Citi Prime Finance’s 2011 IT Trends & Benchmarks Survey
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process and too little emphasis placed on controls to protect
against fraud as underscored by the Bernard Madoff scandal.
The impact of these discoveries on the hedge fund industry has
been profound. Investors have subsequently demanded more
transparency into a hedge fund’s positions, exposures, liquidity,
investment decision-making process and use of leverage. They
are looking to understand the risks their stable of managers are
taking and the controls each hedge fund has set up to monitor
and optimize their investment process, and to ensure that there
are independent checks and balances within the organization.
They are looking for themanager to be able to demonstrate their
success at generating alpha and to show that their performance
is not overly tied to standard market performance (beta).
Regulators are pushing for more widespread registration of
hedge funds as investment advisors. Having this designation
requires that the manager have a robust compliance program
which can be demonstrated in audits or spot evaluations.
Moreover, rules put forth in the U.S. Dodd-Frank Act also state
that each hedge fund must supply information deemed critical
in helping determine the market-wide level of systemic risk.
To capture such information, the CFTC and SEC are jointly
proposing that hedge fund managers fll out new documents
such as Form SLT and Form PF, a new fling expected by year-
end that requires the hedge fund to report on up to 1,900 inputs,
covering areas as diverse as investor concentrations, assets,
portfolio turnover, performance, exposures, value-at-risk and
potential losses in a stress period.
Meeting these investor and regulatory expectations, and having
the fexibility to use their own information more effectively to
improve their alpha generation, proved diffcult for the majority
of hedge funds post the 2008 crisis given their standard IT
confguration. This divergence between emerging demands for
hedge funds to produce data and reports fexibly, and the rigidity
of the existing systems, set the stage for Wave 3 customizations
as shown in Chart 10.
Emerging Data Management Solutions
Offer Required Flexibility
Post-2008, and even today, most hedge funds rely on a few core
systems, which they have only lightly integrated at key points in
their workfow. Reports are generated and the underlying data
populating such reports is typically housedwithin each individual
system. Trading reports are produced and the underlying data
stored in the OMS or EMS. Accounting reports are generated
by, and the underlying data stored in, the portfolio management
system. Risk reports come from the risk system and so on.
There is no normalized “model” that ensures that similar data
points are defned in similar ways across systems. There is no
centralized point of capture where data is housed and reports
can be built that combine information from multiple systems.
To meet this challenge, the most sophisticated funds built
internal data management platforms where they took in feeds
fromall their various systems, normalized the incoming data and
stored the information in customized data warehouses. They
would then purchase separate reporting tools that allowed them
to tap into their data warehouse, build custom reports and feed
such information to investors or to various parts of their own
organization via internal dashboards. Creating these solutions
was time consuming, expensive and complicated. Sustaining
the resulting infrastructure infated the hedge fund’s IT costs
Yet, the lessons learned by hedge fund pioneers in creating these
infrastructure-heavy data management solutions are beginning
to spawn new offerings in the market that offer the promise of
lighter-weight, more nimble solutions for hedge fund managers
now looking to spend money to build capabilities in this space.
As we saw with both Wave 1 and Wave 2 evolution, hedge
fund technologists involved in creating initial Wave 3 data
management solutions have begun to spin out and start their
own consultancies and offer their own product. These teams
are focused exclusively on the hedge fund space. They bring
to the table unique insight into the data structures used by the
foundational systems, counterparties and service providers
aligned to their former hedge fund employers. Upon leaving
those frms, these individuals began to develop consolidation
engines geared toward the disparate sets of hedge fund specifc
industry data. Examples of frms that have had success in this
segment include MiK Fund Services and Indus Valley Partners.
Increased Focus on Alpha Creation & Investor
Desire for Transparency & Controls
Systemization of Investment Decision-Making Process
& Customization of Risk & Compliance Platforms
Measurable Assessment of Idea Generators &
Expanded Risk/Compliance Reporting
Adaptation of HF Tools for Investor Community
HF IT Investment
Resulting Differentiation
Commercialization of IT Spend
Chart 10: Wave 3 Hedge Fund Investment Cycle