golden sources and ownership to be defined for key data classes produced or consumed by trade execution & management.
Legend Business Capability Business Sub Capability Data
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STEP
4 Streamline Underlying IT Architecture Based on Resolution Strategy
Business processes are tightly coupled with the underlying IT architecture, and any change in the former necessitates realignment of the latter to ensure maximum operational efficiency. As the resolution strategy identified in Step 3 will impact business processes, it will also affect the supporting IT architecture. The IT organization will need to understand each proposed item of the strategy, identify the key changes required to support the strategy and then decide on an implementation approach.
Following are key steps/activities that the IT organization would need to undertake for some of the items proposed in Figure 9 (previous page).
• Create a canonical trade data model defined and owned by trade execution and management with the ability to handle all trade lifecycle events.
> IT Alignment: Analyze existing trade models within IBD and define a common trade data model that can accommodate all products and their respective lifecycle events. All systems that are either producers or consumers of trade-related data will need to implement the new trade data model. As trade execution and management (TEM) will now be able to capture all trade types and trade-related lifecycle events, any trade capture functionality in back-office systems must be dis-continued.
• Establish data standards with robust governance.
> IT Alignment: A common messaging standard will need to be agreed upon between TEM and all consumers of trade-related data. The messaging protocol can be developed internally or an industry standard protocol such as FIX or FML can be used. The delivery mechanisms (publish/subscribe or message queue) of the trade data messages must also be agreed upon between TEM and downstream consumers.
• Create business services that can cater to the requirements of various business functions.
> IT Alignment: The creation of shared services supporting a business capability across businesses/entities aids in reusability of components within the IT architecture. Figure 10 illustrates trade routing and booking capability as a service that can be used by all businesses and entities within
the IBD.
• Define golden sources and ownership for key data classes produced or consumed by trade execution and management.
> IT Alignment: Enlist the key data classes consumed as part of the trade lifecycle processing and identify the golden source for each of the data classes together with the target distribution mech-anism. For each data class, any enrichments happening in systems other than the golden source must be discontinued. Figure 11 (next page) uses reference data as an example to showcase how the concept of golden sources can be implemented with delivery through local hubs that act as data quality monitoring gateways, ensuring any upstream data is quality checked for complete-ness and accuracy before it is fed to downstream components.
Illustration of a Capability Designed as a Service
Figure 10
Trade Routing & Booking Service
Mes
sag
e B
us
Publish
Trade CaptureApplication
Invoke
Invoke
Trade Capture Application
Validation Enrichment Distribution
Subscribe
Subscribe
Desk 1
Desk 2
Acknowledgment
Acknowledgment
TradeStore 2
TradeStore 1
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STEP
5 Realign Supporting Control Model to Ensure Efficient Monitoring of Data Flows
Defining robust business and IT operational controls is a must to ensure that all data touch-points (front to back) are monitored. Cross-functional controls should be emphasized. Any control breaks such as data SLA breaches and poor quality data must be managed through a well-defined quality assurance process.
The realignment of a control model can be broken down into the following sequential steps:
• Create a framework by key IT and business representatives to document controls with a defined list of attributes. Figure 12 highlights some key control attributes that should be a part of the framework.
• Identify and document key controls as per the control framework. Figure 13 (next page) provides an example for defining controls related to the trade execution and booking process.
• Implement the controls identified in the step above. The design must ensure that each control is performed as per the frequency defined in a service level agreement and all breaks are reported in real time. Any break that requires real-time intervention should be handled through a well-defined exception management process.
Reference Data Sourced from Golden Stores Through Local Hubs
Figure 11
Figure 12
Exception Management
Fin
ance
Dat
a L
ayer
Fro
nt
Off
ice
Dat
a L
ayer
FinanceData Store
Book DataGolden Store
Client DataGolden Store
Product DataGolden Store
Front OfficeData Store
TradeCapture
IntradayRisk Systems
P&L Analysisand Posting Tool
P&L AdjustmentTool
Reference Data Management Layer
DefinitionElaboration of the
rationale behind the control and what the control is trying to
achieve.
RiskHighlight the probable risk in case the control
is not implemented.
Control CategoryDefine whether the control is a business process control or a system process/feed
control.
Control TypeWhat does the control
check (completeness or accuracy of data)?
OwnershipIdentifies the function
that would own the requirements for the
control.
ScopeIdentifies the entities/
businesses/product lines/products for which the control is relevant.
