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Shining a Spotlight on the Client Commission Costs of CSA-Soft Dollar Aggregation Platforms

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Shining a Spotlight on the Client Commission Costs of CSA-Soft Dollar Aggregation Platforms

Commission Sharing Arrangement (CSA) aggregation platforms offered by brokers and some technology firms are a well-accepted solution to the management of multiple CSA/soft dollar trading relationships. However, most of these solutions are characterized by excessive, unpredictable, and opaque client commission costs, leading to volatile and unnecessary charges on client commissions, asset manager resource allocations, and CSA broker revenues.

CSAs allow asset managers to generate trading commissions for the payment of third-party research. They are a significant portion of the buyside equity commission wallet, accounting for over 40% of total buyside commissions. 4 out of 5 buyside firms have CSAs, and over 50% of CSA program volume is executed electronically. The number of CSA brokers each buyside firm works with varies greatly.

CSA aggregation platforms provide administrative support by managing CSA trading commissions across multiple brokers, tracking credit balances, and handling research payment requests. While funded by client commissions, they do not fit strictly into trade execution or equity research categories, representing a unique aspect of the CSA regulatory landscape. They represent client commissions being used for a service not directly linked to investment decision-making.

Economics

CSA aggregators share the execution component of a CSA trade with the executing CSA broker. Rates can vary depending on several factors. Typically, they range from 4 mils per share (.0004 cents per share) to 10 mils per share (.0010 cents per share, or 1/10th of a cent per share). These “mils” can add up fast. If that particular asset manager is executing 10 million CSA shares per month with that CSA broker, the CSA aggregator is paid $7,000 per month, or $84,000 per year.

Some CSA aggregators implement annual caps on their toll charges. These are put in place to cap fees at, for example, $75k per year per CSA broker. However, caps are far from universal and can still total over $1 million per year for asset managers with well-developed CSA programs and many CSA brokers.

Reducing the Excessive Cost of CSA Aggregation

The problem with this model is excessive costs and overpayment of client commissions. Payment to the CSA aggregator increases as CSA trading volume increases, in some cases dramatically. However, the operating cost of administering the CSA program is essentially the same. The payment to the CSA aggregator can quickly grow out of proportion to the cost associated with managing a client’s research payments, sometimes by hundreds of thousands of dollars.

In a declining margin environment for trading equities, especially using electronic venues, the expense of the current CSA aggregation pricing model is unsustainable. A 4 mil aggregation fee on a 40 mil electronic trade is 10% on every share. In addition, the opaque nature of the current pricing model leads to cost uncertainty, a lack of transparency, client inconsistency, regulatory risk, and unnecessary volatility across time.

The solution is to bring CSA aggregation costs back to reality. S&P Global Market Intelligence provides a best-in-class CSA aggregation platform, free to the asset manager and with a flat annual CSA broker connection fee that does not increase based on trading volume.

This platform is directly tethered to the actual cost of managing a CSA aggregation system, including offering discounts for low-volume CSA brokers. Our pricing can slash CSA aggregation costs across the board, and in certain cases by up to 90%. We are not a broker/dealer and cannot compete for order flow.

Research unbundling has delinked research cost from trade volume, and it’s time for the unbundling of CSA aggregation cost from trade volume as well.

Download the full report today >

For more information/discussion or to schedule a demo, please visit s&pglobal.com/researchmanager.com

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