Delphix_Analyst_Report_Aite_Sept_2014

© 2014 Aite Group. All rights reserved. Reproduction of this white paper by any means is strictly prohibited.
Stress-Test Data Virtualization: Better
Insights, Lower Costs
Prepared for:

Stress-Test Data Virtualization: Better Insights, Lower Costs September 2014
© 2014 Aite Group. All rights reserved. Reproduction of this white paper by any means is strictly prohibited. 2
TABLE OF CONTENTS
EXECUTIVE SUMMARY.................................................................................................................................... 4
INTRODUCTION .............................................................................................................................................. 5
METHODOLOGY........................................................................................................................................ 5
THE REGULATORY DATA BEAST...................................................................................................................... 6
THE SNAPSHOT-IN-TIME CHALLENGE ....................................................................................................... 6
DATA FIRE DRILLS...................................................................................................................................... 8
BANKS' STATE OF BATTLE READINESS....................................................................................................... 8
MEDIOCRITY IS NOT AN OPTION............................................................................................................. 10
STRESS-TEST DATA VIRTUALIZATION...................................................................................................... 11
DATA VIRTUALIZATION...................................................................................................................... 12
CONTINUOUS POINT-IN-TIME CREATION ......................................................................................... 12
SELF-SERVICE MANAGEMENT ........................................................................................................... 13
BENEFITS OF STRESS-TEST DATA MANAGEMENT SYSTEMS......................................................................... 14
IMPROVED PRODUCTIVITY ..................................................................................................................... 14
FEWER DATA CATASTROPHES........................................................................................................... 15
BETTER TRUST IN DATA..................................................................................................................... 15
QUANTIFYING THE PRODUCTIVITY BENEFIT ..................................................................................... 15
MORE RAPID AS-OF DATE DATA RECONSTRUCTION......................................................................... 16
AVOIDING PROVISIONING DELAYS.................................................................................................... 17
SHORTER STRESS-TEST PROJECT CYCLE TIMES.................................................................................. 17
REDUCED STORAGE COSTS ..................................................................................................................... 17
CONCLUSION ................................................................................................................................................ 20
ABOUT AITE GROUP...................................................................................................................................... 21
AUTHOR INFORMATION ......................................................................................................................... 21
CONTACT................................................................................................................................................. 21
LIST OF FIGURES
FIGURE 1: A SAMPLE OF DATA SETS CALLED UPON DURING A STRESS TEST ................................................. 6
FIGURE 2: BANKS' AMBIVALENCE ABOUT SUCCESS WITH DATA MANAGEMENT.......................................... 8
FIGURE 3: BANKS' AMBITIONS FOR THEIR STRESS TESTS............................................................................... 9
FIGURE 4: BANKS SUPPORT STRESS TESTS WITH LIMITED AUTOMATION ................................................... 10
FIGURE 5: ADVERSE REGULATORY FINDINGS A REAL RISK FOR BANKS........................................................ 11
FIGURE 6: ASSESSING THE BENEFITS OF STRESS-TEST DATA MANAGEMENT SYSTEMS .............................. 14
LIST OF TABLES
TABLE A: QUANTIFYING THE IMPACT OF DATA VIRTUALIZATION ON PRODUCTIVITY................................. 15
TABLE B: STRESS TEST-RELATED STORAGE COSTS........................................................................................ 18

