How Integrating the Risk System with Front and Mid office Trading Support Systems helps Risk Analytics in controlling risk effectively and complying with Emerging Regulations
How Integrating the Risk System with Front and Mid office Trading Support Systems helps Risk Analytics in controlling risk effectively and complying with Emerging Regulations
How Integrating the Risk System with Front and Mid office Trading Support Systems helps Risk Analytics in controlling risk effectively and complying with Emerging Regulations
1. Integrating the Risk System with Front and Mid office Trading
Support Systems helps Risk Analytics in controlling risk effectively
and complying with Emerging Regulations
In today's volatile markets financial institutions are under intense pressure to analyze and control their risks. Global economic
uncertainty, plus ever more extensive and complex regulation, requires institutions to be able to measure and manage market,
credit and liquidity risks in a consolidated manner across all instruments, portfolios, business lines and geographies.
At the same time, they must continue to generate revenue in intensely competitive markets. To succeed in such an
environment requires a technology infrastructure that is integrated, efficient and cost effective.
In recent years, many institutions have benefited from straight‐through processing (STP) between front‐ and back‐office
systems. Trading and risk management have lagged behind because there is often duplication and inconsistency in pricing that
must be reconciled before aggregation and analysis can begin.
STP for trading and risk can be achieved by creating a single platform with common pricing and analytics. This consistent
platform will provide a bridge between the front office and risk management, enhancing communication and allowing experts
to focus on their core tasks. The result will be improved efficiency, reduced costs and better decision‐making.
The Problem
In a traditional infrastructure, front‐office trading is optimized for making the best deals and hedging positions, for which it
needs advanced pricing tools and sensitivity analysis. Meanwhile, risk management has the responsibility for oversight of
trading activities and calculating enterprise‐wide exposures, so it too prices the deals before it aggregates positions, runs
value‐at‐risk (VaR) calculations and monitors limits.
Herein lies the crux of the problem.
Trading and risk can use different pricing methodologies. In these instances, results must be reconciled and any discrepancies
resolved before risk management can proceed with its aggregation and analysis.
This delay not only hampers the timely calculation of risk measures, but also holds back the development of new products and
activities, as each new instrument and pricing model must be developed twice ‐ in the trading system and in the risk system.
Many of today's trading systems offer at least some degree of risk management functionality. However, this does not
necessarily solve the problem. They remain trading systems at their core. The risk functionality is focused on the trades
captured in that system and is therefore not sufficient for a risk manager.
To support a complete risk management process, the institution may be forced to supplement the trading system
functionality with consolidation engines, limit management applications and a host of intermediate tools that glue things
together, often including macros, spreadsheets or other applications, which can be difficult to manage and maintain, and
increase operational risk. Trading system risk functionality is naturally tailored to the specific system and is not well suited to
aggregating and managing data from several sources.
The conventional alternative is to install a dedicated enterprise risk management system that is designed to aggregate trading
data and calculate enterprise risk measures.
While these systems can offer sophisticated enterprise risk capabilities, they are at a step removed from the trading
environment, employing their own models for pricing and risk calculations that must then be reconciled with the front office
data and models. This makes them costly to install and maintain, and hampers the fluidity of the interaction between traders
and risk managers.
3. That adds complexity to the systems infrastructure and can be difficult to maintain and upgrade.
Advantages of an Integrated Approach
Tightly integrating risk with the front office through the sharing of pricing models has a number of advantages:
Straight‐through processing. The term is much bandied about in financial technology. However, while trading
systems are routinely able to process transactions straight through, from trade capture to the back office, the
same degree of automation and efficiency is more difficult to achieve in risk management. Evidence shows that
STP is most successful where it is designed into a system rather than superimposed through patches and
workarounds. Such forced solutions are inevitably unreliable and time‐consuming to maintain. To avoid these
problems, STP should apply as much to the front‐to‐risk connection as it does to the front‐to‐back‐office.
Sharing pricing across trading and risk management systems will make STP integral to the overall system
architecture.
Improved efficiency, reduced cost. Duplication of effort is never efficient. Where the front office is already
calculating prices fast and accurately, it makes little sense to transfer the raw data and duplicate the process in
the risk system ‐ especially where this then requires time consuming reconciliation of results. If the front‐office
system is already using state‐of‐the‐art pricing, the most efficient thing to do is to take those prices into the risk
management process. This will help reduce costs too.
Experts allowed doing their job. Trading and risk management require high degrees of expertise and
concentration. It is a misuse of the experts' time to have to perform unnecessary manual procedures, carry out
continual system checks and reconcile results of what are essentially the same processes. The technology
infrastructure should not be a distraction, but rather should support the experts in the performance of their
roles, freeing them to concentrate on where they can add value to the business.
