Managing Operational Risk in the Middle Office

25 октября 2012

Alexey Baburin, Head of QORT development, ARQA Technologies, International Securities Services: Q3 2012

The technological progress and globalization of financial markets has brought about apprehension on the part of securities overseers and pushed them to devise even more stringent regulations.

Most of these involve risk control systems and compliance reporting. Market participants, in turn, have also become more concerned about increasing the efficiency of their risk management systems at the pre-trade and post-trade levels.

In addition to pre-trade control functionality implemented in front-office solutions, the full automation of risk management may also be implemented through the use of a middleoffice solution. The later is the core of a larger system where all information flows come together and the full processing of trade data can be performed. In addition, the depth of accumulated data and its continuous analysis provide the basis for trading restrictions input into front-office systems.

From a business development perspective, the middle office is the place where all relevant information comes together and important management decisions are made. It also allows for integrating data about all of the assets, positions and markets for any group of accounts.

At the core of ARQA Technologies off ering is risk control. The front-office solution QUIK employs a broad arsenal of pre-trade risk control tools. It allows for orders to be filtered and positions to be adjusted from order placement and execution platforms.

Full automation of risk management is achieved through midQORT, which automatically uploads a front-office system with limits and restrictions for client accounts. Ongoing accounting and revaluation of positions in real-time ensure unfavorable consequences from trading operations are prevented.

An important feature of the QORT platform -- and midQORT in particular -- is that it manages information online and not in an end-of-day mode. As a result, its risk management functionality allows brokerage personnel to perform all required risk control procedures concerning clients and traders and to aggregate relevant reports in real-time.

MidQORT lets fi rms accurately evaluate changing positions resulting from trading and non-trade operations which, as a rule can be problematic if done at the level of a front-office system. When it comes to risk analysis, midQORT relies on the following widely used models:

  1. As midQORT offers a single point of data on all clients, operations, accounts and transactions, it makes VAR analysis on the basis of historical data over various time periods. Value-at-risk represents an estimated value of monetary loss which will not be exceeded over a period of time with a specifi c probability. Application of VaR analysis allows for a portfolio of securities to be managed while keeping its value within acceptable loss boundaries. Besides its use in proprietary operations, such an approach is indispensable to servicing clients in trust management.
  2. Monitoring P&L at the middle-office level allows for spotting transactions and potential fraud. The midQORT solution uses the following approaches to making P&L calculations:
    • Breakeven calculations at a given moment of trading by fixing the start-of-day price and further comparing it with the current market price;
    • Calculation of realized profit for a given period from position-closing operations which fall within the period irrespective of the date of opening positions;
    • Calculation of a financial result for the current day as a difference between a financial result for a given period including the current day and a financial result for the same period excluding the current day.
  3. For decision-making purposes when trading in derivative markets, the midQORT platform employs SPAN-like modeling. The SPAN approach allows forecasting changes in the value of a portfolio of derivatives depending on the market condition.

The high capacity of data processing is one of the key requirements for risk control systems and the middle office in particular. The requirement only increases in importance, as algorithmic trading takes up a greater share of trading volume in the fi nancial market. An extra benefit of midQORT is that it can perform simultaneous position keeping for dozens of thousands of customer accounts and process information on 800,000 transactions conducted daily.

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