TABLE C: STRESS TEST-RELATED STORAGE COSTS WITH VIRTUALIZATION TECHNIQUES ............................ 18

EXECUTIVE SUMMARY
Stress-Test Data Virtualization: Better Insights, Lower Costs, commissioned by Delphix and
produced by Aite Group, examines the data management challenges faced by banks that
complete stress tests and identifies the benefits banks can achieve when these hurdles are
overcome using data virtualization.
Key takeaways from the study include the following:
 The capital adequacy tests, often referred to as stress tests, that banks are now
required to complete as a result of the global financial crisis of 2008 are significantly
IT-intensive, requiring data from up to 100 systems and data sets across a bank's
various lines of business, risk management functions, and subsidiaries.
 Banks have lofty ambitions for their stress-test initiatives. A survey completed by
Aite Group found the majority of stress testing banks seek benefits from these
activities that go beyond mere compliance and include insights about the bank's risk
profile.
 Despite banks' ambitions for their stress-test capabilities, these initiatives tend to be
poorly supported by automation. Aite Group's survey of stress testing banks
indicates that the vast majority of banks have stress-test capabilities that are fully or
primarily manual.
 Poor automation extends to data management and data warehousing, a critical
stress test-related capability with which just 45% of banks are satisfied and in which
only 50% of banks have the goal of being stellar.
 When Aite Group compared data virtualization capabilities to banks' stress test-
related pain points, Aite Group identified direct benefits—those benefits that are
most easily achieved and readily quantified—that include reduced hardware costs
and improved productivity as a result of better trust in data and avoiding data-
related catastrophes.
 By using data compression and various storage optimization capabilities, data
virtualization systems can significantly reduce the amount of storage required to
complete a stress test.
 The indirect benefits of data virtualization for stress-test teams that Aite Group
identified include faster point-in-time data set construction, the avoidance of
hardware provisioning delays, and shorter stress-test project cycle times.

INTRODUCTION
Among the lasting impacts of the global financial crisis of 2008 are costly and demanding new
regulations that have profoundly changed the relationships between banks, their regulators, and
their governments. Chief among a government's goals is to avoid being the financier of last
resort to its banking sectors the next time a speculative bubble pops or an economic growth
cycle runs out of steam. With this goal as a mandate, regulators now continually evaluate banks
as potential borrowers using capital adequacy stress testing, a process in which banks estimate
their capital levels under a variety of economic scenarios, some of which are bank-specific, and
many of which are quite severe in their assumptions.
Suddenly in the unfamiliar and uncomfortable position of credit applicant to their regulators,
banks struggle with not just the complexity of stress tests but also the challenge of providing
their compliance departments with timely delivery of the right data for these vast and complex
analyses. Stress tests involve up to five macroeconomic scenarios, each supported—ideally—by
separate test, development, and run environments, which result in large data sets that must be
stored. Stress testing data management requirements force banks to either make significant
investments in hardware or compromise on such requirements, which can reduce the pace and
quality of a bank's stress tests.
It is in this context that Aite Group has added to its stress-test knowledge base an examination of
the potential benefits of data virtualization, a technology used by software development teams
but readily applied to stress testing. This report can be used by mid-level, senior, and board-level
managers at banks to identify and quantify the potential benefits of supporting stress testing
with data virtualization.
METHODOLOGY
This white paper is based on Aite Group's growing body of research on stress testing, which
covers what is required of banks that stress test, the challenges they face when performing
stress tests, and the vendors providing capabilities that automate stress tests or portions of
these complex projects. Aite Group's knowledge is the result of a comprehensive request for
information (RFI) completed by 10 global providers of core stress-test automation tools during
Q2 2013, a survey of 18 compliance professionals involved in their banks' stress testing activities,
and the firm's annual global survey of senior IT executives at banks. This research is further
bolstered by the knowledge of the author, whose career spans 13 years in commercial banking
and eight years in software analysis, most of which were spent considering analytics-related
deployments and quantifying the benefits of technology investments.

THE REGULATORY DATA BEAST
As banks become accustomed to the post-crisis regulatory world in which they must continually
prove the adequacy of their capital and risk management to regulators, one of the biggest
challenges they face is data management. When performing a stress test, banks aggregate,
process, and analyze data from up to 100 applications and data sets from across banks' various
lines of business, risk management departments, and subsidiaries. Figure 1 provides a sample of
the types of data sets called upon during a stress test, which typically occur in numerous
instances across a bank's subsidiaries and lines of business.
Figure 1: A Sample of Data Sets Called Upon During a Stress Test
Source: Aite Group
Once a stress-test cycle is underway, a proliferation of various versions of stress-test scenarios
and underlying data sets results in significant data storage and data management requirements
for stress-test teams and compliance departments.
THE SNAPSHOT-IN-TIME CHALLENGE
Compounding banks' stress test-related storage challenges is the difficulty in performing
snapshot-in-time analyses. Knowing that economic crises and the unfortunate conclusions of
speculative bubbles are rarely synchronized with accounting cycles, regulators now demand that
banks be able to perform ad hoc stress tests as of a given date. Although much attention and
capital at financial institutions has been dedicated to achieving the fabled 360-degree view of a
customer's or individual's risk, the snapshot-in-time view of a bank's entire risk profile can be
equally difficult and costly.
• Corebanking systems
• Loan origination systems
• Underwriting supportsystems
• Risk analysis and underwriting documents
• Ratings bureaus
• Business intelligence capabilities
• Treasury department systems of record
• Manualsurveys of individual assets and
obligorscompleted by underwriting and
risk personnel
• Loan balances
• Maturitydates
• SIC codes
• Geographicdata
• Repayment histories
• Internal riskratings
• Credit sensitivities of individual assets
and obligors
• Collateral data
Data points obtainedData sources accessed

