Betterment

Betterment Architectural Assessment

Betterment functions as an automated investment engine that translates abstract financial goals into executable brokerage instructions. The architecture is built on a modular component framework designed for high-availability wealth management, leveraging a proprietary rules engine to manage portfolio drift and tax-alpha generation 📑.

Core Infrastructure and Asset Management

The platform maintains a decoupled architecture where the goal-setting interface acts as a configuration layer for the underlying trade execution sub-systems. This allows for continuous structural adaptation without manual recalibration of the core investment logic.

• Unified Processing Architecture: Integrates diverse financial data modalities—including market feeds, cost-basis history, and user risk profiles—into a single decision-making framework 🧠.
• Tax-Loss Harvesting+ (TLH+): A native process that systematically identifies capital loss opportunities. The system utilizes a secondary ticker methodology to maintain market exposure while realizing tax benefits 📑.
• Direct Indexing: A specialized sub-process for high-net-worth accounts that disaggregates ETFs into individual equity holdings for granular tax optimization 📑.

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Operational Scenarios

• Drift-Based Rebalancing: Trigger: Portfolio drift exceeds a 3% threshold or a new deposit event occurs. Process: The engine calculates buy/sell orders across the entire portfolio to restore the Target Allocation. Output: Batch orders are transmitted to the clearing partner (Apex Clearing) for execution 📑.
• Tax-Loss Harvesting (TLH+): Trigger: A security price falls below a specific cost-basis threshold. Process: The algorithm performs a wash-sale check across linked Betterment accounts and selects a pre-correlated secondary ticker. Output: Simultaneous sell (Primary) and buy (Secondary) orders 📑.

Evaluation Guidance

Technical evaluators should conduct due diligence on the following architectural constraints:

• Execution Latency: Verify the specific time-to-market for rebalancing batch orders, as execution speed is dependent on external clearinghouse settlement cycles 🌑.
• Third-Party Aggregation: Assess the reliability of external account syncing (e.g., via Plaid) as the wash-sale prevention logic relies on the integrity of these external data streams 🧠.
• API Availability: Confirm the availability of B2B endpoints for institutional integrations, as these remain largely within a private, gated ecosystem 🌑.