With the pressures of regulations as well as the desire to create actionable insights using standard definitions, financial management is seeking to employ the strongest possible approach to their standardization efforts. In this 2015 survey of financial management executives, FIMA has uncovered: How aligned data management strategies are with business goals The levels of outsourcing around reference data management How managers are breaking down data siloes

1. An In-depth Look at Current
Data Management Practices
The 2015 FIMA West Benchmark Report

2. 2
Table of Contents
Executive Summary.....................................................................................................................................................................................2
Research Analysis.....................................................................................................................................................................................3-7
Conclusions and Recommendations.......................................................................................................................................................7
Appendices................................................................................................................................................................................................... 8
Appendix A: Methodology.....................................................................................................................................................................................8
Appendix B: Demographics..................................................................................................................................................................................8
FIMA West..................................................................................................................................................................................................... 9
WBR................................................................................................................................................................................................................ 9
Executive Summary
Since the Dodd-Frank Wall Street Reform and the
Consumer Protection Act in 2010, data governance
for financial institutions has become an ever
increasing set of processes that continues to drive
huge transformation. Due to this strict regulatory
environment, government agencies are now
responsible for regulating most facets of a financial
organization’s process. Any part of the process
that is required for effective data and information
management is fair game. As we move through 2016,
regulations for the financial sector are here to stay.
There is no going back in time. The complexities of
data will only continue to increase.
Sell-side and buy-side firms share many of the same
concerns when it comes to data governance. The
majority of sell-side firms including, investment banks,
commercial banks, and brokerages have kept the
concept of data governance front of mind, dedicating
their attention towards strengthening their reference
data management solutions for greater compliance,
reporting, and enterprise risk management.
The majority of buy-side firms though are not as
established with their data governance initiatives,
and realize a serious reevaluation of data strategies
is a necessary next step to remain compliant with
regulatory demands.
It may seem like a daunting task, but driving change
is a must. And the cost savings and efficiencies
to be gained are significant. But we face two key
obstacles:
Breaking Down Siloes
Except for country-specific siloes where regulatory
differences make them potentially necessary, we
have to take a sledgehammer to the siloes. They
cost us time, money and are rarely in the best
interests of our business.
Alignment
With only 2% of respondents suggesting their data
organizations are aligned with business objectives.
While regulations affect global institutions differently
than a smaller regional firm, it is clear we have some
serious heavy lifting to do.
Interestingly, these two obstacles to progress can
be seen in just about any industry, financial or
otherwise. Both siloes and alignment are problems
faced across every industry Worldwide Business
Research serves. We are fighting human nature. We
are fighting ourselves!

3. 3
Less than one year
1-2 years
3-5 years
5+ years
1
2
3
4
5
7%
2%
24%
9%
33%
17%
36%
35%
37%
How long has the data management function been in operation at your firm?
How aligned is your data management strategy with business goals?
For financial institutions, the concept of data
integrity and data governance isn’t new. For 36% of
institutions within the industry, a data management
function has been in operation at their firm for
over 5 years, 33% for 3-5 years, 24% for 1-2 years,
and 7% for less than a year. Although having a data
management operation may seem like right steps
were taken, there are various components that go
into an effective program, and if those processes
are not in place it can be detrimental to the state
of the firm. Additionally, to remain compliant,
these organizations need to be up-to-date with
the regulatory environment surrounding their data
governance initiatives. As the regulatory environment
changes, all steps need to be reviewed.
(1=Significant Alignment, 5=Little Alignment)
Research Analysis

4. 4
44%
29%
24%
3%
How do you plan to institutionalize the data strategy in your organization?
Alignment is a vital component in any change
management initiative and especially imperative
to a firm that is working to improve existing data
management strategies. Currently, only 2% of
institutions denote that their data management
operation is aligned with business goals. While the
majority of respondents (72%) indicate that their
current data management strategy is not parallel to
their current business objectives.
Think about that for a moment…how can our data
management strategy, which is so critical to how our
business functions, not be aligned with the business
goals? The questions that come to mind quickly are:
Why not? What steps do we need to take to ensure
this? Who are the stakeholders to help me make this
transition? And it’s clear we want a more top down
approach, just by looking at the graph. Why isn’t it
happening? It just may be a story of complexity.
Top-down approach
business driven
Function-based data
strategy
CDO to drive the
global data strategy
Defined as per usage
of downstream
applications
Research Analysis
None, entirely in-house
Only non-critical data
functions are outsourced
Specific functions
like data validation,
cleansing, mapping and
transformation
Managed services for
Enterprise reference data
management
Reference data utility
25%
20%
2%
0%
What is the level of outsourcing across your reference data management functions?
53%

