Hi,
Problem #1: Compliance
Why is there a gap between pre-trade and post-trade compliance? Normally, human error and lousy design are to blame. If your order management system differs from your FX execution management system—which is generally the case—you can be at risk. A rules system that is linked to a database assures static compliance (“Is counterparty A an acceptable credit for subaccount X?”) and also dynamic compliance (“Did the trade I just performed use up all of my exposure limit to counterparty A for subaccount X?”). When the trade tickets are originally generated by the rules engine, you won’t have to explain to angry clients and portfolio managers why you inadvertently violated their guidelines. Eliminate the worry by letting automation take over. Just set it (i.e., the appropriate rule) and forget it.
Problem #2: Optimizing the Trade
Your OMS probably can tell you what currency a subaccount needs to buy or sell (the “dealt” currency), but it’s unlikely that your OMS has the intelligence to optimize for picking the right currency pair to trade. Except for the simple case in which every FX trade is vs. a base currency, how can one determine the counter currency? Cue the rules engine.
The rules engine can solve according to the priorities you set—it can set up objective tests (e.g., sell the currency with the lowest current yield, the highest balance, moving average exchange rates, etc.) or subjective tests you can set up in advance (e.g., selling your least favorite currencies and buying your favorites according to a table where you update your preferences according to your gut feeling.) The same choices can be made based on the type of trade (spot, forward, swap), type of execution (RFQ, order book algorithm, index trades, etc.). Cycling through the countless possibilities takes fractions of seconds, not the hours that many traders have to commit to pre-trade staging. It’s far better to program and update your strategies, then let a state-of-the-art system take over to optimize according to your rules.
Problem #3: Choosing Counterparties
If we’ve narrowed our choice down to 10 different counterparties eligible to be shown the trade, how many and which ones make it to an RFQ? Now you can think big picture while the rules engine sweats the details. Some of your considerations could include which dealers: a) are most competitive in the currency pair selected; b) you want to reward for giving you good ideas; c) have the highest credit quality of those under consideration; d) have the most room available under the credit exposure cap; or e) meet any other customized instructions from management to give a minimum amount of business.
That’s a lot to juggle in your head … over and over on every trade. But not for a computer once you’ve set up your rules. Let’s say you are strongly encouraged to show business to an important bank relationship for an account, but that bank routinely gives bad prices. You can solve the problem by steering WM Index business in major currency pairs to the offending bank, fulfilling your obligations while minimizing the potentially bad execution. Using rules doesn’t mean defaulting to simple processes—indeed, if everything were simple, you wouldn’t need a rules engine. But we bet that EVERY trader can benefit.
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