This is part 3 of a series on the implications of automated portfolio rebalancing technology for the wealth management industry. To start from the beginning, read part 1 here.
Wealth management compliance today is like auto manufacturing 30+ years ago. (You can see an earlier post on this here.) I remember a 1980’s ad for a European luxury car company featuring dozens of quality control inspectors in white lab coats surrounding a car fresh off the assembly line — the company was touting the time and effort they put into catching defects. At the same time this ad came out, Toyota, which pioneered lean production, was manufacturing higher quality cars in less time than the competitor, who only had their inspectors spend time correcting defects. Toyota’s secret (which was subsequently copied by all car manufacturers) was to “build in” quality. They reorganized their assembly lines and their processes to enable them to avoid defects in the first place. The result was both higher quality and lower costs.
Similarly, automated rebalancing enables wealth management firms to “build in” compliance, with a similar double win of both lower costs and superior compliance. When rebalancing is automated, compliance is fundamentally transformed. This comes from two fundamental characteristics of automated rebalancing: “structured” data and support for efficient daily review and rebalancing processes:
- Structured data: Traditionally, an account’s customization parameters have been recorded — if they were recorded at all — as ordinary text, e.g. “the client requested no tobacco stocks.” With automated rebalancing, these parameters are stored in machine readable form (so called, “structured data”). Structured data can be passed from system to system and can be “validated”, meaning that users can be stopped from entering invalid or undesired information, like websites that won’t let you enter “March 34th” as your birthday. This has two implications for compliance:
- Risk-suitable targets: Rebalancing systems don’t determine suitability, but they can be linked to profiling systems that have APIs, ensuring that every portfolio is rebalanced to a risk-suitable target. For example, you can make sure that an “income” client (as determined by the profiling system) will never have an “aggressive growth” target.
- Bounded, validated customization: Customization is critical to providing investors with an investment solution that meets their needs, but customization can also be a backdoor path to non-compliance. For example, it would be problematic to “customize” a strategy by changing the recommended real estate allocation from 5% to 95%, or by designating a small cap ETF as an acceptable alternative to a firm’s recommended large cap holdings. On the other hand, you do want to permit reasonable customizations. For example, it may be okay to increase a 5% allocation to real estate to 10% and it may be OK to replace a large cap mutual fund with a large cap ETF. These sorts of bounds on permitted customizations can easily be built into the rebalancing system.
- Daily review and actionable response: The need for rebalancing can come from many sources — market drift, a change in asset allocation, model changes, a change in client customization parameters, security transfers in or out of an account, cash withdrawals or deposits, etc. An automated rebalancing system needs to be able to handle all of these whenever they occur. This has two implications for compliance:
- Daily compliance review and response: With automated rebalancing, every portfolio is reviewed daily for violation of any type of mandate — drift, ESG constraint, etc. More importantly, the system will automatically propose trades that fix any problem it finds. This means that no portfolio will ever be out of compliance with its parameters for more than one business day.
- Consistent rebalancing process: Consistent processes are at the heart of compliance. With an automated rebalancing system, it becomes possible to design and implement a consistent process for rebalancing. Not just a consistent process for when to rebalance (e.g. “every quarter” or “when asset class ranges drift more than 20%”) but a consistent process for how portfolios — no matter how customized — are rebalanced.
With these changes, compliance is “built in.” Assuming the profiling system has structured data and each account's profile is filled out correctly (which can be validated by sending this information back to clients), every portfolio will be rebalanced according to a consistent process and will automatically:
- Follow a risk-appropriate target.
- Have reasonable customization parameters.
- Be in compliance with all its parameters, every data.
The result: better compliance at lower cost.
Next week: The implications of automated rebalancing for when, why and how portfolios are rebalanced (Spoiler: it's not taking current processes and just automating them.)