1) Build vs license: the honest decision framework
Platforms like MT5/cTrader dominate because they solve not just the UI — they solve connectivity, execution workflows, operational tooling, and ecosystem dependencies. For most brokers, the fastest path to revenue is licensing.
License when:
- You need to launch in weeks, not months.
- Your competitive edge is marketing, sales, or distribution — not execution micro-architecture.
- You don't yet have a specialized team for OMS, risk, FIX sessions, and 24/7 operations.
Build when:
- You need a proprietary UX and product flow that licensors can't support.
- You need unique execution / routing logic or specific asset classes.
- You want full control of roadmap, integrations, data model, and unit economics at scale.
- You accept that the first version won't be perfect — and you can invest in iteration.
The most successful approach is usually hybrid: license to launch, then progressively build your own core capabilities (client portal, back office workflows, risk, analytics, data pipelines) while keeping execution stable.
2) What a trading platform actually is (not just charts)
A real trading platform is a set of services that must be correct under stress: spikes, outages, partial fills, price gaps, network jitter, and adversarial behavior.
Minimum platform modules
- Market data: symbol specs, quotes, spreads, tick snapshots, streaming updates
- Order Management System (OMS): order lifecycle, states, retries, idempotency
- Execution adapters: FIX sessions or bridge connections to liquidity providers
- Risk engine: pre-trade checks (margin, limits), post-trade monitoring, exposure
- Accounts/positions: balances, margin, PnL, open/closed trades
- Wallet/ledger: deposits/withdrawals, adjustments, reconciliation with PSPs
- Client portal: onboarding, KYC, funding, account actions, statements
- Admin/back office: approvals, risk controls, routing rules, support tooling
- Observability: logs, metrics, tracing, alerting, audit events
3) Reference architecture (high-level)
The goal is to separate "what the client asked for" from "what the market executed" and from "what we record internally". This makes the system resilient and auditable.
Core data flows
- UI → API Gateway: auth, rate limits, session control
- API → OMS: create order intent, validate, route
- OMS → Risk: pre-trade checks, margin, limits
- OMS → Execution Adapter: submit to LP via FIX or bridge
- Execution → OMS: acks/fills/rejects (idempotent handling)
- OMS → Ledger: finalize positions, fees, adjustments
- Market Data → WebSocket: broadcast quotes to clients
Storage choices (pragmatic)
- PostgreSQL: canonical state (users, accounts, orders, ledger)
- Redis: sessions, rate limits, ephemeral quote cache
- ClickHouse: analytics, tick history, aggregated reports
4) Connectivity: FIX, WebSockets, data feeds, bridges
Your client app typically uses REST/WebSockets. The market typically uses FIX. You need both.
WebSockets (UI streaming)
- Design for reconnects and backpressure.
- Use snapshot + incremental updates (don't rely on only ticks).
- Throttle and batch updates per symbol group (performance & mobile).
FIX API (liquidity & execution)
FIX looks simple until you run it in production: sequence numbers, resend requests, disconnect storms, partial fills, cancels, and session-level edge cases.
Your platform might implement FIX directly, or it might integrate through a bridge/aggregator. If you're already building a platform, plan FIX as a dedicated "connectivity layer" with strong observability.
You can also position your technical depth by linking to your API pages: FIX API, WebSockets, Data Feed
5) Security & compliance realities
A custom platform increases your responsibility. You're not just building features — you're building controls. Account takeover and payout fraud are real; audit trails and role separation are mandatory.
- Authentication + optional 2FA
- Session/device management
- Rate limiting + WAF rules
- Immutable audit events for KYC and payouts
- Secure document storage for KYC
6) Team, roles, and timelines
If you want a realistic build, treat this like building a fintech product. The minimum team is not "two full-stack devs".
Typical roles
- Trading systems architect: OMS, risk, execution models
- Backend engineers: OMS, ledger, integrations (FastAPI/services)
- Connectivity engineer: FIX sessions, bridge integration, performance
- Frontend engineers: trading UI, order ticket, account UX
- QA automation: market scenarios, edge cases, regression suites
- DevOps/SRE: deployments, monitoring, incident response
Timelines (realistic)
- MVP: 6–9 months with an experienced team
- Production-grade platform: 12–18+ months (multi-asset + mature ops)
7) Cost ranges (and why it's expensive)
The cost is not only engineering salaries. It's also reliability work, test infrastructure, security, compliance, and ongoing operations.
- Small MVP team (6–10): typically $60k–$200k/month depending on location and seniority
- Production platform team (12–25+): $150k–$500k+/month
- Timeline multiplication: if you don't have FIX/OMS specialists, time increases sharply
8) AI/ML: where it helps (and where it doesn't)
AI is useful when it reduces operational load and improves risk outcomes:
- Fraud detection signals (behavior anomalies, device patterns)
- Support triage, knowledge base, auto-summaries
- Incident detection (log/metric anomaly detection)
AI does not replace execution correctness. Execution quality is infrastructure + liquidity + controls.
9) A realistic phased roadmap
Phase 1: foundation
- Accounts, auth, roles, audit logs
- Market data snapshots + WebSocket streaming
- Demo trading / paper trading workflow
Phase 2: first live execution
- OMS + risk checks
- Single LP integration via FIX/bridge
- Basic order types + trade history
Phase 3: operations
- Ledger + deposits/withdrawals + reconciliation
- Support tooling + compliance workflow
- Monitoring + alerts + incident runbooks
Phase 4: scale
- Multi-LP routing + failover
- Advanced risk controls + limits
- Analytics pipelines + performance dashboards
10) Outsourcing vs in-house: how to de-risk the build
If you're starting from zero, outsourcing to a specialized team often reduces risk. The key is structure: milestones, measurable deliverables, and continuous demos.
Our recommended engagement style
- Discovery: requirements, execution model, asset scope, compliance needs
- Architecture: services, data model, protocols, observability plan
- Milestones: phased delivery with test criteria
- Operational readiness: monitoring, incident response, audit trails
If you want to explore this seriously, start with a focused call. We'll map your target platform scope to a realistic plan: Talk to Brokeret