With regard to stress testing, a snapshot-in-time view is like a pop quiz on enterprise-wide risk,
which is difficult enough. The fact that such a quiz can occur on the scale of a Bank of America or
a large regional bank makes it vastly difficult and creates significant IT challenges. Some of the
challenges in performing a snapshot-in-time analysis include:
 Multiple environments: As is common with processes that create content for
influential outsiders such as regulators, stress tests often generate a large number of
iterative drafts, test runs, and backup copies. Further causing banks to create
multiple versions of their stress tests are the various economic scenarios that must
be run that—for the largest banks—consist of a regulatory base case, regulatory
down case, regulatory worst case, global shock case, bank-specific base case, and
bank-specific worst case. Aite Group finds that, due to the importance of stress
tests, the environments that banks seek to create in support of stress tests can
mirror those for application development and include separate environments for
developing, testing, and running stress tests for each of the scenarios.
 Volatility: Banks spend weeks and sometimes months completing a single stress test
with its multiple scenarios. While in flight, the vast number of data points
comprising a stress test are all extremely variable. For example, regulatory
requirements change, their interpretations can be modified, risk ratings are
adjusted, loan balances fluctuate, and risk ratings change. Such fluidity of data
means that ensuring that all data records are accurately and uniformly updated
across all scenarios and environments is a task not readily accomplished in the
absence of automation. Data volatility can also impact performance; the more
variable data a stress test must accommodate, the more slowly it will perform
scenario analyses and publish reports.
 Volume: Stress tests, and the data sets they comprise, are extremely large. These
examinations, especially if they are performed with loan-level granularity, require
information on a large number of portfolios, loans, and loan-specific data points
such as interest rates, risk ratings, and economic sensitivities. Enterprise-wide in
nature, a bank's stress-test capabilities must encompass all commercial loans,
derivatives entered into on behalf of clients, retail loans, car loans, mortgages, lines
of credit, and every position entered into by treasury desks. Adding to the
complexity and volume are the required projection scenarios, which comprise 31
domestic and international economic metrics over a nine-quarter period.
 Storage: Stress tests, their results, and their underlying data sets, due to their
vastness, require large amounts of storage. Although banks often minimize the
hardware-related costs of applications such as customer relationship management
(CRM) by using existing on-premise server space, or turning to software as a service
(SaaS) or cloud-based storage, these cost-avoiding tactics are not available for stress
tests. Comprising an analysis of a bank's capital under a variety of projections, some
of which might be unfavorable, a stress test contains data and analyses that
compliance departments must store with significant levels of security and
governance. Accustomed to achieving such levels of security with on-premise
deployments, banks tend to make significant hardware-related investments for their

