Because FINRA Rule 2111 and the related Dodd-Frank provisions require a significant process reformation and data collaboration, the model should be rules-driven and flexible to optimize the inherent cross business-line data while contemporaneously leveraging any applicable safe harbor provision.
Safe harbors, which constitute a legal provision to reduce or eliminate liability, are often used as a part of a compliance strategy. For example, Rule 2111 requires broker-dealers and associated persons, for both retail and institutional accounts, to document with specificity their reasonable basis for believing that a given profile data element is either not relevant, or alternatively, customer-provided with a reliance on the accuracy of the customer’s submission. The reliance on the submission as part of a rules-based collaborative onboarding process constitutes reasonable basis – provided no red flag or suspicious activity is detected. Because of the ongoing and perpetual suitability requirement, the collaboration feature is likely the next generation of onboarding intelligence.
Rule 2111, in part, is comprised of reasonable-basis suitability. The reasonable-basis obligation requires a broker-dealer or associated person to have a reasonable basis to believe that the product or strategy recommendation is suitable for at least some investors. FINRA, through its guidance, stated that “[b]rokers cannot fulfill their suitability responsibilities … when they fail to understand the securities and investment strategies they recommend.” Where the broker-dealer’s repository already contains product and strategy data, the rules-based query engine could easily harmonize the data (for cross-selling purposes), and/or evaluate profile suitability (for compliance purposes). The collaboration rules are necessary to allow for any after-the-fact determination that may narrow or widen the customer/counterparty risk tolerance, time perspective, or other data element.
Suitability is an often misunderstood concept. Many misapply the suitability test as a subjective determination and attribute the analysis to a single customer – and an anticipated product. This oversimplification effectively wastes useful aggregated customer profile data by failing to leverage system-based profile range analysis.
FINRA Rule 2111 has made customer onboarding more complex. First, the data must be more time-sensitive and dynamic to account for changes in customer risk tolerance, circumstance, or investment strategies. Second, Rule 2111 expands the scope of customer recommendation. The suitability rule applies to any recommendation to a customer. “Customer” is defined broadly as anyone who is not a “broker or dealer” and includes an individual or entity (including institutional customers) with whom a broker-dealer has a business relationship related to brokerage services. Even a non-transactional business relationship where no account was opened, nor any transaction effectuated, under the rules, will constitute a broker-customer relationship.
A rules-based processing engine is necessary to account for changes in customer risk tolerance, circumstance, or investment strategies as required by Rule 2111. Data elements that contribute to customer profiles should be leveraged in advance, while the onboarding solution proactively aligns customers with strategies and simultaneously measures real-time suitability. The collaboration feature must be flexible and rules-based to account for individual circumstances and proprietary business methods.