RIA & Wealth Management
Illustrative scenario

Continuous Tax-Loss Harvesting: Capturing the Windows Your Monthly Process Misses

Running a direct indexing platform at scale means promising clients tax alpha — and then struggling to deliver it because your portfolio analysts are identifying harvesting opportunities at month-end while the real windows open and close during intraday volatility. For a Head of Direct Indexing managing thousands of individual accounts, the gap between what continuous TLH could deliver and what monthly manual monitoring actually captures is a material product quality problem.

Up and running in ~5 wkFor: Head of Direct Indexing / Head of Tax-Managed Investing
Estimate your payback
~3 mo
Payback period
$600K
Est. savings / year
+$440K
Year-1 net

Rough estimate — change the numbers to match your business. We scope the real figures with you on a call.

Month-End Monitoring Misses the Point of Direct Indexing

Tax-loss harvesting value is concentrated in market volatility events — the sessions where positions move sharply intraday and create temporary losses against cost basis. A portfolio analyst reviewing Orion positions at month-end captures the losses that survived to the close of the final trading day. The harvesting opportunities that opened during a volatile session and closed before month-end are simply gone. At $350K–$800K/yr in investment ops labor, your team is working hard and still leaving alpha on the table because the monitoring cadence is structurally misaligned with how harvesting windows actually appear.

Intraday Monitoring With Wash Sale Awareness

An AI Labor Company agent learns from your portfolio analysts' existing harvesting decisions — how they evaluate loss thresholds, which substitute securities they prefer for each index exposure, how they balance round-trip transaction costs against expected tax benefit. The deployed agent monitors direct indexing positions in Orion and Bloomberg throughout the trading day, evaluates unrealized losses against cost basis and your configured harvest thresholds, checks wash sale rules across related holdings, and generates compliant substitute security trade instructions when a viable opportunity exists. Instructions route to a portfolio manager for review before execution — the agent identifies and prepares, your team decides.

What Capturing Intraday Windows Is Worth

This use-case is fundamentally a revenue and product story, not a cost reduction story. Direct indexing platforms compete on after-tax return delivery; demonstrated TLH alpha is a key retention and acquisition driver for high-net-worth clients. An agent that monitors intraday rather than monthly captures volatility-driven harvesting events that monthly processes miss entirely. The efficiency improvement on ops labor is real — typically 65–85% reduction in manual monitoring time — and the agent is typically live in about 5 weeks. But the client-facing value is in after-tax outcomes: accounts that harvest more systematically produce better after-tax performance, which is the core promise your platform is selling.

Works with
OrionBlack DiamondSnowflakeBloombergSalesforce Financial Services CloudCharles Schwab Advisor Services
Questions

How does the agent handle the 30-day wash sale window across related accounts?

The agent evaluates wash sale exposure across all accounts in the household, not just the account being harvested. It identifies substitute securities with similar factor exposure to the sold position and verifies that the substitute doesn't trigger a wash sale from a recent purchase elsewhere in the household. The complete compliance check is documented in the trade instruction packet routed to the portfolio manager.

Can we configure minimum loss thresholds and transaction cost hurdles before the agent flags an opportunity?

Yes. The agent operates against configurable parameters for minimum loss size, round-trip transaction cost hurdle, and minimum tax benefit net of costs. These can be set at the account level or applied uniformly across the platform, and your team can adjust them as your methodology evolves.

Related use cases

Illustrative scenario for financial services, banking & insurance. Figures are example ranges, not guarantees — we scope real numbers with you on a call.

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