stress tests, including the multiple scenarios, underlying data sets, and snapshot-in
time versions.
DATA FIRE DRILLS
As a result of the diversity of data and sources called upon during a stress test, it is common for
bank compliance departments to experience a number of data-related fire drills when
performing a stress test. For example, if rules for combining credit-ratings databases from
different subsidiaries are not crafted properly, scores can default to zero or "not applicable."
Many banks remedy such problems by having administrative or underwriting staff rebuild such
data sets from scratch, a lengthy, costly, and error-prone process. The more manual and
spreadsheet-based a bank's stress-test capabilities are, the more likely such data disruptions and
productivity losses will be.
BANKS' STATE OF BATTLE READINESS
Aite Group finds that with regard to data in general and stress testing in particular, banks may
not be fully prepared to battle the regulatory data beast. In its most recent global survey of
senior IT executives at large banks across the world, Aite Group found banks to be relatively
dissatisfied with their capabilities related to data management and data warehousing (Figure 2).
Figure 2: Banks' Ambivalence About Success With Data Management
Source: Aite Group's global survey of banks with more than US$10 billion in assets, Q1 2014
Aite Group observes two concerns in Figure 2 . First, the dissatisfaction rates that banks have for
data management and business intelligence/performance management were among the highest
of 53 technologies examined by Aite Group. Second, banks appear to lack ambition in these
spending areas; only half or less have the goal of being stellar at both critical capabilities. If
banks have not only limited capabilities in these areas that are so key to stress testing but also
limited goals and spending, it's unlikely they'll be able to overcome the data management and
storage challenges that come with stress testing.
When Aite Group asked about banks' stress testing capabilities in particular, it found banks to be
of two minds: although banks are relatively ambitious about their stress testing capabilities,
Yes No
Do not
have
Be good
enough
Be stellar Down Flat Up
Data warehousing/data management 45% 49% 5% 50% 50% 7% 23% 70%
Business intelligence/performance management 48% 47% 5% 51% 49% 7% 36% 57%
Big-data analysis tools 30% 52% 18% 52% 48% 8% 16% 77%
Average 41% 49% 10% 51% 49% 7% 25% 68%
(% of total respondents)
(% of respondents that
have the technology)
(% of respondents that have the
technology)
Q. Please help us understand your institution's IT initiatives in data
management and analysis. (Average n=77)
Q. Is your firm satisfied with this
capability?
Q. Firm's goal with
capability?
Q. 24-month IT spending forecast?

these systems—despite their importance to one of the most demanding regulatory challenges of
the day—benefit from limited technological support. When surveyed about their goals for their
stress tests, the majority of respondents indicate a desire to gain insights from these complex
analytical and reporting projects. In Aite Group's recent survey of stress testing banks, only a
minority of banks seek merely to comply with stress-test regulation; the majority indicate that
they either stress test to achieve both compliance and insights or that insights were so
important when performing stress tests that compliance is only a byproduct (Figure 3).
Unfortunately, though banks appear to be relatively ambitious about their stress-test
capabilities, Aite Group finds that these initiatives tend to be poorly supported with automation
(Figure 4).
Figure 3: Banks' Ambitions for Their Stress Tests
Source: Aite Group's survey of 18 compliance professionals, Q2 2013
We want to
comply and
achieve insights,
12
We just want to
comply, 3
We stress test to
gain insights;
compliance is a
byproduct, 3
Q. In managing its stress-test capabilities, which statement best
describes your bank's goals?
(N=18)

Figure 4: Banks Support Stress Tests With Limited Automation
MEDIOCRITY IS NOT AN OPTION
Aite Group sees significant risk in banks' lack of support for their stress-test capabilities. First,
there is regulatory risk. The more poorly automated stress tests are, the more likely they are to
contain errors that invoke adverse findings—and require costly remedies—by regulators. Indeed,
surveying by Aite Group indicates a meaningful portion of banks have either received adverse
feedback from regulators, fear such an outcome, or have no idea how satisfactory their stress-
test capabilities will be in the eyes of regulators (Figure 5).
Partially manual,
partially
automated, 12
Fully or primarily
manual, 5
Fully or primarily
automated, 1
Q. Which of the following statements best describes the level of stress-
test automationat your bank?
(N=18)

