Fill Confirmer
Auto-reconciles retail traders' brokerage statements against quote data to quantify invisible slippage, then ranks brokers by real execution quality.
Active retail stock and ETF traders using online brokerages
- Drag-and-drop brokerage CSV/PDF statement importer
- Side-by-side comparison of your fills versus NBBO midpoint at order time
- Broker reliability scoreboard based on community-anonymized execution data
- Monthly slippage dollar report with cost-per-trade breakdown
HN's recurring Java latency debate shows how often low-latency backends regress; that fragility hits retail traders directly as bad fills during news spikes and market opens.
Multiple dedicated slippage/execution-quality tool pages exist (takeprofitapp guide, clearank auditor) and trade-journal tools with execution analytics (Edgewonk, TradeZella) actively market to retail, indicating real, sustained interest among active retail traders.Slippage Analysis Tools 2026 — Broker Execution Guide ↗Edgewonk Trading Journal ↗
Clearank already offers essentially the same product (forensic broker fee & slippage auditor that ingests CSV trade history and grades execution); Edgewonk/TradeZella also surface execution metrics inside broader journals, leaving a thin direct wedge for a clean exit-quality ranking product.Slippage Calculator & Broker Fee Analyzer (Free) ↗Edgewonk Pricing Explained: All Plans, Costs & Fees (2026) ↗
Retail traders do pay $40–200/yr for trade journaling (TradeZella/Edgewonk tiers), but Clearank positions its slippage auditor as free and execution-quality is a niche add-on rather than a must-pay feature — willingness-to-pay for a standalone reconciler is unproven.TradeZella Pricing ↗Slippage Calculator & Broker Fee Analyzer (Free) ↗
Broker execution quality is a structural concern (broker routing, payment-for-order-flow, requotes) that persists across regimes; the underlying SEC Rule 606/605 disclosures are coarse, so a finer-grained independent tool remains durably useful, though the Java-latency 'why now' trigger is a weak proxy for retail demand.
Core difficulty: reconciling every fill against sub-second quote data for US stocks/ETFs requires costly consolidated-tape data at scale, and parsing the fractured statement/csv formats of TD, Schwab, Robinhood, IBKR, etc. is heavy maintenance; the analytical back-end is feasible but the data and onboarding plumbing is non-trivial.