Impacted FunctionsIdentifies those
functions that are dependent on the
control and need to know any control
breaks.
DataThe key data classes
affected by the control.
Key Attributes of Control Framework
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STEP
6 Establish Well-Defined Metrics to Measure Operational Efficiency
A sound performance measurement process will be able to link the key metrics to strategy and therefore the business capabilities defined in Step 1 of the framework. It will enable senior management to:
• Assess the progress towards achieving the key operational efficiency themes by providing insights into the efficiency of the systems/processes and the efficacy of the controls in place.
• Detect risks by identifying inefficiencies and highlighting areas that need attention.
Systematic measurement of operational efficiency starts with the definition of metrics that are based on measurable, specific and actionable parameters. Figure 14 (next page) outlines the essential elements of a metrics-based approach for operational performance assessment.
Control Definition Example (Trade Booking)
Figure 13
Trade Routing & Booking Service
Mes
sag
e B
us
Publish
Trade CaptureApplication
Invoke
Invoke
Trade Capture Application
OrderManagement
Venue Market Connectivity
Validation Enrichment Distribution
Subscribe
Subscribe
Desk 1
Desk 2
Acknowledgment
Acknowledgment
TradeStore 2
TradeStore 1
1 2
Controls
Invoke
Control No.
Definition Risk Control Category
Control Type
Ownership Scope Impacted Functions
Data
Ensure trade data is in sync with exter-nal sources
Internal and external version of the trade out of sync
Business Accuracy Trade businessmanage-ment
All entities/businesses trading cash equities electroni-cally
Trademanage-ment
Trades
Ensure trade store is in sync with order manage-ment store
Integrity issues between pre- and post-trade
System Complete-ness
Trade capture IT
All entities/businesses trading cash equities electroni-cally
Trademanage-ment
Trades
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Performance assessment must be an iterative process that evolves over time. The metrics must be periodically reviewed to test their worth and relevance in a dynamic operating environment. Figure 15 illustrates a set of metrics by using the trade enrichment and validation process as an example.
Metrics-Based Approach to Assess Operational Efficiency
• Metrics should be defined based on some measurable parameters.
• It should provide valuable context for assessing the performance of a specific business process/function.
• Method of metrics calcula-tion (e.g., formula).
• Data required to compute and source the data.
• Appropriate business owner.
• Decide on the format frequency and method of reporting (e.g., dashboards, scorecards, reports, alerts).
• Strategic themes should be identified to ensure that metrics are measuring the progress towards the themes ( e.g., business process simplification).
• Operational goals should be specific and aligned to the strategic themes.
• Desired outcomes should be quantifiable or comparable against any chosen bench-mark.
Define Key Metrics
Develop Metrics Computation Methodology
Establish Metrics Reporting Mechanism
Identify Strategic Performance Themes
Outline Operational Goals and Desired Outcomes
1 2 3 4 5
Figure 14
# Steps to Define Metrics Example
1 Strategic Performance Themes Business process simplification
2 Operational Goals Streamline trade enrichment and validation process
Desired Outcomes Reduction in exceptions handling and manual adjustments by 60%
3 Metrics Definition M1: Volume of manual adjustments due to cancel/corrected trades
M2: % of fully enriched trades per product/asset class wise
M3: Daily trade reconciliation breaks between front office and back office due to incomplete/incorrect reference data (For example: If the coupon rate on a bond is not set up cor-rectly in the front office, incorrect trade cash values will be generated and sent to the back office)
4 Metrics Computation M1: Number cancel/corrected trades (daily) ÷ total number of trades (daily)
M2: Fully enriched trades per product ÷ total trades per product
M3: Number of breaks due to reference data issues ÷ total number of breaks
5 Reporting Daily reports/trendlines to track the improvements over a period of time
Example to Illustrate Metrics-Based Approach
Figure 15
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Conclusion We believe sustainable operational efficiency will become a key differentiator for investment banks in gaining competitive advantage.
The framework proposed above offers benefits of synergy when compared with isolated efforts to reduce operating costs. Some of the key benefits of adopting this approach are:
• It establishes a clear logical business architecture that is in sync with the business strategy and capa-bilities, thus ensuring alignment between business and IT.
• It streamlines the IT architecture through rationalization, use of common services and messaging standards, ensuring reusability and sustained efficiencies.
• It reduces the operational overheads due to manual interventions for resolving discrepancies through a well-defined data sourcing strategy supported by strong business and IT controls.