Figure 5: Adverse Regulatory Findings a Real Risk for Banks
Errors and adverse findings when stress testing are no small issue. When, in April 2014, a large
Tier-1 CCAR Bank identified a longstanding error in its stress-test submissions and brought it to
the attention of the Federal Reserve, the result was suspension of both a planned dividend
increase and stock repurchase plan, causing the bank's stock to fall by 6.2%, a reduction to
market capitalization of approximately US$10 billion.
Productivity is also an issue. Aite Group finds that although banks don't always indicate costly
penalties or citations as costs of regulations, this is because they achieve what Aite Group calls
"compliance at any cost." Seeking to avoid the fines and negative press that result with
regulatory findings but lacking the centralized databases and automation required for complex
reporting, many banks achieve compliance by building small armies of mid- and low-level
analysts and report builders. Aite Group has anecdotal evidence that, among larger banks, these
departments can number in the several hundred, bloating banks' payroll costs by millions of
dollars.
STRESS-TEST DATA VIRTUALIZATION
In an effort to identify solutions to banks' stress test data-management challenges, Aite Group
has examined one data management capability: Delphix Virtual Data Platform (Delphix). Though
originally designed to support software development, this solution has been configured for use
by the stress-test teams of several large banks. In examining Delphix and talking with banks that
have struggled to create cost-effective stress-test capabilities, Aite Group identifies the features
that can improve a bank's management of stress test-related data.
Comments from
regulatorshave
been favorable, 6
No comments, but
we're confident
our tests will
comply, 4
Comments from
regulatorshave
been unfavorable,
2
No comments,
and we're not
confident our tests
will comply, 1
Don't know, 5
Q. Which statement best describes regulators' comments aboutyour
bank's stress-test capabilities?
(n=18)

DATA VIRTUALIZATION
Delphix uses four primary features to reduce the amount of storage a bank requires to support
its stress-test activities:
 Block mapping: This feature takes advantage of the fact that although stress tests
require multiple versions of large amounts of information, a significant portion of
this data does not change from one version, scenario, or copy to the next. For
example, while banks tend to set up individual environments and data sets to test
different assumptions about how their assets will respond to a particular economic
scenario, the vast majority of the data in these assets does not vary from one
environment to the other. Within such environments, all of the data about the loans,
their balances, their risk ratings, and economic sensitivities constitute the majority
of a stress-test data environment and will remain unchanged across all the
environments. The portion of data that changes across the environments is a
relatively small portion of the data set and consists largely of the downstream
impacts of analysts' assumptions about how bank assets will respond to an
economic scenario.
Delphix conserves storage space requirements by first identifying the blocks of
unique data within the stress-test environment that will change from one
environment to the next. When new versions of the stress-test environment are
required, they consist of only such unique blocks of data, which are then combined
with the remainder of the data set that does not change, on only an as-needed
basis. By storing only once the portion of a stress-test data set that is static and
constitutes a significant portion of the overall data, Delphix significantly reduces the
amount of storage required to support a stress-test environment.
 Efficient updating: Once Delphix identifies and stores the static portion of a stress-
test data set and changes to data points are required, Delphix maximizes speed by
accessing and changing only the data blocks that are variable.
 Compression: Delphix further reduces the amount of storage required for a stress
test by identifying gaps in data and blank fields to avoid unnecessary space usage,
then applying industry-standard compression techniques to further reduce the
space requirement.
 Bookmarking: Delphix enables compliance staff to bookmark and archive iterations
of both a stress test and the underlying point-in-time data sets for safekeeping,
much like using "save as" to create a draft version of a Word document.
Compression and block mapping enable such versions to be retained without a
significant addition to the required memory footprint.
CONTINUOUS POINT -IN-TIME CREATION
An important feature of data virtualization capabilities is their ability to be continuously on and
monitoring all of the applications and data sets relied upon for the performance of a stress test.
As a result, Delphix can accommodate the demanding ad hoc, pop-quiz nature of Dodd-Frank
stress tests by creating a snapshot of stress test-related systems as of any point in time. For

example, if a bank using Delphix to manage its stress test-related data sets and applications is
suddenly informed that it must perform a stress test as of a randomly chosen date three weeks
prior, Delphix can create a virtual version of every application and data set as of the end of the
exact business day required for a stress test.
SELF-SERVICE MANAGEMENT
Stress-test data virtualization systems also provide administrative capabilities that enable self-
service management and are designed for use by compliance or risk management staff who lack
technical training. These capabilities include defining users and groups of users, specifying what
data sets—or copies thereof—each can access, and whether each can connect to new sources.
Similar capabilities exist for governing the archiving of financial records as of required dates and
retaining them over the time periods required for regulatory compliance. Self-service
management capabilities can also be used to schedule data refreshes and distribution of data
sets to stress-test team participants.

