Why Asset Managers Implement Compliance Solutions
Even with the systems available today, the picture is far less complete, with many managers carrying out checks only on order entry, and overnight against their accounting records. Some of the market leading systems still have embedded checks, so that they can be sold as stand-alone, without the related compliance tool.
It is more difficult to achieve a good level of integration if you chose to implement a compliance system from a different supplier from your orders and dealing system. We believe that, as compliance restrictions and investment objectives become more involved in the construction of compliant models, it will become impractical to run a genuinely independent compliance engine.
The risk of a compliance implementation is strongly influenced by the sequence of take-on: do you go for pre-trade and post-trade checking together, or can you limit checking to post trade until you are happy with the integrity of your rules and data? If you can afford a period of shake-down of rules and data before the system is relied on for day to day monitoring, then this will reduce project risk and increase the credibility of the solution.
Key determinants of the scale and complexity of a compliance project include:
Compliance systems are data-hungry, and will highlight any deficiencies in your data. Poor data quality will make your compliance service unworkable, and its credibility will soon evaporate, you have no choice but to deliver the data properly.
A compliance implementation can be low risk and high gain: the system can be introduced into the business at a controlled pace, and its scope can be increased over time in line with the availability of rules and data.
The major problem with current compliance systems is that, however good they are at what they do, they are doing the wrong thing: they are passive and negative by design, acting as filters, sieving out breaching orders and creating a reject pile. They allow us to catch breaches earlier, by shortening the feedback loop, but they do not eliminate the feedback loop. The real objective is to construct compliant models and strategies in the first place.
Our mission at DSTi is to do is to provide high quality decision support. We need to use compliance rules constructively in the generation of compliant models and optimised liquidity strategies. Most strategies would not be constructed in the first place if the manager knew that a fraction would be rejected, so checks on a what-if order flow are an inadequate approach.
Compliance engines are rules-driven, which is appropriate for a 'negative' approach, where we are filtering out failures. For constructive compliant modelling we need rules represented as active data, which can act as constraints to an optimisation. It is a challenge to achieve this without creating a replicate store of compliance data.
Rulesets are restriction-focused, they are designed to support the passive breach-filtering process. If we deliver positive and active decision-support, then we will need to represent the positive aspects of mandate - the clients' investment objectives and risk appetites. This will bring us closer to the risk world, and will bridge the gap between the source of the manager's opinions and the decisions they take in practice.
Compliance system support has improved massively in recent years, but the real business benefits and the real technical challenges are still ahead of us.
DST
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www.dstinternational.com
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