5. 5
Individual systems based
on business needs
Centralized reference
data management
Hub and
spokeframework
Multiple distributed
systems
16%
22%
29%
33%
To what extent is your data management function centralized vs. siloed?
The majority (53%) of firms have indicated that
they do not outsource across their reference data
management functions. While less than a quarter
(20%) of institutions are outsourcing for specific
functions like data validation, cleansing, mapping
and transformation, the bulk of organizations are
managing everything entirely in-house. To begin
to achieve economies of scale and reallocate
resources that can be applied to revenue-
generating activities, firms will need to turn to third
party suppliers for reference data management
support.
In which stage are we in the outsourcing journey?
Have we chosen to outsource non-critical
components? Or are we taking conservative steps
now and are looking to outsource more in the
future? Perhaps with more alignment with corporate
goals, we can unload more non-critical activities to
third-parties, freeing up our time internally to focus
on more critical data transformation projects.
And what about managed services? We could
categorize that with outsourcing. Some are
predicting that managed services will be the norm
within ten years. Given the significant cost savings
and efficiencies here, it will be interesting to see how
managed services develop in the next 3-5 years.
Research Analysis
Many firms are still organized in silos, especially
when it comes to data management, with 33%
reporting that they have multiple distributed
systems across their organization. The problem
with distributed systems is that they are complex
and difficult to understand and operate. Data
inconsistencies, reporting issues, and multiple
data sources of client information make it hard for
departments of one organization to work together.
29% of financial firms report that they operate off
of a hub and spoke business model. Some argue
that this model is the future of data management,
allowing their organizations to analyze and process
more forms of data at a lower cost. 22% of financial
institutions have adopted a centralized data
management program, while 16% of firms indicated
their data management function is siloed due to
having individual systems based on business needs.

6. 6
58%
30%
12%
How do you manage a meta-data repository or data dictionary for your reference data?
58% of us indicate multiple data standards due to
diverse data sources. Immediate questions that
come to mind are whether or not multiple standards
are optimal? What should be our preference here?
Given 30% have a standardized data model might
suggest that less standards are optimal, and a single
global standard might be most optimal. But there could
be legitimate needs for a multiple standard approach.
Multiple data
standards due to
diverse data sources
Standardized data
models
Global architectural
standards
Research Analysis
Existence of multiple data
sources and processing of
data in silos
Replacement of legacy
systems
Lack of enterprise-wide
governance model
Inconsistent client and
counterparty data
Instrument data
66%
45%
45%
32%
14%
What are the key challenges associated with adopting standardization in reference
data management?
(Results reflect respondents who selected all applicable answers.)

7. 7
Research Analysis
When it comes to the challenges firms face trying to
adopt standardization in reference data management,
various reasons hold them back. While survey
respondents were able to identify multiple challenges,
the most significant (66%) was the existence of
multiple data sources and processing of data in
silos. The second and third most selected, was the
replacement of legacy systems (45%) and the lack of
enterprise-wide governance models (45%), garnering
the same response rate.
The reason we don’t have enterprise-wide
governance models is likely a function of alignment
with business objectives. [See Chart 4 above]. If the
hub and spoke model is the future, and alignment is
so critical here, then we better get moving.
Data is the biggest asset a financial institution has. And make no
mistake, data management is complex. Even for senior corporate
officers inside the banks. These complexities might be slowing
down our most important data transformation initiatives. For those
of us who feel the transformation is too slow for our liking, we
have to simplify the story with key stakeholders who may have
difficulty seeing past these complexities. We’re talking saving
millions of dollars potentially and eliminating redundancies. It’s a
great story. Perhaps we have to learn to tell it better.
Siloes aren’t helping. We have to take a sledgehammer to the siloes
that are breakable. Clearly, with state and country regulations, siloes
can never be fully torn down. But no matter the industry, siloes
are a serious obstacle to progress. The hub-and-spoke approach
with the CDO at the center, and a single standard may be the key
to putting us in a position to show we can add significant value
beyond reporting. And that is, after all, what we’re all hoping for.
Conclusions and Recommendations

8. 8
Appendix
Methodology
Demographics
The results analyzed in this report were gathered from
responses to an on-site benchmarking survey delivered
at FIMA West 2015 and prepared by report author
Chyna Dama. 46 financial executives responded to
the survey.
How many employees make up your data management organization?
17% 1-5
30% 6-15
13% 16-25
5% 26-35
35% Over 35
New business models are emerging and buy-
side firms want to be on the cutting edge of data
governance. Although our research findings
indicate that 35% (16 respondents) of financial
institutions have 35 or more employees that make
up their data management organization, there are
far less employees on the buy-side compared to
larger investment banks. For 30% (14 respondents),
6-15 employees make up their data management
organization.
Balances of power are slowly shifting, and the drive
to increase efficiencies has led to a restructuring
across organizational landscapes. Firms are gradually
growing their departments, bridging the gap and
bringing together back office technologists, risk and
compliance, and settlements, front office traders,
M&A, advisory and sales representatives. As these
departments continue to grow, having the right
technologies and processes in place (so that they
are understood by more than one department) is
paramount to the growth of any financial institution.

9. 9
About Us
FIMA West
Join us at FIMA West 2016
Worldwide Business Research
Started in 2004, FIMA was created by the Data Management
Community; bringing together leading reference data management
professionals, examining topics that are of fundamental importance
to enterprise-wide data management initiatives. Now, in its 12TH
year, FIMA is regarded as the premier reference data management,
counterparty risk, and data innovation conference. FIMA West is the
only event that brings together the data management community
outside of the Northeast to get the best practices necessary to drive
change and ensure successful data management operations.
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