BENEFITS OF STRESS-TEST DATA MANAGEMENT
SYSTEMS
In examining the capabilities of stress-test data management systems and comparing them to
the challenges faced by stress testing banks, Aite Group identified two primary benefits of these
systems: the avoidance of hardware costs and productivity improvements caused by better data
management. Identified in Figure 6, with their respective magnitudes, achievability, and ease of
quantification, these benefits warrant significant consideration by banks seeking to improve the
cost effectiveness of their stress testing procedures and capabilities. Identified as particularly
achievable and quantifiable was the benefit of reduced infrastructure costs.
Figure 6: Assessing the Benefits of Stress-Test Data Management Systems
Source: Aite Group
IMPROVED PRODUCTIVITY
Aite Group anticipates that banks using stress-test data virtualization can achieve productivity
increases as a result of fewer data catastrophes, better trust in data, and more rapid
construction of as-of data environments.
Low
Low
High
High
Achievability
Easeofquantification
Avoidance of
provisioning
delays
Shorterproject
cycle times
Less costly
point-in-time
construction
Avoidance of
data
reconstruction
projects
Better trust in
data
Improved
productivity
Reduced
infrastructure
costs

FEWER DATA CATASTROPHES
When stress-test teams are equipped with stress-test data virtualization capabilities such as
compression, block mapping, and bookmarking it becomes far less costly to save multiple
versions of stress-test data sets. With more saved versions of the stress-test data environments,
stress-test teams can recover from data catastrophes far more rapidly: Rather than perform a
labor-intensive sequence of root-cause analysis and data reconstruction, teams simply roll back
the environment to a pre-disruption point-in-time version or bookmark.
BETTER TRUST IN DATA
Although many banks perform stress tests without virtualization capabilities, and data sets can
be rebuilt or repaired when data catastrophes arise, lingering doubts about the data can be
costly. When unsure about the quality that underlies a stress test, managers—both in
compliance roles and in the lines of business impacted by the results—typically respond with
multiple layers of verification. In such environments, underwriters often confirm that the source
data is accurate, loan officers perform a sanity check on the performance of their loans under
projected conditions, and managers who supervise teams of lenders examine the underlying
data used to stress the portfolios for which they are responsible. Lastly, senior managers
responsible for the accuracy of submissions to regulators also perform double checks in an effort
to not wind up in an orange jumpsuit. Conversely, when stress-test teams benefit from fewer
data catastrophes and data reconstruction projects, a higher level of trust in data is the result—
for both stress-test team members and internal consumers of stress-test results who take
responsibility for their banks' submissions to regulators.
QUANTIFYING THE PROD UCTIVITY BENEFIT
Aite Group estimates that seven roles can be impacted when data virtualization both reduces
the number of data catastrophes and increases the level of trust in data. The resulting
productivity improvement has been estimated by Aite Group in Table A.
Table A: Quantifying the Impact of Data Virtualization on Productivity
Role Benefit Hours of
work
eliminated
per cycle
Average fully
loaded cost
per hour
(US$)
Head-
count
Gross
annual
savings
(US$)
Underwriter Avoided data reconstruction;
eliminated verification of risk
data at the loan level
40 $51.92 60 $249,231
Loan officer Eliminated verification of risk
data at the portfolio level
20 $97.36 10 $38,942
Lending
group
manager
Eliminated verification of risk
data at the portfolio level
20 $129.81 3 $15,577
Mid-level
compliance
Avoided data reconstruction,
eliminated verification of risk
data at various levels, reduced
120 $58.41 20 $280,385