Intra‐day risk analysis and centrally managed limits. An integrated trading and risk system ensures that
economic scenarios are generated just once and used as a "golden source" for all risk and performance analysis.
With consistent and consolidated risk data, users can perform various types of risk analysis and calculation on
demand, from portfolio slicing‐and‐dicing to stress testing and VaR. Consistent and consolidated risk data also
enables limits to be managed centrally with associated alerts.
Reduced operational risk. The intellectual focus on market and credit risk, and more recently liquidity risk,
means that operational risk is often underestimated or overlooked. Yet many of the largest losses in the
industry can be traced back to operational factors. Even where individual operational incidents don't make the
headlines, their cumulative impact can be a drain on resources and a restraint on business. STP not only
improves efficiency, but also reduces operational risk. Automating processes between the trading and risk
systems and avoiding the need to re‐key information drastically lowers the potential for errors as well as the
need for manual intervention. It should go without saying that a system designed to manage market, credit and
liquidity risk should not create operational risk in the process.
Bridges between trading and risk. The primary duty of risk management is the oversight of risk. Therefore, it
should be independent from the front office. This does not mean that trading and risk should not communicate.
On the contrary, there needs to be a constant dialogue through which risk issues can be addressed quickly and
effectively.
The technology infrastructure should not be a barrier, but should rather enhance this communication.
Integration of trading and risk systems will help ensure that all parties start with the same information so they
can get directly to the issues at hand. Instead of having to discuss which valuation is correct or whether a proxy
used in a pricing model is accurate, the parties can get straight to examining particular risk indicators, assessing
high‐risk areas in a portfolio, analyzing the behavior of the markets, or reviewing assumptions about liquidity.
An integrated technology infrastructure will facilitate this conversation, enhancing both risk management and
trading‐revenue generation.
New business facilitated. Another consequence of the disconnection between trading and risk is the brake it
puts on new‐product and business development. Conventionally, if a trader wants to introduce a new product,
or the institution wants to start a new business line, it must be separately implemented in both front‐office and
enterprise systems. Pricing and valuations must then be checked and reconciled, and risk management needs
to validate the pricers used in the trading system and develop or validate new ones for the risk systems. This
duplicates effort, creates an additional step and introduces the possibility of inconsistency and error ‐ all of
which act as a constraint on business, slowing time to market and inhibiting competitiveness.
4. By relying on a single set of product models and pricers, the same level of control can be maintained while
eliminating unnecessary duplication. Furthermore, by focusing risk management efforts on analyzing and
validating a single set of production models and improving the related risk assessment tools, more insight can
be gained than by diverting resources to the maintenance of a second production system. Alternate models are
a key tool of model risk assessment, but these are best deployed in a dedicated environment, allowing
exploration of the modeling space without the constraints of a full production system that must be capable of
handling all existing trades.
Enhanced decision making. Close integration of trading and risk systems creates a single consolidated view of
risk. This makes analysis of risk factors and the exploration of what‐if scenarios easier and faster, fostering
insightful analysis of market and product dynamics and enhancing business decision making.
Greater transparency for shareholders and regulators. An integrated front‐to‐back office system with consistent
position capture, models, pricing and valuation enables the institution to achieve a consolidated view of
exposure across the enterprise. A single representation of data and STP allow for rapid reconciliation and
auditing of the institution's risk profile. This single integrated view of risk facilitates regulatory reporting and
enhances transparency for shareholders.
Rapid implementation. Because the risk system is designed for close integration with front‐office systems and
the sharing of pricing and valuation methodologies, implementation is faster than if the institution either has to
create an additional layer of functionality on top of trading system risk extensions, or is implementing a stand‐
alone risk system with complex interfacing and reconciliation procedures.
Leverage of existing computing grids. Because models are not duplicated, there is no need for separate
hardware and software for pricing. Existing computing grids can be optimized, thereby saving on hardware,
software and operational costs. Similarly, a single set of pricing data eliminates the need for additional storage
and data management. Overall, IT infrastructure is leaner and less complex, and therefore easier and less
expensive to maintain.
Conclusion
Traditionally, risk management has re‐priced deals it has received from the front office. With modern trading systems offering
fast and accurate pricing, this duplication of effort is not only unnecessary, but also often leads to a more complicated and less
reliable infrastructure, and to a distracting and time‐consuming reconciliation processes.
By tightly integrating the risk system with the front office, an institution can not only improve the efficiency and reduce the cost
of its IT infrastructure, but can free up experts to get on with analyzing risk and developing the business.
A publication by James Jeffrey Okarimia
Partner at RM associates: Partners in Enterprise Risk Managements