Connect with the the authors: korrynn.loesch@curinos.com; gregory.muenzen@curinos.com
As we reenter a falling rate cycle, the rate differential between wealth deposits, money market mutual funds and cash sweeps that has existed since 2023 will continue to shrink. In the rising and higher-for-longer rate environment, cash sweeps and wealth deposits products saw massive outflows to digital banks and money funds. Rather than rate–chase to retain those balances, most firms let them run off and instead focused on preserving margin with the cash that remained. Today, sweeps balances hover between 2% and 3% of AUM, down from 5% to 7% of AUM prior to 2023. But as rate compression occurs (with money funds and deposits rates falling with Fed funds and most sweeps products likely to fall far less), it’s likely that sweeps programs will soon reverse course, from flat or nominally negative growth to a modestly positive growth trajectory. With this in mind, firms have two primary levers to optimize margin on their sweeps programs: pricing discipline that considers client elasticity based on client behaviors and the value derived from bank partnership programs (where the case is placed).
The Basics: Cash Sweeps Pricing
Using a sweeps product to drive client and balance acquisition versus using it as a primary revenue and margin driver is generally the difference between pricing to compete with deposits products and maintaining low but fair rates based on cash balance tier. In either scenario, optimizing pricing based on segment-level behaviors allows firms to maximize for growth or margin or to strike a delicate, and complex, balance between the two. But client-facing pricing is only one side of the profitability equation of a sweeps program. It’s imperative to also consider the economics of the bank partnership programs.
The profitability of a sweeps program depends as much on the economics of the bank partnership as it does on client-facing pricing.
The Basics: Bank Sweeps Programs
It’s common for broker-dealers to place cash at regulated depository institutions. Such a practice provides the dual benefit of safeguarding client funds through FDIC deposit insurance and providing margin revenue to the broker-dealer above the rate paid to clients on cash balances. But such programs are entirely or primarily overnight sweep arrangements through which broker-dealers earn floating rates on those balances. They’re thereby exposed to interest rate risk, especially when rates are falling. Such was the case in 2020, when precipitously falling rates prompted by the Covid pandemic resulted in a dual disruption to broker-dealer revenues: eroding asset prices and declining AUM-based management fees.
As a result, leading broker-dealers have increasingly employed fixed/floating cash placement, whereby a portion of sweep balances are placed at fixed terms and rates, which provide incremental returns through term premiums and stability to those returns. From the bank’s perspective, term placements are often preferable, to ensure funding stability or to achieve a target asset/liability duration position. Such broker-dealer strategies require commensurate risk management infrastructure, however, in the form of management limits around fixed-term exposures and duration. This ensures that balances remain accessible to support client withdrawals and/or investment needs. These limits need to be informed by behavioral analytics around client cash portfolios, similar to those employed by traditional banks for measuring liquidity and interest rate risk.
Increasingly, leading broker-dealers have placed a portion of sweep balances at fixed terms and rates, providing stability to their returns.
The Call for Better Cash Behavioral Analytics
In our view, there are several imperatives as broker-dealers apply such analytics:
- Depth of portfolio segmentation. Cash analytics should strive to capture behavioral differences in client cash stability within segments of cash portfolios. These should include client and/or account characteristics such as cash or AUM balance tier, self- vs. advisor-directed account status and brokerage vs. retirement account status. They should also consider the myriad differing advisor characteristics by segment and/or financial-advisor network. Brokerages will find discernible differences in client volatility, and allowable fixed/floating allocations will vary at the portfolio level over time as these concentrations evolve.
- Connection to product and pricing strategy. Cash volatility profiles will change as the pricing of cash balances evolves or becomes more differentiated because of product or balance tier-based pricing strategies described earlier in this perspective. Brokerages will find that cash volatility fluctuates in response to pricing changes, especially for more elastic segments of the portfolio, e.g. across balance tiers in response to balance tier-based pricing strategies.
- Scenario analysis capabilities. Broker dealers should be mindful of the range of alternative market interest rate scenarios that affect not only cash behaviors as described above, directly or indirectly as a result of corresponding pricing strategies, but also the performance (or downside risk) of various fixed and floating allocations.
Tying It All Together
In brief, bank partnership strategy development should be informed by cash analytics that connect to the way broker-dealers approach product and pricing strategy. The quality of client cash balances acquired through a sweeps product will contrast with those acquired as part of a primary checking venture. As a result, investment strategies must be governed in an integrated manner to optimize program returns while staying within the bounds of prudential risk management.
