Robo-Advisory Platform — WealthTech Startup (USA)
Visual: portfolio construction screens, risk profile wizard, and advisor hybrid dashboard.
Client Overview
A US-based WealthTech startup offering automated investment portfolios to retail investors and a hybrid advisor channel for higher-net-worth clients. The startup needed scalable portfolio construction, automated tax-aware rebalancing, and a simple advisor override path.
Challenge
The startup required a rules-based portfolio engine with data-driven risk profiling that could scale and remain compliant with custody integration. They also wanted tax-aware rebalancing logic and a clear path for advisors to customize allocations for clients.
Solution — Scalable Portfolio Engine & Advisor Layer
We built a modular portfolio engine that separates strategy definition, risk profiling, order generation, and execution connectors to custodians. Tax-aware rebalancers and advisor-override layers allowed flexibility across customer segments.
Core modules
Approach
- Define target strategies with investment committee and legal for compliance guardrails.
- Implement simulator to measure tracking error, tax impact, and operational cost of rebalancing alternatives.
- Integrate with custodian APIs for order placement and reconciliation.
- Run pilot with advisor cohort and iterate on UX and override controls.
Technology stack
Implementation — Delivery Phases
Phase 1 — Strategy & Simulation (Weeks 1–6)
Build simulators for model portfolios and rebalancing scenarios to choose the tax-efficient strategy for pilots.
Phase 2 — Engine & Custodian Integration (Weeks 7–16)
Implement order generation, custody connectors, and reconciliation pipelines with test harnesses.
Phase 3 — Advisor Layer & Pilot (Weeks 17–28)
Develop advisor portal with overrides and audit logs; onboard pilot advisor firms and collect UX feedback.
Phase 4 — Production & Scale (Weeks 29–36)
Operational scaling, monitoring of tracking error, and automated monthly rebalancing operations.
Impact & Results
30%
Increase in AUM (pilot to production)
95%
Rebalancing efficiency (reduced realized gains)
Short
Time to generate and reconcile orders (automation)
Positive
Advisor satisfaction with override controls
Qualitative outcomes
- Automated rebalancing reduced operational cost and tax drag for clients.
- Advisors could tailor client allocations with compliance fences and audit trails.
- Faster onboarding and portfolio provisioning improved client experience.
Client Testimonial
Key Highlights & Learnings
- Simulations drive the right trade-offs for rebalancing cadence and tax optimization.
- Advisor override controls must include strong audit trails for compliance.
- Custodian integrations should be abstracted with robust test harnesses for reliability.