Role Benefit Hours of
work
eliminated
per cycle
Average fully
loaded cost
per hour
(US$)
Head-
count
Gross
annual
savings
(US$)
staffer manual reporting
Senior-level
compliance
staffer
Avoided verification of risk data
at the portfolio level and manual
reports
60 $84.38 3 $30,375
Chief
compliance
officer
Reduced time spent verifying and
auditing stress-test inputs and
results
30 $129.81 1 $7,788
Chief risk
officer
Reduced time verifying and
auditing stress-test inputs and
results
30 $129.81 1 $7,788
Total $630,087
Source: Aite Group
MORE RAPID AS-OF DATE DATA RECONSTRUCTION
A less quantifiable benefit of a stress-test data virtualization system identified by Aite Group is
the ability to reduce the time and labor required to complete a profile of the bank's assets,
exposures, and risk-related applications as of the date randomly chosen by the regulator for a
stress test. For the largest banks, regulators perform bank stress tests in a fashion much like a
pop quiz. Twice a year, banks are informed that they must not only perform a stress test, but also
do so as of a randomly chosen date during the preceding fiscal quarter. Building data sets that
accurately reflect the state of all risk-related systems and databases at the end of business on
the stress-test as-of date is extremely labor-intensive, incorporating multiple versions across the
bank of assets identified in Figure 1. Up to 100 systems and data sets can be involved, only some
of which will have been properly backed up on the as-of date; some data sets will be hard to
identify and locate. Further complicating the challenge is the breadth of data that must be
obtained across a bank, including every subsidiary, line of business, and even the treasury
department, where exposures are likely to include complex assets such as hedges, which are
difficult to model in an economic projection.
Aite Group estimates that by providing continuous point-in-time recreation for the sources and
data sets in Figure 1, data virtualization systems enable banks to significantly reduce the amount
of labor required to create as-of data environments. Though difficult to quantify, Aite Group
estimates that among the hundreds of data sets for which accurate as-of-date versions are
required, at least 10% will be unavailable or corrupt, requiring either repair or rebuild by stress-
test teams, data owners, or staff in lending lines of business. Table A is based on a small to mid-
sized bank; Tier-1 and Tier-2 banks that adopt stress test data virtualization will likely experience
far higher savings.

AVOIDING PROVISIONING DELAYS
By enabling stress-test teams to independently fulfill their data requirements, data virtualization
capabilities can eliminate provisioning delays that disrupt analytical processes and lengthen
project cycle times. Stress testing's significant data requirements, including the provisioning of
data required for test, development, and run environments for multiple scenarios leave stress-
test teams highly dependent on other departments, such as procurement and IT. Compared to
compliance departments, such organizations are typically far more process-oriented and less
concerned with regulatory mandates. Additionally, the acquisition and usage of hardware for a
task as complex as stress testing is about far more than procurement, as devices need to be
configured, partitioned, secured, and equipped with varying levels of permission for different
roles within a stress-test team. As a result, stress-test teams often wait weeks or months for the
substantial storage assets they require. Although such delays may be tolerable for an in-house
software development team in a multi-year project, they are extremely disruptive for a stress-
test team with only 13 weeks to perform vastly complex projections of their banks' capital levels.
With data virtualization that can reduce storage requirements by an order of magnitude,
compliance departments can accomplish far more with their existing storage space and make
fewer hardware provisioning requests in a given stress-test season.
Although not readily quantified, avoiding provisioning delays and interruptions is considered
significant by Aite Group. Stress tests are vastly complex projects requiring data, analysis, and
collaboration among a large number of bank employees and departments. Stress tests are also a
highly analytical and intellectual project incorporating a thorough understanding of a bank's risk
profile and multiple projection scenarios. The less such a project is delayed or interrupted by
waiting periods for additional provisioning, the more continuous, accurate, and informed the
stress-test team’s data aggregation and analyses will be.
SHORTER STRESS-TEST PROJECT CYCLE T IMES
Aite Group expects shorter project cycle times to be the net result of fewer data reconstruction
projects, better trust in data, and avoided provisioning delays. Here, two outcomes are
important to Aite Group. First, with shorter project cycle times, banks are better able to meet
regulators' demanding stress-test timetables and avoid the compliance-at-any-cost practice of
dedicating more staff to a stress test in an effort to accelerate it. Better analysis is an even more
important benefit. With the ability to complete stress-test analyses more rapidly, and with fewer
interruptions or delays, banks will have more time to use stress testing to achieve risk-related
analytical insights rather than just complete the process as a regulatory mandate—an important
goal for banks, as indicated in Figure 3.
REDUCED STORAGE COSTS
A primary benefit of data virtualization is a substantial reduction in the amount of storage
required. The volume of data required to support a stress-test environment is significant and
driven by factors that include the number and size of risk-related assets such as enterprise
applications, their underlying data sets, macroeconomic scenarios, and regulatory requirements
that final versions of stress tests be maintained after their completion. Depicted in Table B, these
demands result in potential storage requirements that are cost-prohibitive for most banks. As a