We believe that the key requirements to ensure the effective implementation of the solution framework are:
• Strong sponsorship from senior IBD management.
• A robust governance structure to ensure the implementation aligns with strategic objectives.
• Involvement of cross-functional teams (business and IT) with knowledge of front-to-back processes, systems and data flows.
• A commitment to spending in the short term to deliver sustainable savings in the long term.
Appendix
Figure 16
FICC revenue Total expenses
Unclassified revenue Equities trading revenueAdvisory and underwriting revenue
Net income
184
148 174 202 151 169 178 181 178 179 185
240198
88
274
231202 197
US$b
200 196
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Aggregate Investment Banking Revenue and Expense
cognizant 20-20 insights 12
Footnote1 “UBS Restructuring Shows Need for Banking’s Simpler Future”, Paul J Davies. http://www.wsj.com/
articles/ubs-restructuring-shows-need-for-bankings-simpler-future-heard-on-the-street-1412006159
References
• “Transforming Investment Banks”, Ernst & Young. http://www.ey.com/Publication/vwLUAssets/ey-transforming-investment-banks/$File/ey-transforming-investment-banks.pdf.
• “Investment Banking: Syndetic Solutions to Discordant Challenges”, Grant Thornton Financial Services Group. http://www.grant-thornton.co.uk/Documents/Investment-Banking-Challenges.pdf.
• “Top 10 Challenges for Investment Banks”, Accenture. http://www.accenture.com/microsite/10-chal-lenges-investment-banks-2015/Documents/pdfs/AccentureTop10Challenges_2011.pdf.
• “UBS Tells Why it Cut Off a Limb”, Francesco Guerrera. http://www.wsj.com/articles/SB10001424127887323894704578114863817976002.
• http://uk.reuters.com/article/2015/10/21/uk-credit-suisse-gp-strategy-idUKKCN0SF0AD20151021.
About Cognizant
Cognizant (NASDAQ: CTSH) is a leading provider of information technology, consulting, and business process services, dedicated to helping the world’s leading companies build stronger businesses. Head-quartered in Teaneck, New Jersey (U.S.), Cognizant combines a passion for client satisfaction, technol-ogy innovation, deep industry and business process expertise, and a global, collaborative workforce that embodies the future of work. With over 100 development and delivery centers worldwide and approxi-mately 233,000 employees as of March 31, 2016, Cognizant is a member of the NASDAQ-100, the S&P 500, the Forbes Global 2000, and the Fortune 500 and is ranked among the top performing and fastest growing companies in the world. Visit us online at www.cognizant.com or follow us on Twitter: Cognizant.
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About the AuthorsChris Beer is the Cognizant Business Consulting Lead for Capital Markets in the UK. He has more than 20 years of experience in the European investment banking arena, with a proven track record of creating sustainable client relationships and successfully delivering complex business advisory and business trans-formation initiatives. Chris holds an M.B.A. (Distinction) from Nottingham University Business School and a B.A. (Honors) from Manchester University. He can be reached at [email protected] | LinkedIn: https://uk.linkedin.com/in/chris-beer-3390534.
Surajeet Mishra is Manager-Consulting, Capital Markets, within Cognizant’s Banking & Financial Services business unit. He has over nine years of professional experience in the information technology industry, serving banking and financial services companies across the U.S., Europe and India. Surajeet is a CFA Level-3 candidate and holds a B.E. in information technology and a post-graduate diploma in management from XIMB. He can be reached at [email protected] | LinkedIn: http://uk.linkedin.com/in/surajeetmishra.
Ruchir Mishra is Senior Consultant, Capital Markets, within Cognizant’s Banking & Financial Services business unit. He has nine years of professional experience, working with clients across investment banking, fund management and OTC clearing. Ruchir is a CFA Level-3 candidate and holds a B.Tech. in electrical and electronics engineering from NIT Warangal and a post-graduate degree in management from IIFT, New Delhi. He can be reached at [email protected] | LinkedIn: http://uk.linkedin.com/in/ruchirmishra.
Arti Dharpure is a Senior Consultant within Cognizant Business Consulting’s Capital Markets Practice. She has worked with various clients globally in business process consulting, outsourcing and IT consulting engagements. Arti is a management graduate and has over 10 years of experience in investment banking and the investment management industry. She can be reached at [email protected] | LinkedIn: https://uk.linkedin.com/in/arti-dharpure-876b5430.
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