workaround and cost-avoidance tactic, banks typically build their development, test, and run
environments to support all of their projection scenarios. Although this workaround can reduce
costs, it also has several drawbacks. First, having one set of environments for all scenarios makes
it more difficult for stress-test teams to maintain and govern separate data sets and scenarios.
Performance is also an issue; the more scenarios a given development, test, or run environment
supports, the more slowly applications in the environment will complete analyses and build
reports.
Table B: Stress Test-Related Storage Costs
Optimal Cost optimized
Number of stress test-related systems and data sets 100 100
Average size of a system or data set in terabytes (TB) 1.00 1.00
Number of scenarios modeled 6 6
Number of environments (development, test, run, archive) 4 2
Total system instances required in memory 2400 1200
Average cost per TB (in US$) $635 $635
Total cost (in US$) $1,524,000 $762,000
Source: Aite Group
Aite Group finds that data virtualization can significantly reduce the cost of storage required for
stress-tests with related data virtualization capabilities. In fact, Aite Group estimates that by
applying techniques such as compression, block mapping, and efficient updating, banks can
reduce stress test-related storage requirements by up to 90%. Accomplishing this can result in a
significant reduction to hardware costs for stress testing banks (Table C).
Table C: Stress Test-Related Storage Costs With Virtualization Techniques
Optimal Optimal with
virtualization
Cost
optimized
Cost
optimized
with
virtualization
Number of stress test-related
systems and data sets
100 100 100 100
Average size of a system or
data set in TB
1.00 0.10 1.00 0.10
Number of scenarios
modeled
6 6 6 6
Number of environments
(development, test, run,
archive)
4 4 2 2

Optimal Optimal with
virtualization
Cost
optimized
Cost
optimized
with
virtualization
Total system instances
required in memory
2400 240 1200 120
Average cost per TB (in US$) $635 $635 $635 $635
Total cost (in US$) $1,524,000 $152,400 $762,000 $76,200
Source: Aite Group

CONCLUSION
Given the availability of virtualization technology that can dramatically increase data
management capabilities, banks should consider the addition of such capabilities to their stress-
test technology roadmap. By significantly reducing the amount of storage required to support a
stress test, virtualization can also reduce the capital expenditures required for these analyses. By
enabling reliable, cost-effective bookmarking and archiving of multiple versions of stress-test
data sets, virtualization can also improve stress-test team productivity by reducing the number
of data catastrophes while also improving participants' trust in both their analyses and the data
on which they rely. Due to their continuous ability to perform a point-in-time recreation of a
data set or application, data virtualization capabilities can also significantly reduce the volume of
manual labor required to construct the highly detailed and data-intensive analysis of bank's risk
profile as of the date required for a stress test. By enabling stress-test teams to more
independently fulfill their data requirements, virtualization reduces the number and duration of
provisioning delays that can interrupt the complex collaboration and analysis required for a
successful stress test.

ABOUT AITE GROUP
Aite Group is an independent research and advisory firm focused on business, technology, and
regulatory issues and their impact on the financial services industry. With expertise in banking,
payments, securities & investments, and insurance, Aite Group's analysts deliver comprehensive,
actionable advice to key market participants in financial services. Headquartered in Boston with
a presence in Chicago, New York, San Francisco, London, and Milan, Aite Group works with its
clients as a partner, advisor, and catalyst, challenging their basic assumptions and ensuring they
remain at the forefront of industry trends.
AUTHOR INFORMATION
David O'Connell
+1.617.338.6001
doconnell@aitegroup.com
CONTACT
For more information on research and consulting services, please contact:
Aite Group Sales
+1.617.338.6050
sales@aitegroup.com
For all press and conference inquiries, please contact:
Aite Group PR
+44.(0)207.092.8137
pr@aitegroup.com
For all other inquiries, please contact:
info@aitegroup.com

Delphix_Analyst_Report_Aite_Sept_2014

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